WEARABLE SENSORS TO IMPROVE DETECTION OF PATIENT DETERIORATION
Meera Joshi, Hutan Ashrafian, Lisa Aufegger, Sadia Khan, Sonal Arora, Graham Cooke & Ara Darzi
Abstract
Introduction
Monitoring a patient’s vital signs forms a basic component of care, enabling the identification
of deteriorating patients and increasing the likelihood of improving patient outcomes. Several
paper-based track and trigger warning scores have been developed to allow clinical
evaluation of a patient and guidance on escalation protocols and frequency of monitoring.
However, evidence suggests that patient deterioration on hospital wards is still missed, and
that patients are still falling through the safety net. Wearable sensor technology is currently
undergoing huge growth, and the development of new light-weight wireless wearable sensors
has enabled multiple vital signs monitoring of ward patients continuously and in real time.
Areas covered
In this paper, we aim to closely examine the benefits of wearable monitoring applications that
measure multiple vital signs; in the context of improving healthcare and delivery. A review of
the literature was performed.
Expert commentary
Findings suggest that several sensor designs are available with the potential to improve
patient safety for both hospital patients and those at home. Larger clinical trials are required
to ensure both diagnostic accuracy and usability.
Word Count 185
Key Words: Continuous monitoring, Patient deterioration, Hospital, Vital signs, Ward
patients, Wearable sensors.
1
Introduction
1.1 The need for continuous monitoring
Monitoring of a patient’s observations forms a basic component of clinical care.
National Confidential Enquiry into Patient Outcome and Death (NCEPOD) data shows that
clinical deterioration may present several hours prior to an adverse event(1). Unfortunately,
unwell patients are still currently falling through the ‘safety net(2). Some 39% of acute
emergency patients admitted to the Intensive Therapy Unit (ITU) are referred late(3). A
measurement of a patient’s vital signs is often the first step in assessing for any acute
deterioration in their clinical condition(4)(5).
1.2 Recording of vital signs
Essential vital signs that are routinely captured are: temperature, heart rate (HR), blood
pressure, respiratory rate (RR), oxygen saturations and level of consciousness. Vital signs
inform and guide clinicians on how the patients are progressing during hospital admissions,
and alert in cases of patient deterioration. A measurement of a patient’s vital signs is often the
first step in assessing for any acute deterioration in their clinical condition(4) (5). An acute
deterioration in patient’s condition is accompanied by changes in their physiological
parameters first(6)(7). The vital signs can help detect several problems such as cardiac,
respiratory, shock and sepsis. A patient’s vital signs are crucial to ensure an earlier detection
of sepsis(8)(9). If these changes are not detected and treated there is a risk of cardio-
respiratory arrest(10) (11). With stretched resources and a busy ward the opportunity to
identify deteriorating patients early can be easily missed. Consequently, acute wards with a
high turnover of patients are most at risk and admit sicker patients.
For ward patients, most hospitals offer intermittent monitoring. A range of observation
machines are available and vary depending on the NHS trust. The most commonly used
observation machines in the NHS are the Dinamap Vital Signs Monitor(12) and the Welch
Allyn Spot Vital Signs® Device (13). Most observation machines provide a local display for
the healthcare professional reviewing the observations and it is not common practice
currently for their integration into electronic health records or alerting through mobile
2
devices. During the time of monitoring a physical check on the patient is performed by a
healthcare assistant or junior nurse. This normally takes around 5-10 minutes and a portable
observation machine is used. The observation machines are connected to the patient through
several ways.
The blood pressures is measured by using an appropriately sized blood pressure cuff which is
attached to the patient during the monitoring process, this often takes a few minutes to
calculate and gives both a systolic and diastolic reading. A finger based probe measures the
oxygen saturations and heart rate. The temperature is often recorded using a portable
tympanic probe. There are other routes of recording temperature that are less common such
as; axillary, oral and rectal. In most hospitals, the observation machines have a local display
and this is copied onto the paper based observation chart by the healthcare staff member that
is taking the observation. The way that vital signs are obtained in healthcare has not changed
for several decades with often a single ward nurse managing many patients. Currently in most
hospitals the monitoring of respiratory rate is not automated and cannot be calculated by the
observation machine itself. Instead, the respiratory rate is measured by the healthcare
professional counting the breaths over a time period either for a full minute or for 30 seconds
and multiplying it by two. The current way of measuring respiratory rate has been shown to
highly inaccurate and poorly reported(14). Level of cognition is assessed by healthcare staff
at the bedside and is currently not automated. It is normally measured through simple scales
such as AVPU whereby the patient is Alert or responds to Voice or responds to Pain, or is
Unresponsive.
The common practice for measuring a patients vital signs as recommended by The National
Institute for Health and Care Excellent (NICE) is all patients have their vital signs recorded
every 12 hours as a minimum(2). Every 4-6 hours are when ward observations are typically
taken although overnight they may be very infrequent. The frequency of monitoring is
depended on each individual trust policy and may be increased in certain clinical
circumstances such as very unwell patients or those with a head injury for example that
require more frequent monitoring. The limitations to current monitoring practice is that
deterioration between these time periods of monitoring may easily be missed.
Several paper track and trigger warning scores have been developed to allow clinical
evaluation of a patient and guidance on escalation protocols and frequency of monitoring.
3
One such score that is most frequently used in the National Health Service (NHS) is the
National Early Warning Score (NEWS)(15). The Royal College of Physicians recommends
that the minimum frequency of monitoring should be every 12 hours (15). The frequency of
observations are increased to 4-6 hours for those with a NEWS of 1-4, hourly for a NEWS of
5-7 and continuously for patients with a NEWS of 7 or greater(15). An increased frequency
of monitoring is required for acutely unwell patients.
The reporting of vital signs in their current form has been prone to errors for several reasons.
Firstly there may be an inadequate monitoring frequency for some patients(16) (17) (18). The
calculation of the early warning score itself may be inaccurate(19)(20)(21)(22)(23). Paper
based observation charts have been used over the last 50 years and are still the most common
way to record observations in most NHS hospitals. Most causes of error arise from the use of
paper based observation charts. The paper charts that have been traditionally used are placed
at the patient’s bedside. Any damage to the paper chart due to spillage for example or poor
documentation may leave them to be illegible and lead to false interpretation(24) (25).
1.3 Continuous monitoring of vital signs
For decades, the way vital signs are measured have not changed. They are taken at static
moments in time. Wearable sensors will cause a huge paradigm change. There will be a
dramatic change in the landscape of assessment of vital sign observations as these new
technologies develop further. Patients will be continuously monitored which in turn will be
combined with real time analytics helping to identify unwell or deteriorating patients much
sooner than current technologies. The use of these sensors in high-risk patients and acutely
unwell patients will be an early source of interest.
