Emotion-oriented Requirements Engineering: A Case Study in Developing ASmart Home System for the Elderly

Maheswaree Kissoon Curumsing , Niroshinie Fernando, Mohamed Abdelrazek, Rajesh Vasa, Kon Mouzakisa, JohnGrundyb

aSchool of IT, Deakin University, Geelong, AustraliabFaculty of IT, Monash University, Melbourne, Australia

Abstract

Smart home technology has received growing interest in recent years with a focus on automation and assistance,for example, Alexa, Google Home, Apple HomePod, and many cheap IoT devices. Better supporting elderly peopleto continue live in their home using smart home technology is a key target application. However, most of the existingsmart home solutions for the elderly are not designed with people’s emotional goals in mind, leading to lack of adop-tion, lack of engagement, and failure of the technology. In this paper, we introduce an emotion-oriented requirementsengineering approach to help identifying, modeling and evaluating emotional goals. We also explain how we usedthis technique to help us develop SofiHub - a new smart home platform for elderly people. SofiHub comprises a rangeof devices and software for sensing, interaction, passive monitoring, and emergency assistance. We have conductedmultiple trials including initial field trials for elderly people in real houses. We have used our emotion-oriented re-quirements techniques to evaluate the participants’ emotional reactions before, during, and after trials to understandthe impact of such technology on elderly people’s emotions to the Sofihub solution. Our analysis shows that SofiHubsuccessfully alleviates their loneliness, makes them feel safer and cared about. We also found that the trial participantsdeveloped a strong relation with the system and hence, felt frustrated when SofiHub did not respond in ways expectedor desired. We reflect on the lessons learned from the trials related to our emotion-oriented design and evaluationexperimental approach, including refining our set of evaluation tools.

Keywords: Smart Home, Elderly, Independent Living, Emotions, Loneliness, Emotion-Oriented developmentapproach

1. Introduction

Software professionals often design a product that re-alizes the set of desired functional and non-functionalgoals based on their understanding of the system, re-sulting in an end-product which fails to fulfill the needsof its intended users. A growing concern, as pointed outin the literature [1, 2, 3, 4] is that software engineers failto give adequate consideration to user’s emotional needswhen designing systems, leading to unhappy end-users.Even though the consideration of emotion is becomingpredominant in the area of design, including human-computer interaction, this consideration has not been

Email addresses: {m.curumsing, niroshinie.fernando,

mohamed.abdelrazek, kon.mouzakis,

rajesh.vasa}@deakin.edu.au (Maheswaree Kissoon Curumsing, Niroshinie Fernando, Mohamed Abdelrazek, Rajesh Vasa, KonMouzakis), john.grundy@monash.edu (John Grundy)

successfully mapped to the software engineering field[5]. Evidence [1, 2, 6, 7], on the other hand, suggeststhat user emotions are a key determinant in the accep-tance of a technology, particularly with regards to do-mestic and social systems.

Home-based age-care has emerged as a key alterna-tive to address the growing burden of aged care and el-derly people generally prefer to stay at home and enjoytheir privacy and independence. However, this intro-duces a substantial burden on the government to fundand develop enough skilled staff (such as nurses) to lookafter the growing number of older adults. Smart hometechnology introduces a promising solution to this prob-lem with the aim to help elderly people stay at homeand live independently while maintaining a good qual-ity of life for far less cost and human resources. Eventhough several smart home technologies already exist inthe market, evidence suggests that many elderly people

Preprint submitted to Journal of Systems and Software June 27, 2018

are not fully keen on using these systems [1, 2, 5]. Oneof the major reasons identified for this lack of interestpoints towards the failure to consider human, social andorganizational factors along with technical factors whenbuilding such systems [1, 2, 5, 8].

Building socio-technical or people-oriented systemssuch as smart home technologies has never been morechallenging with the increasing need to understand thesocial requirements of users. As social beings, usershave emotional needs, such as to be independent, tofeel cared about and feel secure. Given that theseneeds cannot be easily converted into functional or non-functional requirements using the existing software en-gineering methodologies, they are often ignored or triv-ialised within the current software development pro-cesses [9]. These social needs, which we refer to as“users’ emotional goals” [10], are critical to the ac-ceptance of a system and therefore should not be ig-nored. The emotional goals we refer to in this paperare sometimes referred to as ”affective or cognitive re-quirements”. In this work we use the term ”emotionalrequirements” as a simple term easy to understand by awide-spectrum audience.

Existing efforts [10, 11, 12, 5] have highlighted theimportance of considering users’ emotional expecta-tions from the inception phase of the software project.They also presented a set of emotion-oriented tech-niques to capture, model and evaluate users’ emo-tional goals. We followed a similar emotion-orientedapproach to develop a new smart home solution –called SofiHub – designed to support independent liv-ing among elderly people, thus addressing a key prob-lem of aging population. This technology was designedas an ambient system using non-intrusive motion sen-sors to alleviate elder people’s concerns regarding theirprivacy, and also ‘feeling old’ when they have to putwearables on.

Research Questions. In this paper, we focus on threekey research questions:

• RQ1: What are the key emotional requirementsbeyond the classical functional and non-functionalrequirements that can help us design software?

• RQ2: What methods are appropriate for imple-menting these emotional requirements in a soft-ware engineering project?

• RQ3: In what ways can we validate our softwaresolution against the emotional requirements?

In order to address these research questions, we haveused our emotion-oriented techniques developed earlier

[10] to identify and model users’ pain points, and cameup with an emotion model and goal model. We thenused the goal model to guide the design and implemen-tation of SofiHub. The goal model was then used toguide the design of our trials to make sure that we cap-tured participants’ emotions as part of the survey andinterviews, that we conducted before, during and afterthe trials.

In this paper, we reflect on the implications of usingan emotion-oriented design approach to develop Sofi-Hub taking into consideration people’s emotions. Wealso discuss the emotion related findings from the tri-als testing the system, within the homes of 10 partic-ipants. In particular, we focus on evaluating the longterm impact that smart homes, such as SofiHub, canhave over people’s emotions and their willingness toadopt the technology over time. The timeline for ourtrial was conducted over only three months but our anal-ysis shows that SofiHub improves and amplifies the af-fordances of a home (compared to a ‘dumb’ home) [13].In addition, it addresses users’ emotional expectationsfrom such systems.

Contributions. This paper has the following contri-butions:

• An industrial case study of using an Emotion-oriented Requirements Engineering approach tothe design of a Smart home emotion model andgoal model. The emotion model captures users’pain points and translates them into a set of goals.The goal model represents the key emotional goalsthat need to be taken into consideration whenbuilding a smart home technology.

• A smart home solution that has emotions as a firstclass citizen, with detailed descriptions of howSofiHub was designed with emotional goals inmind.

The rest of this paper is organised as follows: In sec-tion 2, we outline the key efforts in smart home tech-nologies, and highlight the need to consider emotionswhen designing smart home systems. In section 3, wepresent an overview of the set of emotion-oriented re-quirements engineering techniques that were used to de-sign SofiHub. In section 4, we describe the features ofSofiHub, present the protocol used for the trial, identifythe emotional goals and discuss the key relevant deci-sion rationale. In section 5, we describe our evaluationprocess, key findings and the implications of these find-ings on the next generation of SofiHub. In section 6, wediscuss the threats to validity and in section 7, we reflecton our findings and emotion-oriented approach.

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2. Background

2.1. Role of Emotions within Smart Home Systems

Most applications and devices targeting elderly usershave a focus on offering transactional services for users’functional goals. However, their effect on users’ emo-tional goals are not clear, even though emotional goalsplay a key part in user acceptance and adoption. Portetet al. [14] discusses a case study of smart homes forelderly users, where some elderly users were hesitantto use automated functions (such as opening blinds inthe morning) because they feared that automating partsof their daily routines would leave them with nothingto do, and make them feel useless. In this case, eventhough the functional goal of the system was accuratelyimplemented, it contradicted the users’ emotional goals(independence and feeling useful).

Moreover, unlike typical software, smart home sys-tems are intended to be part of a user’s ‘home’, whichinherently has strong emotional connotations [13, 15].It is therefore vital that the role of emotions be consid-ered in the design and development of software used insmart home systems.

