Accuracy of a Wrist-Worn Wearable Device for Monitoring Heart Rates in Hospital Inpatients: A Prospective Observational Study

Compact Vital-Sensing Band with Uninterrupted Power Supply for Core Body Temperature and Pulse Rate Monitoring

Although wearable devices for continuous monitoring of vital signs have undergone significant advancements, their need for frequent recharging precludes continuous operation, potentially leading to adverse outcomes being overlooked. Additionally, the scattered locations of the sensors hamper wearability. Herein, we present a compact vital-sensing band with uninterrupted power supply designed for continuous monitoring of core body temperature (CBT) and pulse rate. The band─which comprises two sensors, a power source (i.e., a flexible thermoelectric generator (TEG) and a battery), and a flexible circuit─is worn on the forearm. The CBT is calculated by measuring the skin temperature and heat flux, while a triboelectric nanogenerator-based self-powered pressure sensor is utilized for pulse rate monitoring. The TEG is a flexible unit that converts body heat into electricity, accumulating a total energy of 314 mJ (100%). Out of this total energy, only 43.2 mJ (7.2%) is utilized for CBT measurements, while the remaining 270.80 mJ (92.8%) is stored in the battery. This enables reliable and continuous operation of the vital-sensing band, highlighting its potential for use in healthcare applications.

Feasibility of Monitoring Heart and Respiratory Rates Using Nonwearable Devices and Consistency of the Measured Parameters: Pilot Feasibility Study

Background

As Japan is the world's fastest-aging society with a declining population, it is challenging to secure human resources for care providers. Therefore, the Japanese government is promoting digital transformation and the use of nursing care equipment, including nonwearable devices that monitor heart and respiratory rates. However, the feasibility of monitoring heart and respiratory rates with nonwearable devices and the consistency of the rates measured have not been reported.

Objective

In this study, we focused on a sheet-type nonwearable device (Safety Sheep Sensor) introduced in many nursing homes. We evaluated the feasibility of monitoring heart rate (HR) and respiratory rate (RR) continuously using nonwearable devices and the consistency of the HR and RR measured.

Methods

A sheet-type nonwearable device that measured HR and RR every minute through body vibrations was placed under the mattress of each participant. The participants in study 1 were healthy individuals aged 20-60 years (n=21), while those in study 2 were older adults living in multidwelling houses and required nursing care (n=20). The HR was measured using standard methods by the nurse and using the wearable device (Silmee Bar-type Lite sensor), and RR was measured by the nurse. The primary outcome was the mean difference in HR and RR between nonwearable devices and standard methods.

Results

The mean difference in HR was -0.32 (SD 3.12) in study 1 and 0.04 (SD: 3.98) in study 2; both the differences were within the predefined accepted discrepancies (<5 beats/min). The mean difference in RR was -0.98 (SD 3.01) in study 1 and -0.49 (SD 2.40) in study 2; both the differences were within the predefined accepted discrepancies (3 breaths/min).

Conclusions

HR and RR measurements obtained using the nonwearable devices and the standard method were similar. Continuous monitoring of vital signs using nonwearable devices can aid in the early detection of abnormal conditions in older people.

Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study

Background

The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care).

Objective

Provide an evidence-based approach to creating monitoring protocols based on a patient's risk of deterioration and link these to nursing workload and economic impact.

Design

Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders.

Setting and participants

Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations.

Results

Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a 'round', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation.

Conclusions

We explored several different scenarios with our stakeholders (clinicians and patients), based on how 'risk' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient's risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used.

Study registration

This study is registered as ISRCTN10863045.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.

