First Approach to Automatic Performance Status Evaluation and Physical Activity Recognition in...

First Approach to Automatic

Performance Status Evaluation and

Physical Activity Recognition in

Cancer Patients

Salvador Moreno · Miguel Damas · Hector PomaresJose A.Moral-Munoz · Oresti Banos

Email: [email protected]

SUT4Coaching 2016 – Granada, Spain

Index of Contents

1. Motivation

2. State of the Art

3. System Design

4. System Implementation

5. Conclusions

Automatic Performance Status Evaluation.S. Moreno Gutiérrez

15th December 2016

SUT4Coaching – Granada, Spain. 2

1. Motivation

● 14 million new cases and 8 million cancer-related deaths in 2012

● Is projected to increase by 70% in two decades.

● The estimated total annual economic cost of cancer was approximately US$ 1.16 trillion in 2010

● Between US$ 100 billion and US$ 200 billion could have been saved in 2010

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[1] World Health Organization, World Cancer Report 2014. Lyon, FRA:International Agency for Research on Cancer, 2014

1. Motivation

● Cancer treatment relies in several aspects under the subjectivity of the oncologist.

– Interviews

– Family's Feedback

● Patients are sometimes hard to treat.

● Hard to remember by heart and measure the activity realized.

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1. Motivation

Solution Proposed:

Automatic Tracking of the

Patient's Physical Activity

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2. State of the Art

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Patient's Condition

PerformanceStatus

PhysicalCondition

ECOG

KPS

IPAQ


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2. State of the Art

KPS (Karnofsky's Performance Status) – 1949

Normal, no complaints. No evidence of disease. 100

Able to carry on normal activity. Minor signs of disease. 90

Normal activity with effort. Some signs or symptoms of disease. 80

Cares for self; unable to carry on normal activity or do active work. 70

Ocassional assistance. Able to care for most of personal needs. 60

Considerable assistance. Frequent medical care. 50

Disabled. Requires special care and assistance. 40

Severely disabled. Hospital admission indicated. Death not imminent. 30

Very sick. Hospital admission necesary. 20

Moribund. 10

Exitus. 0

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[3] Karnofsky DA Burchenal JH. The clinical evaluation of chemotherapeutic agents in cancer. Evaluation of chemotherapeutic agents., pages 191–205, 1949. New York Columbia. University Press.


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2. State of the Art

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ECOG (Eastern Cooperative Oncology Gropp) – 1960

Asymptomatic. Normal, no complains. 0

Symptomatic but completely ambulatory. Able to carry work of light or sedentary nature like housework or office work.

1

Symptomatic and able of all self care but unable to carry out work activities. Less than 50% of waking hours in bed or chair.

2

Symptomatic and capable of only limited self-care. Confined to bed or chair 50% or more of waking hours.

3

Bedbound. Completely disabled. Cannot carry any self-care. 4

Exitus 5

[15] C.G Zubrod et al. Appraisal of methods for the studyof chemotherapy of cancer in man: Comparative therapeutic trial of nitrogen mustard and triethylene thiophosphoramide. Journal of Chronic Diseases, 11(1):7–33, 1960.


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2. State of the Art

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IPAQ: International Physical Activity Questionnaire

– IPAQ 3: High Physical Activity

– IPAQ 2: Moderate Physical Activity

– IPAQ 1: Low Physical Activity

Physical activity measured in MET·min

[22] IPAQ scoring protocol - International Physical Activity Questionnaire.


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2. State of the Art

● IPAQ● Category 1: Low

– This is the lowest level of physical activity. Those individuals who not meet criteria for categories 2 or 3 are considered low/inactive.

● Category 2: Moderate– 3 or more days of vigorous activity of at least 20 minutes per day OR– 5 or more days of moderate-intensity activity or walking of at least 30 minutes

per day OR– 5 or more days of any combination of walking, moderate-intensity or vigorous

intensity activities achieving a minimum of at least 600 MET-min/week.

● Category 3: High– Vigorous-intensity activity on at least 3 days and accumulating at least 1500

MET-minutes/week OR– 7 or more days of any combination of walking, moderate-intensity or vigorous

intensity activities achieving a minimum of at least 3000 MET-minutes/week


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[22] IPAQ scoring protocol - International Physical Activity Questionnaire.