A growing concern can be found in literature sur-rounding the adoption of technology by the elderly peo-ple where researchers [3, 16, 17, 1, 2] point out that soft-ware engineers fail to give adequate consideration tousers’ emotional needs when designing systems, lead-ing to unhappy end-users. Users’ emotions – which re-late to the way users feel or how they want to feel –are rarely explicitly considered in software development[18, 19, 20, 21, 3]. Evidence, on the other hand, sug-gests that users’ emotions play a determining role in theacceptance of a technology, particularly with regards todomestic and social systems [18, 19, 20, 16, 17, 1, 2, 7].

Several studies in the area of socio-technical systemsfor the elderly have highlighted the importance of users’emotions during system design [1, 22, 2]. For exam-ple, a study conducted by Demiris et al. [1] investigatedthe way older adults perceive smart home technologiesinstalled in their homes. The findings revealed issuesrelated to violation of privacy and independence whichrefer to the way the users feel about the system. Anotherstudy by Pedell et al. [2] was geared towards the is-sues that older adults face when using emergency alarmpendants. Issues such as lack of independence, feelingold, frail, stigmatised and uncared for were some ofthe most common comments found from the interviewsconducted with those older adults. The findings alsoshowed that these people wanted to feel connected totheir loved ones and cared about. These issues and ex-pectations clearly do not relate to a functional or quality

goal of a system. They refer to the emotional expecta-tions that users have from the system. Given that theseemotional issues act as barriers to the adoption of tech-nology, they cannot be ignored and have to be somehowreflected in the design of the technology.

These findings reiterate the need to address users’emotional goals when designing socio-technical sys-tems. Addressing user’s emotional goals in softwaredesign entails a number of challenges. First of all, emo-tion in itself is a very complex and subjective concept,making it hard to capture and measure [23, 11]. In ad-dition, existing software methodologies barely addressthe concept of user emotional expectations [5, 10]. Thisleaves software engineers with little guidance on howto incorporate user emotional expectations within theirexisting software development life cycles.

While emotion is a well-researched topic in disci-plines such as design (including human computer inter-action), affective computing and information systems, ithas been barely explored in the area of software engi-neering. The literature involving emotion and softwaredevelopment is mainly focused on requirements gather-ing and modelling [24, 25, 4, 26, 27, 28]. For example,Thew and Sutcliffe [26], Sutcliffe and Thew [27] andSutcliffe [28] referred to people’s feelings as ‘soft is-sues’ and argued how vital it is to consider user beliefsand values for the success of a software. They proposeda taxonomy consisting of a set of values and motiva-tions and determined the severity of their impact on therequirements. Proynova et al. [29] considered personalvalues to find requirements which may have remainedhidden. In the area of requirements modelling, Yu [30]proposed the i* framework with an attempt to repre-sent some aspects of social modeling which they termedsoft goals. Along with the traditional non-functionalrequirements such as “reliability”, soft goals such as“trustworthy”, which are more aligned with user emo-tional expectations, were also represented. In this per-spective, the work of Ramos et al. [4] is better alignedwith our approach in that they present examples ofprojects failing due to requirements being affected byemotions. They further advocate the need to identifysuch issues as soon as they arise and to handle themthrough a number of psychological techniques. In an-other work, Miller et al. [5] evaluated the i* modelsagainst a set of people-oriented software engineering(POSE) models to represent people’s needs into require-ments engineering models. Their results revealed that“participants understand POSE models better and morequickly, prefer POSE models as boundary objects formodelling socio-technical systems, and prefer the useof explicit emotional goals in models over our previous

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approach of using quality goals to represent these socialaspects.” [5]

Miller et al. [5] and Lopez-Lorca et al. [31] adapt thework of Marshall [32] to the area of software engineer-ing. In this context, Miller et al. [5] refers to emotionas a feeling that characterises a state of mind and in-cludes examples such as feeling of joy, terror or safety.Based on this definition, an emotional goal is definedas “the way people feel about a system and also cap-tures their engagement in the greater socio-technicalsystem”. Miller et al. [5] further categorise emotionalgoals into two types, namely personal emotional goalsand system-dependent emotional goals. Personal emo-tional goals refer to “the way a person wants to feel suchas feeling loved, safe or angry” and are independent ofthe existence of a system. System dependent emotionalgoals refer to “the way a person feels about a systemfor example, feeling engaged or frustrated with the sys-tem”. Unlike personal emotional goals, system depen-dent emotional goals rely on the existence of the systemand if the system is removed, these emotional goals areeliminated.

While there has been some early progress on incor-porating the concept of emotion in software solutions[24, 25, 4, 26, 28], to the best of our knowledge, thereis no structured software methodology or framework tocapture, model and incorporate user emotional goalswithin the software development life cycle. In a re-cent work [10], one of the authors, presented a set ofemotion-informed techniques to capture, represent andevaluate user emotional expectations. These techniqueswhich build upon the work of Miller et al. [5], Lopez-Lorca et al. [31] and Marshall [32] were applied andtested within three case studies in different domainswith different stakeholders. In this work, we apply thesame set of techniques to the design and evaluation ofour smart home technology for the elderly. The nextsection discusses these emotion-oriented techniques inmore details.

3. Emotion-Oriented Software Engineering

3.1. Emotions and Emotional Goals

Table 1 provides a summary of some of the classifica-tions of emotion over time [10]. This highlights the dif-ferent classifications of emotion as presented within dif-ferent disciplines such as psychology, philosophy, neu-roscience, medicine and computer science.

An important finding is that the terms used to identifyemotion such as anger, disgust, fear, joy, sadness andsurprise do not relate to user emotional expectations.

Our long-term focus is to incorporate such user emo-tional expectations within the software development lifecycle, in order to ensure that users’ emotional needsare addressed by the software. For example, some useremotional expectations for a particular system, such asa smart home technology, could be “feeling cared for”,“feeling connected” and “feeling independent”. Theseterms do not fit under any of the classifications of emo-tion listed in Table 1. Our work described in this paper isa preliminary approach to eliciting, modelling and rea-soning with such emotional goals in software engineer-ing.

For instance, how do we map “cared for” to a list ofemotions consisting of terms like anger, disgust, fear,joy, sadness and surprise. Even though user emotionalexpectations relate to the way users feel or want to feel,they are not emotions. User emotional expectations re-late mainly to the way users perceive the end product.For instance, the term “feeling cared for” depends onhow the users think that using a software can make them“feel cared for”. Given the subjectivity and complexityof emotion, there is no way to guarantee that users willactually feel cared for after using the end-product. Itall depends on the way they perceive the system. Useremotional expectations are therefore more complex thansimple emotions since they relate to the affective andcognitive requirements of the user. As mentioned in theintroductory section of this paper, we use the term emo-tional goals as a simple term easy to understand by awide-spectrum of audience and to align our work withprevious work [5, 31, 32, 10] in the area.

Based on the analysis of the different theories of emo-tion, in one of her previous work [10], the first author ar-gues that while most theorists agree that the four com-ponents, namely cognitive processes, affect or subjec-tive feelings, physiological arousal and behavioural re-sponses are important, debate is still going on regard-ing the mandatory presence of all four of them in everyemotional event and the sequence in which they shouldoccur. Different theories of emotion have been proposedover time which elaborate on the different sequence ofcomponents related to emotion, but in general most the-orists agree that perception is at the beginning of eachsequence of components. That is, perception is gener-ally accepted as the trigger for an emotion. Hence, ourconsideration of perception is justified. In our work,users’ emotional expectations or users’ emotional goalsrefer to how users perceive the end product.