Continuous monitoring of vital signs through the latest wearable sensors may help in the
early identification of patient deterioration. Fortunately, to tackle the above challenges, there
have been significant developments of wearable sensors in recent years (26)(27)(28)(29)(30)
(31)(32)(33). It has been possible to develop smaller, light-weight sensors, with greater
4
sampling frequency that can relay information wirelessly ensuring that patient mobility is not
compromised and the sensors will be well tolerated.
The continuous monitoring of heart rate and respiratory rate can predict and reduce the
occurrence of potentially adverse events such as cardiac arrest and respiratory failure. It has
been shown that respiratory function deteriorates in a significant number of patients prior to
an ITU admission(34). As well as the standard vital signs mentioned above newer wearable
sensors may be able to measure the ‘physiological signal’ which may represent the
complexity of the integrated compensatory responses that change early in the clinical process
rather than outcome variables such as vital signs(35). Newer markers such as age combined
with traditional vital signs may help better triaging of patients than traditional vital signs (36).
Whilst vital signs are useful in detection of patient deterioration it should be noted that
normal physiological processes are in place to help compensate when patients become
unwell. At times, vital signs do not change until quite late until the progression of the
patient’s condition particularly in shock(35). Patients use compensatory physiological
mechanisms (such as vasoconstriction, tachycardia and deep inspiration) to help maintain the
consistency of blood pressure(37)(38)(36)(39).
A range of options are used to transmit the data from the sensor wirelessly including
Bluetooth, radiofrequency and Wi-Fi signal. The wearable sensor technology can transmit
data back to the clinicians via alerting through a centralised monitoring system, integrating
into electronic health records and alerting to mobile applications for portable hand held
devices such as smart phones and Personal Digital Assistant (PDA).
With faster and better prediction of patient deterioration through proactive monitoring of a
patient’s vital signs it is likely patient outcomes will improve and make substantial
improvements to patient safety. Whilst it is likely that wearable sensors will improve patient
safety and patient outcomes the use of wearable sensors in clinical practice is currently very
novel. Consequently, there are very few high-quality studies or randomised controlled trials
thus far reviewing patient outcomes. The benefit of continuous monitoring must be offset by
5
both practical and economic considerations of running a well-controlled large trial in high
risk patients.
Early studies on outcomes have found promising results. Several studies have shown
wearable sensors to improve a diverse range of patient outcomes from; reduced pressure
sores(40), a reduction in the number of total days spent on an Intensive Care unit(41),
reduction in hospital stay (42), a greater diagnosis of heart arrhythmias such as atrial
fibrillation (43),
However, the results may be conflicting, a randomised control trial has found continuous
monitoring to have no effect on adverse events and mortality. Only 16% of patients were
monitored for 72 hours as intended and thus the study was significantly underpowered(44).
Patients on high dependency units and intensive care often require continuous monitoring as
small changes in physiology may have a profound effect on patient outcomes. This
monitoring is impractical for ambulating ward patients as existing systems are often heavy,
expensive and require indwelling lines and or additional wires. One of the key strengths in
the use of wearable sensors is the encouragement of patients to ambulate early in hospital.
There is significant data which shows the benefits of early ambulation in hospitalised patients
and an improvement in recovery. Much of this work started in the 1990s when the concept of
enhanced recovery after surgery was first proposed(45). Early mobilisation of surgical
patients is one of the pillars in the Enhanced Recover After Surgery (ERAS) programme
which has been widely adopted worldwide. Improved adherence to ERAS is associated with
improved clinical outcomes after patients undergo major colorectal surgery(46). As well as
the benefit in surgical patient’s early mobilisation has also been encouraged for medical
patients. Early physical rehabilitation has been shown to reduce hospital length of stay in
medical patients such as those with acute respiratory failure(47). Early mobilisation after an
intensive care unit admission have been shown to improve neuromuscular weakness and
physical function(48).
The current forms of monitoring used on the wards are often bulky and have lots of wires
restricting the movement of patients. Whilst they are useful for patients confined to bed, most
6
patients are ambulating on the ward and would be severely restricted if such monitoring was
continuous. In additional there is the potential that current monitoring used continuously may
inadvertently slow recovery by reducing mobility. Performing manual observations on
patients can take between 5-10 minutes per patient and can be time consuming for staff. The
use of automatic monitoring systems such as wearable sensors can free up staff to perform
other tasks. The way that observations are taken currently is open to user interpretation,
whereas wearable sensors will help to reduce any bias in recording observations.
The newer wearable sensors that have been developed offer several advantages to current
monitoring. They are often wireless enabling greater movement and less restrictions than
current monitoring. The sensors are lighter and smaller in size and so can be worn more
discretely by patients. They offer more comfort than current forms of bedside monitoring.
Respiratory rate is manually counted by a nurse at the bedside and is not currently automated.
Data shows that respiratory rate is repeatedly the vital sign where documentation is poor(49)
and often inaccurately calculated and recorded(50). Automated ways of calculating
respiratory rate through wearable sensors aim to provide greater accuracy and greater
documentation. Additionally vital sign data from wearable technology can be used in the
development of ‘automated health event prediction, prevention and intervention’(51).
Continuous monitoring has the potential to be a great benefit in identifying patients with
sepsis where deterioration can be very rapid (52). Additionally, identifying the
‘normalisation’ of patients earlier may result in earlier discharges, reducing both length of
stay and costs. With the growing elderly population and more patients with chronic disease
being managed in the community there is an increasing role for continuous monitoring at
home too.
1.4 Latest wearable sensors
The wearable sensor market is rising rapidly and driven by major technology companies
(Google and Apple) as well as those specialising in sports clothing (Nike and Adidas). This is
a huge industry with an expected market worth of $2.86 billion dollars by 2025(53). There is
7
currently no out right leader in the field. The key factors in wearable sensor growth are a
combination of higher user demand, advancement in sensor technologies resulting in
miniaturisation, reduced production costs, coupled with both wireless communication streams
and a longer battery life.
Wearable bio sensors are non-invasive devices that capture, transmit and process health
related data(54). Ideal sensors should be low cost, reliable, light weight, easy to wear, easy to
use, have a long battery life and allow the wearer to ambulate normally. Thus, far there is
little in the literature for wearable sensor use in routine ward-based patient care.
This paper reviews wearable sensors that can measure multiple vital signs continuously.
Whilst most available sensors are consumer graded there are a few manufacturers that have
obtained European Conformity (CE) and or Food and Drug Administration (FDA) approvals
for use in hospital settings. Whilst this was not a systematic review our search strategy used
Ovid, Medline and Google. Only those wearables that have both FDA and CE marking
approvals will be described. The search was reviewed by both authors MJ and HS.