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2. State of the Art

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Physical Activity

Measurement

Heart Rate Intensity

(Karvonen)

DailyStep Count

(Tudor-Locke)

Class Steps/day

Sedentary <5000

Low Act. 5000 – 7499

Medium Act. 7500 – 9999

High Act. 10000 – 12499

Very High Act. >12500

[35] Dr Juha Karvonen and Timo Vuorimaa. Heart Rate and Exercise Intensity During Sports Activities. Sports Medicine, 5(5):303–311, November 2012.

[39] Catrine Tudor-Locke and David R. Bassett Jr. How many steps/day are enough? Sports medicine, 34(1):1–8, 2004.


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3. System Design

Objectives:

● Automatic tracking of the activity performed.

● Develop algorithm for IPAQ estimation

● Develop algorithm for ECOG and KPS estimation.

● Focus on tendencies rather than the absolute measures.

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3. System Design

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Google FIT:

– Sensors API

– Recording API

– History API

– Sessions API

– BLE (Bluetooth Low Energy) API

– Config API


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Data Recorded

– Activity Recognition● Still, walking,

running...● Sleep tracking

– Calories Expended (cal)

– Heart Rate (BPM)

– Step Count (count)

3. System Design

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Wearable selected:

Sony Smartband 2 SWR12

Cost <100€

Measures:

– Heart Rate (HR)

– Step Count

– Activity Recognition

– Calories Expended


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3. System Design

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● Gamification

[31] Kevin Werbach and Dan Hunter. For the Win: How Game Thinking Can Revolutionize Your Business. Wharton Digital Press, October 2012.


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3. System Design

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Gamification Design:

– Interactive interface for the patient.

– Highlight achievements done in the recovery.

– Engagement and progression loops.


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17Trabajo de Fin de Grado


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3. System Design

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Planteamiento del sistema.


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IPAQ Estimation*

1. SQLite query

2. Sampling Frequency adaptation between data.

3. Daily detection and data bucketting.

4. IPAQ rules application.

5. Weekly approach of the estimation.

– *Intensity of the Activity Detected by using Heart Rate and Calories Count.


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IPAQ Algorithm Validation

● Comparison betweenIPAQ MET estimationand Google Fit'sCalorie Count convertedto MET

● Pearson Correlation

– 0.8505 with all data

– 0.9665 without outliers


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ECOG and KPS estimation*

1. SQLite Query

2. Sampling Frequency adaptation between data.

3. Daily detection and data bucketting.

4. ECOG and KPS Table Rules application.

5. Weekly approach of the estimation.

– *Activity detected, Intensity of the Act. Detected, Steps Count, Proportion of Active Waking Hours.

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Daily proportion of active Waking Hours

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4. Implementacióndel sistema


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Week 1 Week 2

IHR ECOG KPS ECOG KPS

> 0 % 1 90 2 70

> 1 % 2 70 2 70

> 2 % 2 70 2 70

> 3 % 2 70 2 70

> 4 % 2 70 2 70

> 5 % 2 70 2 70

Preliminary Test Results:

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5. Conclusions

● Extensive review of the State of the Art.

● Needs assessment performed with the help of Oncologists and psychologists from the Hostpital Virgen de las Nieves in Granada.

● Android, SQLite and MATLAB have been used for the system implementation.

● It is the first approach to automatic performance status evaluation in cancer patients.

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15th December 2016


First Approach to Automatic

Performance Status Evaluation and

Physical Activity Recognition in

Cancer Patients

Salvador Moreno · Miguel Damas · Hector PomaresJose A.Moral-Munoz · Oresti Banos

Email: [email protected]

SUT4Coaching 2016 – Granada, Spain

3. System Design

● Wearable market grows 171.6% between 2014 y 2015 and smartphones keep their sales (Source: IDC)

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Physical Activity time detected

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● Execution time of a nineteen-days-query.

Execution Time:

ET = (3,4 ± 0,4) s


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2. State of the Art

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● Gamification:



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2. State of the Art

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● IoT & mHealth



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33SUT4Coaching – Granada, Spain.


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First Approach to Automatic Performance Status Evaluation and Physical Activity Recognition in...

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