When asked about what they want from a system,users very often tend to describe their expectations byhighlighting features that they do not want. In otherwords, they describe their requirements in terms of pain

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Table 1: Classification of EmotionsTheorist Reference #Emotions Basic EmotionsPlutchik Plutchik [33] 8 Acceptance, anger, anticipation, disgust, joy,

fear, sadness, surpriseArnold Arnold [34] 11 Anger, aversion, courage, dejection, desire, de-

spair, fear, hate, hope, love, sadnessEkman, Friesen, andEllsworth

Ekman et al. [35] 6 Anger, disgust, fear, joy, sadness, surprise

Frijda Frijda [36] 6 Desire, happiness, interest, surprise, wonder,sorrow

Gray Gray [37] 3 Rage and terror, anxiety, joyJames William [38] 4 Fear, grief, love, rageMatsumoto Matsumoto et al. [39] 22 joy, anticipation, anger, disgust, sadness, sur-

prise, fear, acceptance, shy, pride, appreciate,calmness, admire, contempt, love, happiness,exciting, regret, ease, discomfort, respect, like

McDougall McDougall [40] 7 Anger, disgust, elation, fear, subjection, tender-emotion, wonder

Mowrer Mowrer [41] 2 Pain, pleasureOatley and Johnson-Laird

Oatley and Johnson-laird [42]

5 Anger, disgust, anxiety, happiness, sadness

Panksepp Panksepp [43] 4 Expectancy, fear, rage, panicParrott Parrott [44] 6 anger, fear, joy, love, sadness, surpriseTomkins Tomkins [45] 9 Anger, interest, contempt, disgust, distress,

fear, joy, shame, surpriseWatson and Rainer Watson and Rayner

[46]3 Fear, love, rage

Weiner and Graham Weiner and Graham[47]

2 Happiness, sadness

points or in terms of negative emotions [31], for ex-ample, “I don’t want to feel old” and “I don’t wantto feel dependent on others”. In recent work [10], thefirst author describe how these negative emotions can bemapped to one or a group of functional, quality and/oremotional goals that the system should achieve in orderto document and then counteract these negative emo-tions through an emotion model. We refer to these painpoints as ‘emotional threats’. They help to maintaintraceability between negative emotions, identified dur-ing the elicitation process, and the system’s goals.

3.2. Emotion-Oriented Methods

In this section, we describe the emotion-orientedtechniques, which were used (i) during the design anddevelopment of the Sofihub technology, (ii) to analysethe data collected from the Sofihub trial and (iii) to iden-tify any new requirements arising from the findings ofthese trials. The next section describes how these tech-niques were applied within the different developmentstages of SofiHub. Figure 1 illustrates the emotion-oriented development approach used for this case study.

3.2.1. Emotion-Oriented Requirements ModellingIn one of the first author’s previous work [12], a

comprehensive set of emotion-oriented models were de-signed to support early-phase requirements to detaileddesign to demonstrate how to capture the viewpointsof stakeholders, in particular the emotional viewpoints,throughout the entire process. Earlier agent-orientedmodels were extended to represent three types of goalsnamely, functional, quality and emotional. A compre-hensive explanation of the syntax and semantics of thesemodels is available in Miller et al. [5].

Table 2 summarises the modelling suppport we usefor this Emotion-Oriented Requirements Engineering(EORE).

Role ModelThe role model enables us to model key user roles in

the system and associate emotional goals and expecta-tions with each role. For example, in our smart homesystem scenario key roles include cared-for ageing per-son, family member, professional carer, and mainte-nance personnel. The expectations of the older adult is

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Figure 1: Emotion-Oriented Development Processes

to feel cared about, safe, independent, in touch and un-burdened of the obligation of routinely getting in touchwith their relative/carer (personal emotional goals). Inaddition to that, they want a system that feels integratedin their life and they also want to feel in control of thesystem (system-dependent emotional goals).

Goal ModelThe goal model represents the functional goals of the

system to be developed along with any quality and emo-tional goals linked to the functional goals. The goalmodel is a valuable tool widely used during discussionswith stakeholders. It provides an overall picture of thesystem in terms of its goals (functional, quality andemotional) and roles associated to these goals. It alsorepresents how each functional goal can be further de-composed and shows the link between the quality, emo-tional and functional goals. The model also identifiesthe quality goals and emotional goals attached to eachparticular functional goal.

In this model we represent a set of functional goals,broken into tasks and sub-tasks, with associated rolesand emotional impact of performing the tasks on therole(s) associated with them. This is a sub-set of whatcould be described generally as ”emotional require-ments” of software systems i.e. is task-oriented and fo-cuses on emotional impact of tasks/sub-tasks on users.

A high level modelling icon set was developed to rep-resent the different goals as illustrated in Figure 2 wherethe conventional parallelogram and the cloud was usedto represent the functional and quality goals respec-

tively. The heart shape was introduced to represent theemotional goals. In this work, we briefly describe twoof those models which we applied in our case study. Adetailed description of the models we used can be foundin [5].

Figure 2: Icon set for functional, quality and emotional goals

Figure 3 provides a meta-model for our goal modelsused in the case study in this paper. A set of Roles andGoals are linked. Goals may be Functional, Quality orEmotional goals of the system or user. Sub-functionaland Sub-quality goals allow for refinement of models.Emotional goals may be positive or negative, that is, re-flect positive reactions or negative reactions to the sys-tem and its features. Each role has a set of emotionalgoals they need to have either fulfilled (positive) oravoided/minimised (negative) in the system being mod-elled. Multiple emotional goal models are used for largesystems.

A number of checks can be performed on theemotion-oriented goal models relating to completeness,correctness, and consistency.

• completeness checks

– all emotional goals should be associated to a

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Table 2: Emotion-oriented Requirements Engineering enhanced models

Model Description Emotional Goals Captured

Role Model provides an overview of the different roles involved in thesystem by listing out the responsibilities, constraints andemotional goals associated with each role

personal emotional goals

system-dependent emotionalgoals

Goal Model represents the functional goals of the system to be devel-oped along with any quality and emotional goals linked tothe functional goals

positive emotional goals

negative emotional goals

Motivational Scenarios high-level purpose of the overall system including functional,quality and emotional goals

emotional description

Interaction Model describes the interactions between agents making up the sys-tem

annotated interactions with pos-itive emotionsannotated interactions with neg-ative emotions

Scenario Model describes collective activity of how goals are achieved in sys-tem

rows to describe generally theemotional goals achieved by thescenariocolumns for each activity tohighlight the relevant emotions

Behaviour Model describes what individual agents do in the system annotations on states to modelrelevant emotions

Figure 3: Meta-model for the emotion-based goal model

role, for instance, in our case study, the emo-tional goals safe, independent, empowered, incontrol, integrated, comfortable and privacysecured are associated to the elderly personwhile the emotional goal reassured is associ-ated to the carer/relative;

– all emotional goals should be related to atleast one functional and/or quality feature ofthe system, for example, in the goal modelrepresented in Figure 5, the emotional goalreassured is linked to the functional goal sup-port independent living, which implies thatcarers/relatives feel reassured if the system isable to support independent living;

– all functional goals should be refined to ap-propriate sub-goals, for instance, in our smarthome case study, the functional goal supportindependent living is decomposed into learnuser’s routine and behaviour which is fur-ther decomposed into issue notifications andlearn user’s routine and behaviour;

– any missing emotional goals should be de-tected. This can be done during the processwhere the goal model is validated with keystakeholders of the system;

• correctness checks

– constraints as to which emotional goals can

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be linked to which functional and qualitygoals need to be checked, for instance, in ourSofiHub scenario, the emotional goal safe islinked to the goal detect anomaly because el-derly people feel safe knowing that in caseof an anomaly such as a fall, the system willdetect the anomaly and escalate the incidentto the service provider and/or carer. Simi-larly, carers/relatives feel reassured knowingthat the service provider is supporting theirelderly relatives in their day to day living;

• consistency checks

– conflicting functional, quality and emotionalgoals should be resolved, for instance captur-ing people’s movement while ensuring thatthey feel independent;

– conflicting emotional goals, for example,positive and negative emotion for the samesub-goal should be resolved;

Examples of goal models for our smart home scenarioare given and described later in this paper. The otheremotion-augmented modelling techniques outlined be-low have also been enhanced with this approach.

Motivational ScenariosMotivational Scenarios provide the high-level de-

scription of the purpose of the system in terms of func-tional, quality and emotional goals. It reflects how theagents enacting a particular role are going to achievethe goals assigned to them. For example, in our smarthome scenario we have an overarching goal of provid-ing technology-support care via passive monitoring. Wecapture scenario descriptions from carer, relative and el-derly adult viewpoints including quality goals. We alsocapture emotional goals such as reassurance of well-being (family), adherence to medication and exercise(carer), and independence and safety (elderly adult).

Interaction ModelThe interaction model represents a set of interac-

tions that exist between the different agents within thesystem. It is expected to have several interaction modelsfor a particular system whereby each model representsa particular scenario or functionality of the system. Wemodel this on UML-style sequence diagrams and anno-tate the interactions between system and user with ap-propriate emotional goals to document where these im-pact usage. For example, in our smart home scenariowe capture potential anxiety around elderly adult and

remembering to take medication, and security for rela-tive provided by the medication reminder function.