8
2. Expert commentary – continuous wearable sensors measuring multiple parameters
2.1 Early Sense Monitoring System
The Early Sense Monitoring System measures HR, beat-to-beat fluctuations (i.e. RR
intervals) and bed motion. The sensor is placed under the patient’s mattress and is a non-
disposable sensor. It is attached to the bedside monitor and display centre for healthcare
professionals via a wire (26). The system consists of a sensor under the bed, a bedside
monitor, a central display station and software. As the sensor is attached to a mains power
supply the battery life of the sensor is not a factor. The system can alert to a bedside unit,
central display station and a mobile device. As this sensor is not directly attached to the
patient there are no concerns about the weight of the sensor. The sensor can only be used
when the patient is in bed (55). The Early Sense system is perhaps the most researched
monitoring system to date; it has been tested on patients and has both FDA and CE marking
approvals. In a study involving a 316-bed community hospital two models were constructed.
Model A was a care based model in which the estimated total cost savings of intervention
effects were reviewed. Whilst model B was a conservative model in which only the direct
variable cost component for the final day of length of stay and treatment of pressure ulcers
was included (56).When evaluating the costs of the system both cost models found a positive
return on investment when used in both surgical and medical wards(56).
Its use on medical and surgical wards has shown to significantly reduce both the length of
stay and Intensive Care Unit days for transferred patients(41). The estimated reduction in
length of stay is likely to be attributable to the continuous monitoring of vital signs reflecting
the earlier detection and more effective intervention for clinical problems which are known to
prolong both ICU and hospital stay(41). Thus, far to our knowledge this has mainly been
used for research purposes as opposed to routine clinical care. The main limitations of the
system are that it is only of use whilst the patient is in bed and is currently unable to interface
with the electronic medical record.
2.2 Vital Connect HealthPatch™
The Vital Connect HealthPatch™ is an alternative light weight sensor that monitors a total of
eight vital signs; single lead Electrocardiography (ECG), HR, HR variability, RR, skin
9
temperature, body posture, fall detection and activity (57). There is a wireless adhesive sensor
that is placed on the patient’s chest. The patch is disposable with a battery life of 4 days and
has been tested on patients (57). The specifications are a weight of 11grams and size of 11.5
x 3.6 x 0.8 cm. The vital connect sensor transmits signals via Bluetooth to a centralised
monitoring device and via text to a mobile device. It is both FDA approved and CE marked.
Like similar sensors described above it can transmit real time continuous observation data at
a sampling frequency of 125Hz(27). The patch was validated in health individuals
undergoing various physiological assessments such as exercising. A comparison was made
between the patch and standard reference monitoring and 3 patches were placed on each
patient (27). The patches were placed in three possible locations: (1) in a modified lead-II
configuration on the left midclavicular line over intercostal space (ICS) 2, (2) vertically over
the upper sternum, or (3) horizontally on the left midclavicular line over ICS 6(27). The
monitoring used was a Actiheart device for heart rate, oxygen cannula attached to an Oridion
Capnostream capnography monitor for respiratory rate and two pedometers (Omron and
FitBit) for measuring steps(27). The patch was proven to be accurate. In comparison to the
reference monitoring the heart rate measurement had a mean absolute error (MAE) of less
than 2 bpm(27). Respiratory rate had an MAE of 1.1 breaths per minute during metronome
breathing(27). The posture detection had an accuracy of over 95% in two of the three patch
locations, steps were counted with an absolute error of less than 5%, and falls were detected
with a sensitivity of 95.2% and specificity of 100%(27). However, there was a very small
sample size of 25 healthy participants. The patch was tested in well elderly subjects with
various medical co-morbidities over 50 consecutive days in their homes(58). The patch
sensor was paired to a smart phone in which data streams could be reviewed in real-time. HR,
RR and skin temperature estimated the mean absolute errors to be <3 beats/min, <3
breaths/min and <1.2 ◦C, compared to reference monitoring(58). This data suggests that it
may be possible to use such a patch at home for monitoring of both elderly and vulnerable
patients.
2.3 Sotera Wireless VisiMobile System
The ViSiMobile System continuously measures HR, ECG, RR, oxygen saturation level, skin
temperature and non-invasive blood pressure(28). The sensor is worn around the wrist and
has a thumb sensor for oxygenation saturation. The main unit of the sensor weights 110
grams. The size dimensions are; 2.6 cm in height x 4.9 cm in width x 9.4 cm in length. The
10
battery life for this system is between 12-14 hours before it needs to be recharged. It uses Wi-
Fi technology, can integrate into the electronic health systems and send alerts to tablets or
smartphones for significant changes in vital signs. The ViSiMobile System has been FDA
approved and CE marked. It has been used in a study at the John Hopkins Hospital for
patients on a surgical ward (59). This was run as a quality improvement pilot study, the
results of which are currently being analysed. The early results from this study are
encouraging. The 3-month surveillance has identified patients with pulmonary emboli, the
early stage sepsis, myocardial infarction and atrial fibrillation. On discharge 98% of patients
showed satisfaction with the system. The satisfaction from nursing staff was recorded at 70-
75%. A concern for multi parameter continual vital sign monitoring is the risk of alarm
fatigue; which occurs when one is exposed to frequent alarms they can become desensitised.
This system in particular has been shown to have low rates of alarm fatigue(60).
2.4 Sensium Vitals Monitoring Technology
This is a wearable, wireless, continuous monitoring device for inpatients in a ward setting. It
is able to measure HR, RR and axillary temperature(29). It is a low cost, single use, low
powered device with near real time vitals every 2 minutes and a battery life of 5 days. The
patch is attached to the patient’s chest via ECG electrodes and a wire is attached around the
patients back with a sensor measuring axillary temperature. The battery life for this sensor is
up to 5 days. The lower power consumption is a real strength of this product over its
competitors. The data from the sensor is transmitted via radiofrequency to a centralised
monitoring device or smartphone. The sensor is both FDA approved and CE marked. The
patch has been tested in 60 patients and has been shown to have reliable heart rate values(61).
The study was performed in recovery after patients underwent routine surgery and on a
general ward. The wearable patch has ambulatory algorithms which insure that noisy or
irregular signals are not reported to ensure a reduction in false alerts and alert fatigue(29)(62).
2.5 Philips Bio Sensor
The Philips Bio Sensor is small light weight sensor measuring HR, RR, skin temperature,
body posture, fall detection, single lead ECG, RR-interval and step count(30). It is a wireless
self-adhesive sensor worn on the chest. It weighs 12 grams and the size dimensions are 1cm x
3.6cm x 0.8 cm. During a normal ECG waveform, the R interval equates to a point
corresponding to the peak of the QRS complex. The RR-interval in this context is the interval
11
between successive R peaks on an ECG. The Philips Bio Sensor is disposable and has a
battery life of 4 days. The sensor technology is ECG electrodes that detect heart rate, a
thermistor to detect skin temperature and 3 axis accelerometer to detect motion(30). The
patient data is transmitted via Bluetooth to an IntelliVue Guardian Software tool which can
integrate into electronic medical records and alert to smart phone devices. The sensor is both
FA approved and CE marked. There are currently no research papers with the use of the
sensor on the wards for continuous monitoring.