Scenario ModelsA scenario is a behaviour model which represents a

collective activity that models how a particular goal isachieved by agents enacting particular roles. A systemcan have more than one scenario depending on its com-plexity and number of functionalities involved. Eachscenario provides information about a particular func-tionality by identifying the associated quality and emo-tional goals, the initiator of the function, how the func-tion gets triggered and the set of activities linked withthis function. We added rows and columns to captureemotional goals associated with activities. For exam-ple, when the system calls for help in terms of a de-tected anomaly, emotional goals such as safety is beingcontributed to.

Behaviour ModelsA behaviour model focuses on what individual

agents do within the system. There are two kinds ofbehaviour models namely behavioural interface modelsand agent behaviour models. The behavioural interfacemodel captures the different behavioural units (activity)and interface (trigger, pre-condition and post-condition)for each unit. The agent behaviour model describes thebehaviour of an agent in terms of rules and triggeringmessages. We annotate with additional rows to capturerelevant emotional goals for activities, triggers and con-ditions.

3.2.2. Emotion-Oriented Requirements Elicitation Pro-cess

We make use of an adaptation of two existing tech-niques, namely content analysis [48] and affinity dia-gram to elicit emotion-oriented requirements [10]. Con-tent analysis is a technique for analysing content thatmay consist of words, meanings, pictures, symbols,ideas, themes, or any message that can be communi-cated [48]. The text is searched for recurring wordsor themes to identify core consistencies and mean-ings. Content analysis involves identifying, coding, cat-egorising, classifying and labelling primary patterns inthe data. The coding process starts with a complete viewof all the collected data. In the initial reading, the an-alyst can start visualising some coding categories andpatterns but the actual coding occurs in the second read-ing. Content analysis relies on the skill of the analystin being able to recognise patterns in the data and beingable to find appropriate terms to label them.

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During the analysis session, an affinity diagram isthen used to organise the identified patterns and codesinto a hierarchy to draw higher-level concepts out ofthe data [49, 50]. The patterns and codes are groupedtogether by related themes to create a story about thephenomena studied [51]. The affinity diagram is builtbottom up. Individual ideas are grouped into commonthemes, suggesting categories to which they belong, us-ing an inductive process.

3.2.3. Emotion-Oriented Design and ImplementationIncorporating users’ emotions during the software de-

sign and development phases is an area that has onlybarely been explored to date and no well defined tech-nique has yet been proposed to incorporate emotionalgoals during the design and implementation phases.Personas have been used to bridge the gap between therequirements and design phases but nothing beyond thathas so far been mentioned [10].

Our team is currently exploring ways to formalisethe process of including emotional goals during the de-sign and implementation phases. In this case study, theusers’ emotional goals were communicated to the engi-neers through the emotion and goal models. We alsoconducted discussions and workshops to ensure that theengineers (i) understood the importance of each goaland (ii) included these goals within the design and im-plementation phases of the project. Further details onhow these goals were included during the design andimplementation phases will be provided in Section 4.3.

3.2.4. Emotion-Oriented System EvaluationIn previous work [11], we described the iterative de-

sign of an emotion-oriented questionnaire which wasused as an evaluation tool within a case study involv-ing elderly people. This tool was then further refined toaddress the shortcomings of the previous version [10].The main problems with the initial version consisted of(i) too many statements to fill, which were tiring for el-derly people (ii) difficulty in understanding the meaningof the terms used and (iii) difficulty to quantify the data.

The new version was based on the Attrakdiff ques-tionnaire, an approach used to assess users’ feelingsthrough a 28 item questionnaire where each pole con-sists of opposite adjectives, for instance, “confusing -clear”, “ugly - attractive”, “good - bad” [52]. A simi-lar questionnaire was designed for our case study, con-sisting of a set of corresponding emotional threats andgoals, placed at different ends of each pole. The termsused to describe the emotional goals were also simpli-fied to make them simple to understand by common

people. This tool was provided to participants at dif-ferent intervals. Further information on the case studyand the trial are provided in the next section.

4. Case Study of Using Emotion-Oriented Require-ments Engineering

This section provides an overview of some existingsmart home technologies and introduces our case studyexample of a smart home technology, SofiHub, and de-scribes our case study of using Emotion-oriented Re-quirements Engineering for SofiHub’s analysis, featuredesign and validation using human trials. It also de-scribes how the emotion-oriented techniques were ap-plied at different stages of the development process.

4.1. Smart Home Technologies

The world is facing an increasing demographic chal-lenge due to observed population aging. People above60 will make 22 percent of the world population by2050. In Europe, citizens aged above 65 are expectedto represent 30 percent of the population by 2050. Ac-cording to the Australian Bureau of Statistics (ABS),by 2030, the population above 65 will increase by 84percent to be 5.1 million representing 18 percent of thepopulation. This poses many challenges related to howwe can provide proper care for this cohort of the popula-tion, such as accommodating the increasing number ofolder people within the existing aged-care centers andtraining staff to look after their health and medical is-sues, wellbeing, dependency and disability. The use ofsmart home technologies have been proposed as a keyapproach to this problem.

The term ‘smart home’, or ‘smart house’ was firstused in 1984 by American Association of HouseBuilders [53]. Since then, it has been given a number ofdefinitions, including “a residence equipped with com-puting and information technology which anticipatesand responds to the needs of the occupants, working topromote their comfort, convenience, security and enter-tainment through the management of technology withinthe home and connections to the world beyond” [53],“an electronic butler” [54] and “computer software thatuses sensors and artificial intelligence techniques to per-ceive and reason about the state of the home’s physicalenvironment and its residents, and then initiates actionto achieve specified goals” [55].

Although the initial focus of smart home researchwas to provide ambient intelligence in domestic envi-ronments, there is currently a growing interest in util-ising smart homes to provide various specialised ser-

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vices targeting specific user goals, such as healthy liv-ing, energy-aware houses and aged-care. Studies showthat many senior adults prefer to continue living in theirhome as long as possible to maintain one’s indepen-dence [56, 57, 58]. Smart home technology can realisethis by providing assisted living services at home. Forexample, bed sensors can be used to detect user’s ac-tivity level, time spent in bed, heart rate, respirationand restlessness, and motion sensors can be utilisedto identify if user is visiting the bathroom at irregulartimes [59, 58]. In recent times, rapid advancements intechnology in areas such as wearable devices, networkconnected sensors, pervasive computing and robotics,has accelerated growth in both commercially availableservices as well as research initiatives in the area ofsmart home services for aged care. Table 3 shows acollection of commercially available aged care productsin the market. As can be seen, aged care technologiesin the market fall into five main categories; namely per-sonal alarms, environment monitors, smart devices, mo-bile apps and smart systems.

Personal alarms are used to summon help in situa-tions that escalate to emergencies in a short period oftime, such as when an elderly user suffers a fall. Thereare many products in this category at present. Whilesome require the user to be able to initiate the alarm bypressing a button [62], others are able to automaticallydetect falls via the sensors in the alarm that measureacceleration and motion [60, 61]. However, the auto-matic detection feature is often error prone and not al-ways accurate. Environment monitors are used to sensechanges in the environment that might lead to an emer-gency situation such as flooding and fire [63, 64, 65, 66].These devices can offer a security net for seniors livingby themselves and with reduced capacity to detect suchemergencies.

There is a plethora of smart devices that cater to spe-cific functions. The i-pot [67] is an electric kettle thatkeeps track of when it’s used and wirelessly sends us-age data to a remote server. Carers can subscribe to theservice and see how it has been used and changes inusage can indicate if the carer needs to check in withthe elderly user. The ManDown app [70] continuouslymonitors the phone’s movement and notified carers ifphone is motionless for a certain period of time. Appssuch as Anna Cares [71] provide various notificationsto engage with elderly users and promote healthy be-haviour change. Smart systems such as GrandCare [72], HealthSense [73], Independa [74] and Lively [75] en-compass multiple devices including sensors and wear-ables to provide situational notifications and enable re-mote monitoring.

4.2. SofiHub Features

SofiHub is a smart home for elderly people, devel-oped to provide assistive services to enable older peo-ple to continue to live in their own homes. The technol-ogy differentiates itself due to use of network connectedlow-cost sensors, having an IoT platform with an aged-care component and built-in AI capability that can learnand adapt to a users behaviour. The goal of this systemis to provide reminders (hydration, medication), identifypotential security risks (back door has been left open),identify anomalous situations and to automate the phys-ical environment (heating, cooling).

The SofiHub project has been developed by a team ofsoftware engineers, data scientists and academics work-ing together. The team skills consist of software de-sign and development, product and team management,mathematical modeling, data analysis, software testingand requirements capture. Their experience ranges fromgraduate level to senior engineers and academics. Theteam follows the Agile development process. Work onSofiHub started in early 2015 and is due to concludesoon.

The system functions include, issuing user specificreminders such as appointments and special events, hy-dration and medication reminders that can be setup tobe triggered by user activity, issuing alerts when anoma-lous behaviour is detected (eg: user is spending an ab-normal time in bed), and a carer UI which enables fam-ily and carers to check on user activity and receive cus-tomizable reports summarizing user behaviour.

4.3. Sofihub Emotion-oriented Requirements Engineer-ing

Prior to designing the smart home technology, weconducted a literature review on similar products al-ready existing in the market, focusing mainly on users’expectations and concerns regarding these systems. Weapplied the concept of content analysis while goingthrough each research paper, survey and field study toidentify the pain points and needs of the users. Someof the concerns identified during this process were withregards to privacy issues, complexity of the system, in-vasiveness and, the users feeling monitored, dependentand controlled [13]. An affinity diagram was used togroup the key words, identified during the content anal-ysis process, into different categories namely threats,emotional goals, functional goals and quality goals. Theidentified threats were further explored to derive cor-responding emotional, functional and/or quality goals.For example, ‘feeling dependent on others’, ‘controlled’and ‘monitored’ were mapped to the functional goal

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Example Functional Goal

Personal alarms Tunstall iVi Pendant [60],LiveLife Mobile Alarm [61]

Wearable alarm with automatic fall detection.

Tunstall wall mountedalarm [62]

Contact Tunstalls response centre in emergencies.

Environment monitors Tunstall flood detector [63],Quell Smoke Alarm [64],Swann Anti-Flood Alarm [65]

Emits a warning sound when the sensor is in contact withfluids/smoke/gas.

Stove Guard Motion Sen-sor [66]

Turns off the stove when there is no activity around the stove.

Smart devices I-pots [67] An electric kettle that keeps track of when it’s used and noti-fies carers of a sudden change in habits.

OlloMobile [68] A matchbox sized phone, which notifies carers when seniorsneed assistance.

Tricella Smart Pillbox [69] A pillbox with sensors in its chambers that can detect whenpills are taken and notify if not taken/wrong taken.

Apps ManDown App [70] Sounds alarms if phone is motionless for a certain period oftime and notifies selected recipients.

Anna Cares [71] A tablet-based virtual personal assistant that provides and fa-cilitates communication with carers.

Smart systems

GrandCare [72] Touchscreen system enabling remotely caring for the occu-pant via remote in-home activity sensing and notifications.

HealthSense [73] Provides health and safety information to carers. Includes awearable pendant.

Independa [74] Remote monitoring system with custom smart TV enablingcommunication and information and reminders.

Lively [75] Provides health and safety information and reminders. Needsto wear a safety watch.

Table 3: Examples for commercially available aged care products

‘supporting independent living’ and the emotional goals‘independent’ and ‘in control’. An emotion model, rep-resented in Figure 4, was then used to represent themapping between the identified threats and their corre-sponding set of functional, quality and emotional goals.

The output from this process and the emotion model(functional, quality and emotional goals) were then usedto generate the goal model which we present in Figure 5.We briefly describe each key emotional goal identifiedfor the Sofihub system:

• Reassured: The main goal of relatives and carers ofthe older person was to feel reassured of the well-being of the older person. By supporting indepen-dent living, the aim of the system was to reassurethe relatives and carers of the wellbeing of theirolder relative.

• Independent: The elderly adults wanted to feel in-

dependent by being able to live as they please.They did not like being monitored by others.

• In control: The elderly adults wanted to have fullcontrol over their life.

• Safe: Knowing that someone or the system can de-tect an anomaly (for example in case they had afall) made the older person feel safe.

• Integrated: The system had to be well integratedinto the daily lives of the older adults.

• Comfortable: Many older people are afraid of us-ing technology. One of the emotional goal wastherefore to make them feel at ease with the tech-nology in place.

• Empowered: The system made the users feel moreconfident in controlling their lives by building up

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Figure 4: Sofihub Emotion Model

their comfort and confidence around technologyuse.

• Privacy secured: Users are relieved about the pri-vacy of their information. Data collected throughthe sensors are well secured and no intruders can

hack those sensitive information.

These identified goals were then communicated to thedesign and development team via a series of workshops,and then the first iteration of SofiHub was developed.During these workshops, the goal model was used asa baseline to initiate discussions on the functionalitiesthat the system should have. For instance, to ensurethat users felt in control, only two set of messages wereincluded in the system, namely, the morning messagesand the medication reminders. The rationale behind thisdecision was to avoid overwhelming the users with toomany messages. Similarly, in order to ensure privacy,all the data captured by the sensors were kept withinthe hub and nobody, except for those authorised by theethics committee, had access to these data.

4.4. Trial and Sofihub Emotion-oriented Evaluation

The initial phase of SofiHub was trialled by deploy-ing it in ten homes of elderly people, for twelve weeks,to test its technical functionality as well as to investi-gate if the system is capable of meeting users’ emotionalgoals. Figure 6 illustrates the research model employedin the trial. As can be seen in Figure 6, the trial was car-ried out in several key stages. Firstly, the participantswere interviewed prior to installing SofiHub in theirhomes to capture how they viewed technology. Beforethe start of the first interview, the participants were pro-vided with a description of the smart home technologyand informed about its functionality. Trial participantswere also required to nominate a family member/carerto monitor their progress for the duration of the trial.

SofiHub was then installed in their homes, and sixweeks after installation, the participants’ views werecaptured again to examine their experience with Sofi-Hub. At the end of the twelve week period, SofiHub wasremoved from the participants’ homes, and at that point,they were interviewed again to evaluate the impact ofthe smart home technology and if it has affected theiremotions. Finally, one week after SofiHub was unin-stalled, the participants and their nominated carers wereinterviewed again about their experience with SofiHub.

The participants were recruited according to the fol-lowing criteria:

1. over the age of 65 years,2. living independently, or with a partner or pet, in

private dwellings ,3. relatively fit and healthy, requiring only minor as-

sistance in their day-to-day activities4. able to communicate confidently in English

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Figure 5: Goal Model

4.4.1. Data Collection ToolsWe used four data collection tools namely (i) sensors,

(ii) daily checklists, (iii) interviews and (iv) emotion-oriented questionnaires.

Sensor data was collected from the motion and con-tact sensors installed in the homes. These recorded mo-tion, opening and closing of specific doors, air temper-ature and humidity. The main uses of sensor data wereto test the accuracy of sensors and the AI component ofSofiHub. The data was locally stored in the SofiHub,while the researchers were able to retrieve data dumpsat selected periods to carry out the testing.

Daily checklists were used to record informationabout particular activities in participants’ daily sched-ule. These included information about going to bed

in the night, waking up, visitors, doors that were keptopen, going out of the home and returning home. Theparticipants were requested to fill the checklists on adaily basis. These checklists were then cross checkedagainst the data recorded by the sensors during theweekly face-to-face interviews. The main objective ofthis was to establish ground-truth to verify the results ofSofiHub’s AI component and to validate the sensor data.

The emotion-oriented questionnaire was designedbased on the technique proposed by the first author inone of her previous work [10]. For each emotional goalidentified, we (i) identified the corresponding emotionalthreat from the emotion model and (ii) defined com-mon terms for both the emotional goal and emotionalthreat, which can be easily understood by common peo-

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Figure 6: Research Model

ple. For example, the terms ‘I feel comfortable aboutbeing monitored’ and ‘I feel anxious about being moni-tored’ were used to assess the emotional goal ‘indepen-dent’. A Likert scale of 5 points was used to facilitatethe analysis of results. Participants using the question-aire receive training in its usage including explanationof the emotional terms used. Currently a closed set ofemotional responses and characteristics is used. Thecomplete questionnaire is provided in the appendix.