2.6 Isansys Lifetouch Sensors
The Lifetouch manufactured by Isansys and is a small light weight wireless wearable sensor
that examines the ECG trace to extracts the HR, RR, and heart rate variability before relaying
information to a central server(31). The Life touch weighs 7 grams and sensor dimensions for
a small sensor are 14cm x 4.7cm x 0.95cm. It is attached to the patient’s chest via ECG
electrodes(31).This sensor battery life is between 4- 6 days as a maximum(31). It transmits
data via Bluetooth and can be transferred into electronic health systems. This is FDA and CE
marked. There is another sensor they have called Lifetemp which sticks to the body by using
silicone gel adhesive and is normally placed in the axilla(31). It can continuously measure
relative skin temperature from patients and transmit readings wirelessly to a blue tooth
enabled receiver. There are currently no research papers with the use of the sensor on the
wards for continuous monitoring.
2.7 Zephyr Bio-HarnessTM
The Bio-HarnessTM has been used predominantly for commercial purpose, it has been tested
in fields such as sport and the military(32). The sensor can measure HR, HR Variability, RR,
temperature, posture and accelerometry data. HR is captured through electrode sensors within
the chest strap and reported as beats per minute(63). RR is measured using a capacitive
pressure sensor that detects expansion and contraction of the torso and gives an output of
breaths per minute(63). Triaxial accelerometry uses piezoelectric technology and reports 1Hz
per second(63). There is also a micro electro-mechanical sensor accelerometer with a
12
capacitive measurement scheme and is sensitive along 3 orthogonal axes (vertical, sagittal
and lateral)(63). The skin temperature is measured using an infrared sensor through a clear
window at the apex of the device(63). These parameters were tested using a repeated,
discontinuous incremental treadmill protocol(63). The coefficient of variation was low for
HR, accelerometery, posture and skin temperature(63). RR was less reliable(63). This is a
wearable sensor with an elasticated belt that is typically worn around the chest(32). The
sensor is non disposable with a battery life of 24 hours. The data is transmitted via ECHO or
Bluetooth to a centralised display. The sensor is both FA approved and CE marked. There are
currently no research papers with the use of the sensor on the wards for continuous
monitoring.
2.8 Advanced Medical mONitoring (AMON) Wearable Sensor
Advanced Medical mONitoring (AMON) is a wearable sensor that can continuously measure
HR, oxygen saturations and temperature of a patient (33). It is a wrist worn sensor and
weighs 286 grams. The sensor is a non-disposable sensor with a variable battery life
depending on power consumption. The data is uploaded via Wi-Fi to centralised monitoring
and can incorporate into electronic health records. In addition, it can measure the level of
physical activity, blood pressure and one lead ECG when necessary. This sensor has both
FDA approval and CE marking. Automatic alerts can be sent to the healthcare team if any
deviations are found in measurements. In a study of 33 healthy volunteers the accuracy of
the device when compared to manual observations was questioned(33). There was initially a
design flaw in the pulse algorithm; once corrected 85% had a difference of less than 5 beats
per minute(33). There was unfortunately great deviation in the oxygen saturations measured
and there was no ECG concordance apart from HR(33). There are currently no research
papers with the use of the sensor on the wards for continuous monitoring.
A summary of each wearable sensor and the vital signs measured can be found in table 1.
A further description of each wearable sensor can be found in table 2.
13
Conclusions
3.1 Comparison of the sensors described
A range of sensors measuring a variety of vital signs have been described above and the
results are encouraging. Wearable sensors and digital technology have the potential to
improve patient safety for both hospital patients and those at home. Several sensor designs
are available. The Early Sense monitoring system sensor is placed under the mattress.
Although useful for some patients those that are ambulating on the wards or in a chair next to
the bed for example would not receive monitoring. Several sensors were placed on the chest
either through adhesives or ECG electrodes (Vital Connect, Sensium, Philips and Isansys).
These can easily be worn under the patient’s clothes and are unobtrusive. The wrist worn
sensors were the Amon and VisiMobile ones whilst the Zephyr sensor is worn around the
chest. All the sensors described above measure HR which is the most commonly measured
vital sign. Respiratory rate and temperature were the second most commonly measured vitals.
No system yet exists that can perform all routine observations. For example, assessing
cognitive levels are difficult to assess using wearable sensors. In addition, there is yet
insufficient data to allow wearable sensors to replace routine ward observations.
The power consumption of the sensors is quite variable; the VisiMobile system battery life
was 12-14 hours whilst the Sensium vitals patch could be worn for up to 5 days. All sensors
reviewed in this study had a combination of FDA and or CE marking approvals. Due to the
nature of a google search there may be potential bias in the selection of sensors.
3.2 Future challenges
Future challenges of using sensor technology to measure vital signs is the need for sensors
and data transmission to be reliable, accurate, as well as to ensure that the collected patient
data is securely saved (64). Accuracy compares sensor readings to the current gold standard
of ward observations to see how close together the readings are. Whilst reliability ensures
that the sensor will calculate the correct vital signs all the time. For widespread wearable
sensor use they must be both accurate and reliable. The combination of battery life, size,
accuracy and reliability of a sensor in practice will determine its usage. There is a need to
reduce power consumption of the sensor electronics to extend the battery life. If the battery
life is poor and needs constant replacement this would cause a significant inconvenience for
14
patients and healthcare staff alike, reducing user satisfaction and sensor uptake. Large heavy
sensors will inevitably reduce usability for end users. There are a few trials that have used
wearable sensors in a hospital setting but these have small numbers of patients (61)(65)(66).
Non-industry led larger trials are needed to ensure independent accuracy and reliability.
Once reliability and accuracy are proven more widespread sensor use can take place. There is
the potential for use in the community by patients with chronic medical conditions or high
risk patients at risk of deterioration such as the elderly. If there is suitable safe monitoring in
the home environment clinicians may be more likely to discharge patients sooner from
hospital. A centralised review of the data could be carried out by outreach services such as
hospital at home. The costs of outreach services, sensors and supporting software require
must be reviewed. There is little in the literature thus far on the economics of sensor use.