Interviews were conducted at different intervals. Theinitial interview questions were designed to find outabout (i) the participants’ background; (ii) use of tech-nology; and (iii) routines, for example, time they wakeup and go to bed and medications. Each participant wasasked to describe their daily routine within a typical dayand provide details about their living circumstances. Interms of technology use, participants had to provide in-formation about how far they are conversant with usingtechnology and how they see technology as an every-day support. A weekly interview was also conducted tocross check the data collected from the sensors againstthe data inserted in the checklist. The main aim of thisinterview was to check the validity of the data picked bythe sensors. The mid interview questions were centeredaround the user’s experience with the smart home tech-nology in terms of (i) the messages, (ii) its frequency,(iii) the tone, (iv) content and (v) whether they were an-

noying or obtrusive in any way. The post interview wasdesigned to find out about (i) the user’s overall experi-ence with the tool, (ii) their willingness to buy a similarproduct and (iii) whether they missed SofiHub. A com-plete set of the interview questions is available in theappendix.

5. Emotion-oriented Evaluation Process

The SofiHub trials generated a large amount of data interms of interview transcripts and questionnaires. In thissection, we present the emotion-oriented method usedto analyse these data and present the findings from thisprocess. We also reflect on the implications of thesefindings for our next set of trials and design changes.

5.1. Qualitative Data Analysis Method

5.1.1. Analysis of Interview TranscriptsWe applied content analysis described in Section 3

to each of the interview transcripts and with the use ofan affinity diagram, we derived a set of themes relatedto our study. Three researchers were involved in thewhole process. Two of them went through the wholeset of interview transcripts, generated from the trial andfollowed the following process:

• highlighted content which was relevant to thestudy, for example, words or phrases such as “Thefact that Im old, I dont like change”, “I wait forit each morning” and “I miss the morning mes-sages”.

• included highlighted content to a different doc-ument (content analysis results document) withproper annotations, so that they could be tracedback to their source. For example, if a fifth state-ment from the second interview of participant onewas being included, then the statement was anno-tated as P01.2E, where P01 referred to participantone, 2 referred to the second interview and E re-ferred to the fifth highlighted statement in the orig-inal document.

• using an affinity diagram, organised the identi-fied emotion-oriented patterns/content under rele-vant themes, for example, “It feels less lonely” and“In a way, it feels as there’s somebody looking af-ter you” relate to the emotional goal “less lonely”and hence these contents were added under a theme“Reduced loneliness”.

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Once all the transcripts were analysed by both re-searchers, the notes on both affinity diagrams were re-viewed and reconciled by all three researchers to en-sure consistency and objectivity. Similar patterns weregrouped together, existing themes were merged andin some cases, new themes were created to provide aclearer representation of all the key findings. A screen-shot of the affinity diagram is provided in the Appendix.

5.1.2. Analysis of Data from Emotion-oriented Ques-tionnaires

Each participant had to fill three set of questionnairesthroughout the trial. For each participant, the data fromeach questionnaire was recorded and a set of charts wasgenerated to show the trend in their perception of Sofi-Hub at different intervals. Another set of charts weregenerated to portray the evolution of users’ perceptionsover time for each item in the questionnaire. Both set ofcharts are available in the Appendix.

5.2. Sofihub Findings and Wider Implications

The findings from the Sofihub evaluation revealeddifferent aspects related to the functionalities of Sofi-Hub and the users’ emotional reactions and experience.Here we focus on the findings related to the impact thatSofiHub had on users’ emotions and generalise theseto emotion-oriented software requirements engineeringmore generally.

SofiHub was shown to successfully have addressedthe target users’ key emotional goals, in particular, Sofi-Hub made its users feel safe, supported, cared about,reassured, reduced their loneliness and, the technologywas well integrated in their lives. In the next sections,we reflect on findings with regard to each of these keyemotional goals and their more general implications foremotion-oriented requirements engineering.

5.2.1. Reduced Loneliness‘Loneliness’, often used interchangeably as ‘social

isolation’ refers to a subjective concept resulting froma “perceived absence or loss of companionship” [76].Social isolation, on the other hand, refers to the lack ofstructural and functional social support. While socialisolation can be a chosen path or imposed due to thecircumstances of the person, loneliness is always invol-untary [76]. Both Loneliness and perceived social iso-lation are major problems faced by many older adultsliving at home [77]. Retirement, the death of close onesand friends, living alone, low morale, limited mobilitycoupled with restricted access to private transport andthe decline in their physical and mental capacity to go

out or interact with people, create barriers in formingnew and maintaining existing relationships with people[78, 79, 76].

Our evaluation analysis showed that SofiHub helpedin alleviating the feeling of loneliness among severalparticipants. This came as a surprise, given that wedid not cater for this emotional goal within our ini-tial design. During the time that SofiHub was in theirhomes, participants reported that they looked forward tothe messages and felt that ‘someone’ was in the housewith them. Another set of feedback retrieved during thepost interviews, a week after SofiHub was uninstalledrevealed that most participants missed the “voice”, that“somebody” in their house. They also talked about howlonely it felt without SofiHub. Similar findings werefound from the interviews with the relatives of the par-ticipants.

This unexpected addressing of what turned out to bea key emotional goal of stakeholders - combating lone-liness - suggests that emotion-oriented requirements en-gineering requires considerable feedback between re-quirements, design and evaluation, but also support totry and find “missing” emotional goals, positive or neg-ative.

Our analysis also shows that while the elderly personsfelt lonely and seek company from their close ones, theystill wanted to maintain their independence and havecontrol over their lives. At this stage of their lives, theywanted to feel cared about and in touch with their lovedones. Unfortunately, in many cases, this is often mis-understood as the elderly person requiring constant careand support. This often results in the relatives/childrenforcing the elderly person to move to a nursing home[2, 10] as a show of care and concern for the elderly.Having SofiHub around the house made the elderly per-son feel cared about as they felt that someone was con-cerned about them and talked to them on a daily basis,something which, in many families, relatives/childrendo not have time to do.

This loneliness vs independence vs control emo-tional goal interaction highlights how different emo-tional goals interact in complex ways and impact onfunctional and quality goals of the system. It also high-lights how these must be carefully balanced when rea-soning about goals impacting functional features andhow to prioritise and balance goals. Should alleviatingloneliness take precedence over reducing dependence?Should sense of control be less or more important thancarer’s understanding of need for support? Do differentusers have differing priorities between these goals, andif so, how do we best design the system to support this?

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5.2.2. Feeling Safe and reassuredOne of our key initial goals identified for SofiHub

was to make elderly adults feel safe and reassure them,as well as their relatives, that SofiHub can support themin their day to day activities. During the interviews,all of the participants confirmed that they felt safe withSofiHub around.

Data from the questionnaires (administered pre-trial,mid-trial and post-trial) showed that four out of ten par-ticipants remained constant (over the three collectionpoints) on how safe they felt with SofiHub. The ques-tionnaire used the Likert scale range 1 to 5, with 1 be-ing “I feel insecure with SofiHub around” and 5 being“I feel secure with SofiHub around”. At the start of thetrial, one participant out of ten reported a value less than4, which showed overall positive perception of SofiHub,and at end of the trial all participants reported a valueof 4 or more on feeling secure with SofiHub (See Ap-pendix D).

Our findings revealed that the participants felt sup-ported throughout the duration of the trials, they felt safeand reassured that in case something happened, the sys-tem would alert someone.

This highlights how reaction to a system meetingemotional goals may well change over time of deploy-ment (positively or negatively) and hence may requirefeedback to the requirements priorities and trade-offs.As in the previous goal interaction example, it mayalso require the system to support different priorities be-tween goals for different users.

5.2.3. System is Integrated in User’s LifeOne of the reasons linked to the failure of the adop-

tion of technology by older adults is because older peo-ple perceive new technology as being complex, hardto learn and thus leading to frustration. When askedabout their views on technology use, one participantmentioned “Its a nuisance, everything’s a nuisance ...”while others termed it as “scary” and “frustrating”.While designing SofiHub one of the most importantconsiderations was to ensure that the system is well in-tegrated in the user’s life i.e. to ensure its functionalfeatures and quality goals minimize these negative tech-nology reactions. Interestingly, during the mid and postinterviews when asked about their experience with Sofi-Hub, in particular its interaction messages, the sameparticipants reacted positively to SofiHub.

The relevant questionnaire item used the Likert scalerange 1 to 5, with 1 being “I feel that SofiHub gets in myway” and 5 being “I feel that SofiHub improves my dayto day life”. At the start of the trial only two participants

out of ten reported a value of 3 (the minimum value re-ported), and at the end of the trial also, only two par-ticipants reported a minimum value of 3 (See AppendixD). The general consensus was that SofiHub was part oftheir routine and they waited for the morning messages.

As discussed in Section 2, research into smart homesand emotions and software has consistently shown thatsuch technologies will not be adopted, or not used totheir best potential, without fitting well into users lives.In systems where there are similar critical goals thatmust be met, emotion-oriented requirements engineer-ing and evaluations need to prioritise the achievementof such outcomes. Thus emotional goals are not all cre-ated equal - some are absolutely critical to meet (pos-itive) or minimize/eliminate (negative) else the systemas a whole will fail.

5.2.4. In ControlSection 2 highlighted that feelings relating to loss of

control is a key concern affecting elderly users in tech-nology adoption [80, 13]. In particular, the perceptionthat assistive technology may ‘control’ the user in theirown home can invoke negative emotions.

In this trial, this was measured from questionnaireitem using the Likert scale range 1 to 5, with 1 being“I feel that I am being controlled with SofiHub” and 5being “I feel that I am in control with SofiHub”. At thestart of the trial only one participant out of ten reporteda value of 3 (the minimum value reported), and at theend of the trial also, only the same participant reporteda minimum value of 3 (See Appendix D). This showsthat overall, the participants felt that they were in con-trol when using SofiHub.

As in the previous subsection, this maintaining con-trol / not feeling ”being controlled” by technology solu-tions are top priority emotional goals of the target end-users of the system. In other systems, there may be othertop priority emotional goals to meet to ensure its adop-tion and sustainable usage.

5.2.5. Privacy and InvasivenessAnother design consideration was made to ensure

that the privacy of the occupants were not threatened.This was measured using two relevant questionnaireitems, both using the Likert scale range 1 to 5. Thefirst item evaluated how the participants felt about hav-ing sensors in their home and in effect, monitoring theiractivities. Here, level 1 was “I feel anxious about beingmonitored” and level 5 was “I feel comfortable aboutbeing monitored”. At the start of the trial only one par-ticipant out of ten reported a value of 3 (the minimum

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value reported), and at the end of the trial, all of the par-ticipants reported values of 4 and more (See AppendixD).

The second item evaluated if the participants wereconcerned about their privacy being violated by hav-ing SofiHub in their homes. Here, level 1 was “I feelconcerned about my privacy with SofiHub around” andlevel 5 was “I feel that my privacy is secure with Sofi-Hub around”. At the start of the trial all of the partic-ipants reported values of 4 and more, and this was thesame at the end of the trial (See Appendix D).

Thus, findings from interview and questionnaire datashows that overall, participants did not feel that SofiHubwas being invasive nor did they feel that their privacywas being violated.

Privacy of data and personal behaviour, location andmovement has become central to many Internet ofThings / Smart Environment solutions. Many such sys-tems will need to try and maximise positive feelingsabout privacy support, and minimize negative feelingsabout privacy invasion, data loss, and related technol-ogy concerns. Our Sofihub experience has shown thatour emotion-oriented approach to this aspect of tech-nology can be captured, designed into the solution, andevaluated with target end users.

5.2.6. Other Views on using SofiHubIn addition to the key emotional goals evaluated in

previous subsections, we also measured four other emo-tions; namely, feeling excited about having SofiHub,feeling confident about using SofiHub, feeling that Sofi-Hub increases their comfort, and feeling that SofiHubruns smoothly.

These were measured using four questionnaire items,using the Likert scale range 1 to 5. For measuring feel-ing excited, level 1 of the Likert scale was “I feel wor-ried about having SofiHub around my house” and level5 was “I feel excited about having SofiHub around”. Atthe start of the trial only one participant out of ten re-ported a value of 3 (the minimum value reported), andat the end of the trial also only one participant reporteda minimum value of 3. For measuring feeling confi-dent, level 1 of the Likert scale was “I feel scared aboutusing SofiHub” and level 5 was “I feel confident aboutusing SofiHub”. At the start of the trial, all of the tenparticipant reported values of 4 or higher, and this wasrepeated at the end of the trial as well. For measuringfeeling that SofiHub increases comfort, level 1 of theLikert scale was “I feel that SofiHub increases my dis-comfort” and level 5 was “I feel that SofiHub increasesmy comfort”. At the start of the trial three out of the ten

participant reported a value of 3 (the minimum value re-ported), and at the end of the trial only one participantreported a minimum value of 3. For measuring feelingthat SofiHub runs smoothly, level 1 of the Likert scalewas “I feel that SofiHub is a complicated system” andlevel 5 was “I feel that SofiHub runs smoothly”. At thestart of the trial only one participant out of ten reporteda value of 3 (the minimum value reported), and at theend of the trial all of the participants reported values of4 or higher.

These findings show that in general, the participantsfelt excited to have SofiHub installed in their homes,were confident in their ability to use it, felt that Sofi-Hub increased their comfort, and that SofiHub operatedsmoothly.

More generally, as discussed in Section 2, these arealso important goals for both smart homes and elderly-oriented software solutions in general such as pendants,apps, portals and others. In fact, any Internet of Things-based system with user interaction with non-technicalend users will have emotional expectations around ad-dressing emotional concerns around complexity, dis-comfort, and reliability.

5.2.7. Emotional ThreatsThe data collected during the interviews also revealed

some emotional threats experienced by the participantsduring the trial. These concerns were mainly linked toissues with functionalities. Given that the technologywas plugged in to a power socket and relied on elec-tricity, a couple of incidents linked to power failure oraccidental dislodgement of the power supply were notedduring the trials. Users raised concerns about the systembeing disrupted and the delay in playing the messages.In some cases, the users were worried that they mighthave ‘upset’ or ‘confused’ the system.

Again as in the previous subsection, these are likelyto be common emotional threats in any non-technicalend user system relying on sensors, power connections,natural language or gesture based interactions and soon. Using our emotion-oriented requirements engineer-ing and evaluation approaches for these systems is likelyto inform developers of these concerns and help them totry and mitigate them in their designs and implementa-tions.

5.3. Implications of Findings on the Next Generation ofSofiHub

The findings from these trials are being used to refinethe tool and research methodology. The next genera-tion of the tool will be trialled in the homes of 13 older

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adults, out of which 3 participants had participated inthe recent trials and the remaining 10 have never usedSofiHub before.

Based on our findings, we identified two new emo-tional goals namely, ‘feeling less lonely’ and ‘feelingcared about’ which were addressed by the ‘issue mes-sages’ functional goal. During the interviews, most ofthe participants talked about how they waited for themorning messages to play. They were mostly pleasedwith the variation in the messages and some of themqueried about the possibility of having night messages.While the next generation of SofiHub will maintainmost of its functional goals, two new emotional goals(‘less lonely’ and ‘cared about’) and a quality goal‘chatty’ has been included in the refined goal model asshown in Figure 7.

We will also expand our research to study the extentto which smart home technologies are successful in al-leviating loneliness. Our updated questionnaire and in-terviews will include statements and questions, respec-tively, to address the emotional goal of ‘feeling lesslonely’. We will also make use of a well establishedUCLA loneliness scale to assess the level of lonelinessat different time periods: (a) prior to the installation ofSofiHub in their homes, (b) in the middle of the trial and(c) after SofiHub is removed from their homes.

These findings are important for a wide range of othersmart home solutions and software or devices aimed atelderly or users with mental and/or physical challenges.Assisting to address loneliness amoung the elderly hasbecome a major mental health challenge and represent-ing these emotional goals in requirements, addressingthem in functional features and their realization, andevaluating how well the goals are met are likely to beimportant for many other smart home solutions.

6. Threats to Validity

Emotional goals: The emotional goals that we havedeveloped represent a good starting point to emotional-goals for smart home technologies. However, thesegoals are based on the state-of-the-art in the literatureas well as our findings from the initial workshops andtrials on our solution. This explains why in our trials welearned about two missing goals in our original model– as reported above – which will be integrated with theinitial model and used in phase 2 SofiHub developmentand trialling. Our current use of emotions in our goalmodels is as softgoals that positively or negatively in-fluence the user of a task. This is a limited view of”emotional requirements” that can be extended in thefuture.