Some of the newer wearable sensors have the potential to be used at home. The monitoring of
vital signs at home has been shown to reduce resource utilisation and facilitate the
management of patients with heart failure in the community(67). A wearable sensor patch
worn by patients at home has been show to detect irregular heartbeats such as atrial
fibrillation(68). This can be reassuring for both patients and hospital staff. A typical example
of potential home sensor use is patients’ post-surgery, where complications may develop
several days after the patient has been discharged. At home monitoring of a patient’s vital
signs may alert staff at the hospital if the patient becomes unwell. Additionally, a patient with
normal observations can be more reassuring. At home monitoring of both HR and RR has
been performed previously(69). It is hoped in the future that other vital signs such as level of
cognition may be measured through wearable sensors allowing for more a complete vital
signs assessment that can be used to populate scoring systems such as NEWS.
As well as vital signs, it is possible that wearable sensors can measure other parameters such
as accelerometer data. These sensors may be useful to monitor patients with mobility
difficulties such as those with Parkinson’s disease and facilitate the titration of medication in
the late stages of disease(70). Unintentional falls can cause significant injury in elderly
patients. It may be possible to use non-invasive wireless sensors worn around the waist to
detect a fall occurrence and the location of the person with a fall(71).
15
3.3 Sensor integration and training
However great the sensor technology is, it is reliant on the way it is delivered to the medical
team. It must be delivered to the clinicians in an easy user friendly format to encourage use.
Newer sensor technology enables digital alerts to be sent to hand held devices such as smart
phones. The smart phone technology is readily available and often used by many in their
everyday lives. In this way, it may be easily co-ordinated into the healthcare professional’s
lifestyle without the need for extensive training which occurs with alternative technology.
The network capacity in sensor technology must with stand the large amounts of data
generated both from the sensors and the communication device used to relay this information.
Whilst having FDA approval and CE marking is required sensor integration in a clinical
setting is often challenging. The sensors described in this review measure vital signs which
are routinely measured in a clinical setting. Other types of sensor may measure physiological
‘signals’ and these may be difficult to interpret in clinical practice. The workload after the
introduction of sensors may change due to the use of wearable sensors and digital alerting.
Clinicians may not have the time to measure large quantities of data on a daily basis and a
‘data deluge’ effect may occur(72). Therefore ‘Intelligent’ data processing systems are
required to support healthcare staff and allow for predictive monitoring of patients to identify
those patients most at risk (72). Successful implementation of wearable sensors may rely on
good integration with current clinical systems and processes. Currently many NHS trusts are
adopting electronic health records. Data from the wearable sensors should be easily
incorporated into electronic health records. In a clinical study of patients using wearable
sensors in real ward settings, patient wearing the ECG sensor found it too uncomfortable for
prolonged use. In addition, data dropout was a huge challenge due to infrastructure problems
(interruptions in Wi-Fi) and expired sensor batteries (72). Prior to widespread
implementation the hospital infrastructure should be developed enough to support the new
technology. It is not just the sensors themselves but the way that the data from the sensor is
received handled and processed in the most effective way. Strategies for interruptions in Wi-
Fi for example should be developed and readily available at the start of the project. Whilst it
may be useful to have alerting within centralised electronic health records these would
require the clinical staff to be at a work station a majority if the time. There must be sufficient
work stations in all clinical areas for healthcare staff to use as well as more portable systems
for when staff are not at their desk. This would include alerts being sent to smart phones and
16
personal device assistants.
There are currently many innovative technological tools flooding healthcare. There are
several strategies that have been suggested to improve successful implementation particularly
in the acute setting. These include; early input from staff on the new technology, appropriate
education, accessibility to the technology combined with early evaluation and feedback to
staff(73). The adoption of any new technologies relies on successful staff engagement. There
are several strategies in place that can help. One of the key factors in workforce engagement
methodology is to enable involvement in the decision making process(74). In addition all
roles within the hospital should be considered and adequate training provided(74).
Overall wearable sensors create an exciting opportunity to improve patient safety both in the
hospital and for users at home. An engaged healthcare work force is vital to ensuring their
success. Larger studies are required in a hospital setting and a good evidence base needed
before large scale roll out.
4. Five-year view
It is anticipated that wearable sensors are the future and will form an integral aspect of patient
care both in hospital and at home. As reliability and diagnostic accuracy are established and
enhanced, their use will become increasingly widespread. It is anticipated that over the next 5
years much of the focus of work will be in the hospital setting and follow-up and post-
discharge settings or for at risk patients within the community. Those new acutely unwell
patients admitted to the hospital might be the individuals that may benefit most from these
technologies in their early distribution. In addition, high risk groups of patients such as those
on immunosuppressive treatments may routinely have a wearable sensor as standard care.
The wearable sensor technologies will only be adopted if they are adequately supported by
evidence with appropriate and safe training of all staff and patients using these devices.
17
5. Key messages
5.1 Further larger scale studies are required in patients to review the effects of
wearable sensors.
5.2 Wearable sensor technology should have the ability to integrate into electronic
health records.
5.3 Ideally wearables should be able to measure multiple vital sign parameters
simultaneously.
5.4 Healthcare work force engagement in sensor technology is vital to ensuring their
success.
5.5 Sensors need to have a high diagnostic accuracy (and low number of false
positives) results to ensure healthcare engagement.
5.6 The cost-effectiveness of wearable sensors and potential costs savings should be
reviewed.
18
6 Expert Commentaries
6. 1 Key weaknesses in management so far
It is known that patients admitted to general wards are still falling through the safety nets.
Whilst there have been substantial improvements in patient safety; patient deterioration is
often missed and referrals and escalation to more intense levels (such as ITU) are late. Some
patient groups are typically presenting to hospital later and more unwell; the elderly
population is increasing and many patients have multiple co-morbidities. The acute admitting
wards such as the acute medical and surgical wards have a high turnover of patients with
altered physiology and rapid patient deterioration. This is coupled with increased pressures
on nursing staff and high numbers of temporary staff. These factors can make the
identification of early patient deterioration particularly challenging. Whilst the track and
trigger approach to care has been helpful, the actual way that the vital signs are measured has
not changed significantly over several decades and could benefit from fundamental
enhancement.
6.2 Potential Goal of the future
Continuous monitoring through wearable sensor technologies may help provide some of the
solutions to offer closer monitoring for patients. Wearable sensors have undergone a huge
recent growth. The newer sensors are smaller, lighter, wireless, have longer battery lives and
more processing power than their predecessors. The goal is for all patients that show signs of
deterioration to be identified early so they can be given treatment sooner. This may help to
prevent some of the adverse outcomes associated with delayed identification. Whilst the
sensors in this paper have focused on the traditional vital signs it may be that newer sensors
which measure arterial pressure and flow waveforms may be the future.
6.3 Ultimate goals
The goal is to have a discrete wearable sensor that is well tolerated by all patients and staff
which correctly identifies acute deteriorating patients in real time. The sensor ideally should
be able to measure all vital signs. Developing a sensor that can measure real time blood
pressure and level of cognition is a real challenge for the future. The first goal is to ensure
19
that the sensors are reliable by independent researchers in large-scale high quality trials with
appropriate clinical endpoints.
6.4 Expected Challenges
The expected challenges are several fold. The first are the sensors themselves; they may need
to be smaller still with longer battery lives, with good reliability and accuracy. They also
must have great diagnostic accuracy to reduce the number of false alerts and the potential for
alert fatigue, and should, ideally measure all vital signs including blood pressure and level of
cognition so track and trigger scores can be calculated. The integration of them into the
existing medical health record is essential for long-term uptake. All sensors should be used as
an adjunct to care and not limit the staff and patient interaction. A proactive risk assessment
for the implementation of wearable sensors has been suggested(75). A carefully designed
implantation will help ensure successful integration into clinical workflows preventing
problems and potential harm to patients(75). An evaluation would be performed focusing on
the normal procedures and actions required for sensor use. In this way potential challenges
hope to be identified and addressed (75). A proactive assessment can help address which
patients will wear the wearable sensors and which clinical areas may require them the most
(75). Lastly, the economic costs of the sensors must be reviewed and should be cost effective
prior to wide scale roll out.
6.5 Areas of interest
Ultimately these sensors with provide a whole new archetype of real-time continuous patient
physiological assessment; these will link into the digital and big-data analytical platforms for
the next-generation of healthcare where they will act as a catalyst for even better early
diagnostics, preventions and cures.
20
References
1. National Confidential Enquiry into Patient Outcomes and Death. An acute problem?
London: National Confidential Enquiry into Patient Outcome and Death, 2005.
2. Acutely ill patients in hospital: recognition of and response to acute illness in adults in
hospital. 2007;
3. McQuillan P, Pilkington S, Allan A, Taylor B, Short A, Morgan G, et al. Confidential
inquiry into quality of care before admission to intensive care. BMJ. 1998 Jun
20;316(7148):1853–8.
4. Smith GB. In-hospital cardiac arrest: Is it time for an in-hospital ‘chain of prevention’?
Vol. 81, Resuscitation. 2010.
5. DeVita MA, Smith GB, Adam SK, Adams-Pizarro I, Buist M, Bellomo R, et al.
“Identifying the hospitalised patient in crisis”—A consensus conference on the afferent
limb of Rapid Response Systems. Resuscitation. 2010;81(4):375–82.
6. Sax FL, Charlson ME. Medical patients at high risk for catastrophic deterioration. Crit
Care Med. 1987 May;15(5):510–5.
7. Smith AF, Wood J. Can some in-hospital cardio-respiratory arrests be prevented? A
prospective survey. Resuscitation. 1998 Jun;37(3):133–7.
8. Kenzaka T, Okayama M, Kuroki S, Fukui M, Yahata S, Hayashi H, et al. Importance
of Vital Signs to the Early Diagnosis and Severity of Sepsis: Association between
Vital Signs and Sequential Organ Failure Assessment Score in Patients with Sepsis.
Intern Med. 2012;51:871–6.
9. Bloos F, Reinhart K. Rapid diagnosis of sepsis. Virulence. 2014 Jan 1;5(1):154–60.
10. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-
hospital cardiopulmonary arrest. Chest. 1990 Dec;98(6):1388–92.
11. Franklin C, Mathew J. Developing strategies to prevent inhospital cardiac arrest:
analyzing responses of physicians and nurses in the hours before the event. Crit Care
Med. 1994 Feb;22(2):244–7.
12. GE Carescape V100 Dinamap Vital Signs Monitor From £1,249 | Numed Healthcare
[Internet]. [cited 2018 Oct 8]. Available from:
https://www.numed.co.uk/products/carescape-v100-dinamap-vital-signs-monitor
21
13. Welch Allyn. Welch Allyn Vital Signs Devices and Monitors. 2016.
14. Cretikos MA, Bellomo R, Hillman K, Chen J, Finfer S, Flabouris A. Respiratory rate:
The neglected vital sign. 2008 Jun 2;188(11):657–9.
15. Royal College of Physicians. National Early Warning Score (NEWS) 2 Standardising
the assessment of acute-illness severity in the NHS Updated report of a working party
Executive summary and recommendations The Royal College of Physicians. 2017;
(2017):3.
16. Chen J, Hillman K, Bellomo R, Flabouris A, Finfer S, Cretikos M. The impact of
introducing medical emergency team system on the documentations of vital signs.
Resuscitation. 2009;80(1):35–43.
17. Hands C, Reid E, Meredith P, Smith GB, Prytherch DR, Schmidt PE, et al. Patterns in
the recording of vital signs and early warning scores: compliance with a clinical
escalation protocol. BMJ Qual Saf. 2013 Sep;22(9):719–26.
18. Buist M, Stevens S. Patient bedside observations: what could be simpler? BMJ Qual
Saf. 2013 Sep;22(9):699–701.
19. Smith AF, Oakey RJ. Incidence and significance of errors in a patient “track and
trigger” system during an epidemic of Legionnaires’ disease: retrospective casenote
analysis. Anaesthesia. 2006 Mar;61(3):222–8.
20. Smith GB, Prytherch DR, Schmidt P, Featherstone PI, Knight D, Clements G, et al.
Hospital-wide physiological surveillance-A new approach to the early identification
and management of the sick patient. Resuscitation. 2006;71(1):19–28.
21. Prytherch DR, Smith GB, Schmidt P, Featherstone PI, Stewart K, Knight D, et al.
Calculating early warning scores—A classroom comparison of pen and paper and
hand-held computer methods. Resuscitation. 2006 Aug;70(2):173–8.
22. Mohammed M, Hayton R, Clements G, Smith G, Prytherch D. Improving accuracy
and efficiency of early warning scores in acute care. Br J Nurs. 2009;18(1):18–24.
23. Edwards M, McKay H, Van Leuvan C, Mitchell I. Modified Early Warning Scores:
inaccurate summation or inaccurate assignment of score? Crit Care. 2010;14(Suppl
1):P257.
24. Preece MHW, Hill A, Horswill MS, Watson MO, Massey D, Aitken LM, et al.
Supporting the detection of patient deterioration: observation chart design affects the
22
recognition of abnormal vital signs. Resuscitation. 2012 Sep;83(9):1111–8.
25. Christofidis MJ, Hill A, Horswill MS, Watson MO. Observation charts with
overlapping blood pressure and heart rate graphs do not yield the performance
advantage that health professionals assume: an experimental study. J Adv Nurs. 2014
Mar;70(3):610–24.