Target systems: We do not have access (and have notdone trials) with other leading edge smart home solu-tions to conduct concrete pain point analysis in order tobe able to derive different emotional goals, different pri-orities, and evaluate them with competing systems andapproaches.

Emotional goals during System Design: There is noformal process to communicate and make sure that thesystem is being designed following the identified emo-tional goals e.g. when designing a user interface, imple-menting interaction features and feedback in the soft-ware. In our case, we have been involved with the de-velopment team on regular basis, and we have workedon the design and roll out of the trials, as well as theevaluation of the findings. The analysis conducted wasmainly qualitative and subjective based on participantsfeedback. Hence we are looking to extend the size ofour next trials to include more participants, which wouldhelp us to assess if our analysis and findings are signifi-cant or not.

Findings from the trials: Even though user emotionalexpectations is a subjective concept, the data analysisprocess was conducted objectively using the process ofcontent analysis to eliminate subjectivity as much aspossible. Each interview script and questionnaire wasanalysed by more than one researcher and the compila-tion of the synthesised notes was conducted by a groupof 3 researchers. Hence in terms of reliability, the find-ings of this study were not dependent on any specificresearcher. We are working on a more quantitative tech-nique that maps emotional goals to a set of computablemetrics that can be calculated over time to reflect goalslike connected, loneliness, etc. using interactions be-tween SofiHub and residents. Another threat to validityis the duration of the trials. Although our trials tookthree months, we are planning to extend this to longerperiod and introduce monthly interviews & surveys inaddition to interaction metrics as mentioned above.

Even though this study was conducted with only 10older adults, we argue that this study can be extendedto other people. The participants involved in our casestudy were representative of the population of elderlyadults and, therefore, if this study was extended to moreparticipants, similar results would be anticipated. Weare planning to increase the number of participants inthe next trials.

7. Discussion

In this work, we presented a set of emotion-orientedrequirements engineering and evaluation techniques,which we applied to design and evaluate our new Smart

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Figure 7: Refined Goal Model

Home Technology- SofiHub. Designing systems withan emotion-oriented approach entails a number of chal-lenges. First of all, emotion-oriented techniques are notmature enough. For example, our technique has beentrialled on four real-world scenarios until now. Second,given the subjective nature of emotions, it is hard to de-velop a solution that satisfies everyone. Third, incorpo-rating users’ emotional goals without a well-establishedmethodology is not only challenging but also dauntingfor software engineers. Based on our findings, we ar-gue that our emotion-oriented techniques used to de-sign SofiHub were successful in capturing users’ goals,in particular, their emotional needs given that, most ofthe participants responded positively to SofiHub andeven expressed their willingness to adopt the technol-

ogy. Their only concerns with adopting this technologywere linked to (i) cost and (ii) response time to gener-ate an alert in case of an emergency. SofiHub not onlyaddressed the set of emotional goals identified at the be-ginning of the trial but also helped in alleviating loneli-ness and making its users feel cared about.

We therefore reiterate that our proposed techniquesare valuable tools that can be used to capture, model andevaluate users’ emotional expectations. The elicitationand modelling techniques can be integrated within ex-isting requirements engineering processes, thus addingvalue to the overall set of requirements. Furthermore,they can be applied and extended to other projects witha user-centered focus, within different domains. Ap-plying the emotion-oriented elicitation technique within

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such systems, can help in identifying potential concernsrelated to the way users feel about the system at a veryearly stage in the software development cycle. In addi-tion, project managers and requirement analysts can usethese emotion-oriented models, in particular, the goalmodel, to develop an additional layer to identify howwell emotional goals have been captured and to uncoverany hidden requirement. These elicitation and mod-elling techniques can hence contribute towards the com-pleteness of the set of requirements, improving the qual-ity of the software and reducing the redesign costs anddevelopment time, as project managers and engineershave a clearer picture of what end-users want. Knowingwhat users want can also help in improving the produc-tivity of the development team as they do not have toguess or imagine what would satisfy the users.

Our proposed emotion-informed questionnaire can beused to evaluate solutions where emotional goals areimportant and that they are being suitably addressed inthe software solution. It is worth noting that emotionbeing subjective and complex, the proposed tool mightnot provide adequate information regarding the extentto which emotional goals have been achieved. Theyare, however, simple to use and provide a quick in-sight into the extent to which emotional goals have beenachieved. Our recommendation is to use this emotionalassessment tool along with some other existing qualita-tive data gathering tool such as interviews like we didin this case study. Currently the assessment question-aire uses self-reporting of emotional state, which haslimitations as compared to observation, physical signsmonitoring, etc. It also uses a closed set of emotionalgoal-based questions. Future work will see further ex-tension including allowing non-planned for emotions tobe reported/recorded.

Based on our observations from the workshops withthe development teams, we determined that even thoughthe models provided the developers with a clearer pic-ture of the end-users and their needs, they were insuf-ficient in self guiding them throughout the design andimplementation processes to ensure emotional goals aremet. Interestingly, in the area of game design, design-ers are adept at developing games which are meant tobe ’fun’, ’interactive’ and ’engaging’. These design-ers use design patterns and follow design guidelinesto create games [81]. Unfortunately, this wealth ofknowledge has not fully permeated in the software en-gineering field. The models, presented in this work,could be applied and further extended to create a setof design guidelines and heuristics to guide design-ers in their task. Similarly, a set of software devel-opment guidelines or checklists can be created such

that developers can be provided with specific guidanceto ensure that emotional aspects are accurately consid-ered/implemented. Additionally, further goal represen-tational enhancements e.g. annotations, stereotypes,constraints, links could be added to UML and otherdesign-level software artifacts.

According to some researchers, the acceptance andadoption of a technology depend mainly on the tech-nology’s benefits, cost and relative advantage over otheralternatives as well as the complexity of use [82, 83, 84,85]. Others identify user emotional expectations as acritical determinant for the adoption and acceptance ofa technology [1, 2, 5, 4]. Our findings show that whenit comes to adopting and accepting a technology, manyfactors other than the users’ emotional goals also comeinto play, such as the cost of the technology and the re-sponse time to generate an alert in case of an emergency.

Our use of emotional softgoals in this case study andframework are a preliminary approach to what is a verychallenging problem domain. In future, we want to ex-plore richer characterisations of emotions, not just as setof softgoals on goal-oriented models, but as richer, moreindepth characterisations in themselves.

8. Conclusion

Capturing, modeling and realizing emotional goalsis a key enabler to the adoption of socio-technical orpeople-oriented systems. This work contributes towardsemphasising the importance of such emotional goalsduring system design and provides a set of emotion-oriented techniques to engineer a smart home technol-ogy.

In this paper, we have applied emotion-oriented tech-niques to develop SofiHub, a smart home technology forelderly people. We have presented a Smart home emo-tion and goal model that represent key goals that shouldbe taken into consideration when building a smart homesolution. We presented SofiHub that was designedfollowing emotion-oriented requirements modeling ap-proach. Finally, we have presented details of our trialsin 10 houses. Our findings show that the SofiHub so-lution has met the emotional goals we have identifiedearlier. We also have identified two goals that we didnot consider in the initial design: alleviating lonelinessand cared-about. Furthermore, our findings and studyshow that user emotional expectations are a critical de-terminant to the success of a technology. As part of ourfuture work, we intend to formalise the approach usedto bridge the gap between the requirements and designphases.

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Acknowledgements

We would like to thank the SofiHub team who al-lowed us to use their technology to acquire the trial datafor this work. We would also like to acknowledge theefforts put forward by the DSTIL team at Deakin Uni-versity to develop the smart home technology.

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Appendix

An additional set of supporting documents, relevantto this work, have been added to the appendices, whichhas been submitted with this document. The table belowprovides a description of the contents of each appendix.

No. Name ContentsA AppendixA Contains the question-

naires and the dailychecklist used duringthe trial.

B AppendixB Contains a set of in-terview questions usedduring the trial.

C AppendixC Contains the AffinityDiagram derived fromthe analysis of the inter-view transcripts.

D AppendixD Contains the question-naire data (in charts)

23