26. Center C, Portland O, Helfand M, Christensen V. EarlySense for Monitoring Vital
Signs in Hospitalized Patients. 2016;
27. Chan AM, Selvaraj N, Ferdosi N, Narasimhan R. Wireless Patch Sensor for Remote
Monitoring of Heart Rate, Respiration, Activity, and Falls. 2013;
28. Resources - Sotera Wireless [Internet]. [cited 2017 Apr 27]. Available from:
http://www.soterawireless.com/resources/
29. Sensium | Early detection of patient deterioration [Internet]. [cited 2017 Feb 2].
Available from: https://www.sensium.co.uk/
30. View details of Philips Wearable biosensor [Internet]. [cited 2017 Feb 8]. Available
from: http://www.usa.philips.com/healthcare/product/HC989803196871/wearable-
biosensor-wireless-remote-sensing-device
31. isansys: sensors [Internet]. [cited 2017 Feb 8]. Available from:
http://www.isansys.com/en/products/sensors
32. ZephyrTM Performance Systems | Performance Monitoring Technology [Internet].
[cited 2017 Apr 27]. Available from: https://www.zephyranywhere.com/
33. Anliker U, Ward JA, Lukowicz P, Tröster G, Dolveck F, Baer M, et al. AMON: A
Wearable Multiparameter Medical Monitoring and Alert System. IEEE Trans Inf
Technol Biomed. 2004;8(4).
34. Goldhill DR, White SA, Sumner A. Physiological values and procedures in the 24 h
before ICU admission from the ward. Anaesthesia. 1999 Jun;54(6):529–34.
35. Convertino VA, Wirt MD, Glenn JF, Lein BC. The compensatory reserve for early and
accurate prediction of hemodynamic compromise: A review of the underlying
physiology. Shock. 2016;45(6):580–90.
36. Bruijns SR, Guly HR, Bouamra O, Lecky F, Lee WA. The value of traditional vital
signs, shock index, and age-based markers in predicting trauma mortality. J Trauma
Acute Care Surg. 2013;74(6):1432–7.
23
37. Orlinsky M, Shoemaker W, Reis ED, Kerstein MD. Current controversies in shock and
resuscitation. Surg Clin North Am. 2001;81(6):1217–62.
38. Wo CC, Shoemaker WC, Appel PL, Bishop MH, Kram HB, Hardin E. Unreliability of
blood pressure and heart rate to evaluate cardiac output in emergency resuscitation and
critical illness. Crit Care Med. 1993 Feb;21(2):218–23.
39. Parks JK, Elliott AC, Gentilello LM, Shafi S. Systemic hypotension is a late marker of
shock after trauma: a validation study of Advanced Trauma Life Support principles in
a large national sample. Am J Surg. 2006;192(6):727–31.
40. Pickham D, Berte N, Pihulic M, Valdez A, Mayer B, Desai M. Effect of a wearable
patient sensor on care delivery for preventing pressure injuries in acutely ill adults: A
pragmatic randomized clinical trial (LS-HAPI study). Int J Nurs Stud. 2018
Apr;80:12–9.
41. Brown H, Terrence J, Vasquez P, Bates DW, Zimlichman E. Continuous monitoring in
an inpatient medical-surgical unit: A controlled clinical trial. Am J Med.
2014;127(3):226–32.
42. Brown H, Terrence J, Vasquez P, Bates DW, Zimlichman E. Continuous Monitoring
in an Inpatient Medical-Surgical Unit: A Controlled Clinical Trial. Am J Med. 2014
Mar;127(3):226–32.
43. Steinhubl SR, Waalen J, Edwards AM, Ariniello LM, Mehta RR, Ebner GS, et al.
Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of
Undiagnosed Atrial Fibrillation The mSToPS Randomized Clinical Trial. 2018;92037.
44. Watkinson PJ, Barber VS, Price JD, Hann A, Tarassenko L, Young JD. A randomised
controlled trial of the effect of continuous electronic physiological monitoring on the
adverse event rate in high risk medical and surgical patients.
45. Kehlet H. Multimodal approach to control postoperative pathophysiology and
rehabilitation. Vol. 78, British Journal of Anaesthesia. 1997.
46. Gustafsson UO, Hausel J, Thorell A, Ljungqvist O, Soop M, Nygren J. Adherence to
the Enhanced Recovery After Surgery Protocol and Outcomes After Colorectal Cancer
Surgery. Arch Surg. 2011 May 1;146(5):571.
47. Needham DM, Korupolu R, Zanni JM, Pradhan P, Colantuoni E, Palmer JB, et al.
Early Physical Medicine and Rehabilitation for Patients With Acute Respiratory
24
Failure: A Quality Improvement Project. Arch Phys Med Rehabil. 2010 Apr
1;91(4):536–42.
48. Needham DM. Mobilizing Patients in the Intensive Care Unit. JAMA. 2008 Oct
8;300(14):1685.
49. Leuvan CH Van, Mitchell I. Missed opportunities? An observational study of vital sign
measurements. Crit Care Resusc. 2008 Jun;10(2):111–5.
50. Badawy J, Nguyen OK, Clark C, Halm EA, Makam AN. Is everyone really breathing
20 times a minute? Assessing epidemiology and variation in recorded respiratory rate
in hospitalised adults. BMJ Qual Saf. 2017 Oct;26(10):832–6.
51. Dunn J, Runge R, Snyder M. Wearables and the medical revolution. 2018;
52. Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, et al. Duration of
hypotension before initiation of effective antimicrobial therapy is the critical
determinant of survival in human septic shock*. Crit Care Med. 2006;34(6):1589–96.
53. Wearable Sensors Market Worth $2.86 Billion By 2025 | CAGR: 38.8% [Internet].
[cited 2018 May 12]. Available from: https://www.grandviewresearch.com/press-
release/wearable-sensors-market
54. Andreu Perez J, Leff D, Ip H, Yang G-Z. From Wearable Sensors to Smart Implants -
Towards Pervasive and Personalised Healthcare. IEEE Trans Biomed Eng.
2015;PP(99):1.
55. early sense monitoring system - Google Search [Internet]. [cited 2017 Apr 27].
Available from: https://www.google.co.uk/search?
q=early+sense+monitoring+system&client=safari&rls=en&source=lnms&tbm=isch&s
a=X&ved=0ahUKEwiS8qbhjcTTAhUgOsAKHb36CjsQ_AUICygC&biw=1440&bih=
816#imgdii=2HPB2voDC8HpaM:&imgrc=IVK0wYMESL5fKM:
56. Slight SP, Franz C, Olugbile M, Brown H V., Bates DW, Zimlichman E. The Return
on Investment of Implementing a Continuous Monitoring System in General Medical-
Surgical Units*. Crit Care Med. 2014 Aug;42(8):1862–8.
57. Home - VitalConnect [Internet]. [cited 2017 Apr 18]. Available from:
https://vitalconnect.com/
58. Selvaraj N. Long-term remote monitoring of vital signs using a wireless patch sensor.
2014 IEEE Healthc Innov Conf HIC 2014. 2014;83–6.
25
59. Miller PJ. Continuous monitoring of patient vital signs to reduce “failure-to-rescue”
events. Biomed Instrum Technol. 2017;51(1):41–5.
60. Welch J, Kanter B, Skora B, McCombie S, Henry I, McCombie D, et al. Multi-
parameter vital sign database to assist in alarm optimization for general care units. J
Clin Monit Comput. 2015;30(6):895–900.
61. Hernandez-Silveira M, Ahmed K, Ang S-S, Zandari F, Mehta T, Weir R, et al.
Assessment of the feasibility of an ultra-low power, wireless digital patch for the
continuous ambulatory monitoring of vital signs. BMJ Open. 2015 May
19;5(5):e006606.
62. Burdett Cto A, Group T. A Wearable, Wireless Early Warning System for Enhanced
Patient Outcomes. 2015;
63. Johnstone JA, Ford PA, Hughes G, Watson T, Garrett AT. BioharnessTM multivariable
monitoring device. Part II: Reliability. J Sport Sci Med. 2012;11(3):409–17.
64. Yilmaz T, Foster R, Hao Y. Detecting vital signs with wearablewireless sensors.
Sensors. 2010;10(12):10837–62.
65. Weenk M, van Goor H, Frietman B, Engelen LJ, van Laarhoven CJ, Smit J, et al.
Continuous Monitoring of Vital Signs Using Wearable Devices on the General Ward:
Pilot Study. JMIR mHealth uHealth. 2017 Jul 5;5(7):e91.
66. Breteler MJM, Huizinga E, van Loon K, Leenen LPH, Dohmen DAJ, Kalkman CJ, et
al. Reliability of wireless monitoring using a wearable patch sensor in high-risk
surgical patients at a step-down unit in the Netherlands: a clinical validation study.
BMJ Open. 2018;8(2):e020162.
67. Heidenreich PA, Ruggerio CM, Massie BM. Effect of a home monitoring system on
hospitalization and resource use for patients with heart failure. Am Heart J. 1999;138(4
I):633–40.
68. Steinhubl SR, Feye D, Levine AC, Conkright C, Wegerich SW, Conkright G.
Validation of a portable, deployable system for continuous vital sign monitoring using
a multiparametric wearable sensor and personalised analytics in an Ebola treatment
centre. BMJ Glob Heal. 2016;1.
69. Adib F, Mao H, Kabelac Z, Katabi D, Miller RC. Smart Homes that Monitor Breathing
and Heart Rate. Proc 33rd Annu ACM Conf Hum Factors Comput Syst - CHI ’15.
26
2015;837–46.
70. Chen BR, Patel S, Buckley T, Rednic R, McClure DJ, Shih L, et al. A web-based
system for home monitoring of patients with Parkinson’s disease using wearable
sensors. IEEE Trans Biomed Eng. 2011;58(3 PART 2):831–6.
71. Chen J, Kwong K, Chang D, Luk J, Bajcsy R. Wearable Sensors for Reliable Fall
Detection. In: 2005 IEEE Engineering in Medicine and Biology 27th Annual
Conference. IEEE; 2005. p. 3551–4.
72. Clifton L, Clifton DA, Pimentel MAF, Watkinson PJ, Tarassenko L. Predictive
Monitoring of Mobile Patients by Combining Clinical Observations With Data From
Wearable Sensors. IEEE J Biomed Heal INFORMATICS. 2014;18(3).
73. Langhan ML, Riera A, Kurtz JC, Schaeffer P, Asnes AG. Implementation of newly
adopted technology in acute care settings: a qualitative analysis of clinical staff. J Med
Eng Technol. 2015 Jan;39(1):44–53.
74. NHS. The Staff Engagement Toolkit Staff Engagement in the NHS: A Quick Guide.
2013;2013(December):1–97.
75. Kowalski R, Capan M, Lodato P, Mosby D, Thomas T, Arnold R, et al. Optimizing
usability and signal capture: a proactive risk assessment for the implementation of a
wireless vital sign monitoring system. 2017;
27
Table 1.: Is a summary of each wearable sensor and the vital signs measured.
28
Device Heart
Rate
Heart Rate
Variability/ RR
Interval
Single Lead
Electrocardiography
Respiratory
Rate
Skin
Temperature
Bed Motion Body
Posture
Fall
Detection
Activity Oxygen
Saturations
Non-invasive
Blood
Pressure
Current Monitoring
Devices
Yes Yes Yes Yes
Early Sense
monitoring (26)
Yes Yes Yes
Vital Connect (27) Yes Yes Yes Yes Yes Yes Yes Yes
VisiMobile System
(28)
Yes Yes Yes Yes Yes Yes
Sensium Vitals (29) Yes Yes Yes
Philips Bio
Sensor (30)
Yes Yes Yes Yes Yes Yes Yes Yes
Isansys Life Touch
Sensor (31)
Yes Yes Yes
Zephyr Wearable
Sensor (32)
Yes Yes Yes Yes Yes Yes
Amon wearable
Sensor (33)
Yes Yes, measured 3
times a day or on
request
Yes Yes Yes Yes, measured
3 times a day
or on request
29
Table 2.: A description of each wearable sensor.
Device Description of sensor Duration
/ sensor use
Disposable Tested on Patients
Approval EHR Integration Mechanisms of alerting
Early Sense monitoring (26)
Sensor placed under patient’s mattress N/A No Yes FDA Approved + CE marked
No Centralised
Vital Connect (27) Wireless adhesive sensor placed on the chest 4 days Patch disposable, Sensor not disposable
Yes FDA Approved + CE marked
Yes Centralised & Mobile Device
VisiMobile System (28)
Sensor worn around the wrist to measure BP, a chest sensor to measure HR, RR and skin temperature, a thumb sensor for oxygen saturation
Battery Life 12-14 hours
No Yes FDA Approved + CE marked
Yes Centralised & Mobile Device
Sensium Vitals (29) Adhesive sensor on the chest attached via ECG electrodes 5 days Yes Yes FDA Approved + CE marked
Yes Centralised & Mobile Device
Philips Bio Sensor (30) Self-adhesive sensor worn on the chest 4 days Yes Yes FDA Approved + CE marked
Yes Centralised & Mobile Device
Isansys Life Touch Sensor (31)
Adhesive sensor on the chest attached via ECG electrodes 4-6 days Yes Yes FDA Approved + CE marked
Yes Centralised & Mobile Device
Zephyr Wearable Sensor (32)
Sensor worn in a belt, typically around the chest 24 hours No Yes FDA Approved + CE marked
Unknown Centralised
Amon wearable Sensor (33)
Wrist worn sensor Variable depending on power consumption
No Yes FDA Approved + CE marked
Yes Centralised
BP = Blood pressure, HR = Heart Rate, RR = Respiratory Rate, ECG = Electrocardiography, CE = Conformity European (CE), FDA = Food and Drug Administration
30
Top Related