Evaluation of measurement accuracy of wearable devices for heart rate variability

This paper proposed a method based on heart rate variability (HRV) for evaluating the accuracy of wearable devices in measuring heart rate. HRV refers to the variation in time intervals between successive heartbeats, widely used in many fields such as clinical and sports fields. Wearable devices such as Electrocardiogram (ECG) electrode patches have gained popularity due to their portability and ease of use. However, they can be prone to measurement interference caused by environmental noise, human respiration, etc. The proposed method consists of four main components: selection of "gold standard measurement devices", identification of HRV measurement metrics, construction of an HRV evaluation framework, and quantification of measurement errors. The method is validated through simulated experiments using ECG patches. The evaluation framework and quantification model established in this method have significant implications in establishment of industry standards and diagnosis of diseases in clinical practice.

Use of wearables for monitoring cardiometabolic health: A systematic review

INTRODUCTION

Cardiometabolic disorders (CMD) such as hyperglycemia, obesity, hypertension, and dyslipidemia are the leading causes of mortality and significant public health concerns worldwide. With the advances in wireless technology, wearables have become popular for health promotion, but its impact on cardiometabolic health is not well understood.

PURPOSE

A systematic literature review aimed to describe the features of wearables used for monitoring cardiometabolic health and identify the impact of using wearables on those cardiometabolic health indicators.

METHODS

A systematic search of PubMed, CINAHL, Academic Search Complete, and Science and Technology Collection databases was performed using keywords related to CMD risk indicators and wearables. The wearables were limited to sensors for blood pressure (BP), heart rate (HR), electrocardiogram (ECG), glucose, and cholesterol.

INCLUDED STUDIES

1) were published from 2016 to March 2021 in English, 2) focused on wearables external to the body, and 3) examined wearable use by individuals in daily life (not by health care providers). Protocol, technical, and non-empirical studies were excluded.

RESULTS

Out of 53 studies, the types of wearables used were smartwatches (45.3%), patches (34.0%), chest straps (22.6%), wristbands (13.2%), and others (9.4%). HR (58.5%), glucose (28.3%), and ECG (26.4%) were the predominant indicators. No studies tracked BP or cholesterol. Additional features of wearables included physical activity, respiration, sleep, diet, and symptom monitoring. Twenty-two studies primarily focused on the use of wearables and reported direct impacts on cardiometabolic indicators; seven studies used wearables as part of a multi-modality approach and presented outcomes affected by a primary intervention but measured through CMD-sensor wearables; and 24 validated the precision and usability of CMD-sensor wearables.

CONCLUSION

The impact of wearables on cardiometabolic indicators varied across the studies, indicating the need for further research. However, this body of literature highlights the potential of wearables to promote cardiometabolic health.

Contemporary wearable and handheld technology for the diagnosis of cardiac arrhythmias in Singapore

Twelve-lead electrocardiography (ECG) remains the gold standard for the diagnosis of cardiac arrhythmias. It provides a snapshot of the cardiac electrical activity while the leads are attached to the patient. As medical training is required to use the ECG machine, its use remains restricted to the clinic and hospital settings. These aspects limit the usefulness of 12-lead ECG in the diagnosis of cardiac arrhythmias, especially in individuals with short-lasting and infrequent paroxysmal symptoms. The introduction of ECG recording features in wearable and handheld smart devices has changed the paradigm of cardiac arrhythmia diagnosis, empowering patients to record their ECG as and when symptoms occur. This review describes contemporary ambulatory heart rhythm monitors commonly available in Singapore and their expanding role in the diagnosis of cardiac rhythm abnormalities.

Biophysiologic Monitoring for the Neurosurgical Patient

Biophysiologic monitoring exists as a method of collecting objective information about the neurosurgical patient throughout their treatment and recovery process. Such data is crucial for an improved understanding of the disease processes while providing the surgeon additional clarity as they decipher the next best steps in decision-making and medical recommendations. In the current review article, the authors discuss the commonly used wearable and placeable monitoring devices and the biophysiological data that can be collected to monitor, as well as, assess the neurosurgical patient. Special focus is placed on invasive and non-invasive neurologic monitoring devices, but important and commonly used monitors for the rest of the body are also discussed as they relate to the neurosurgical patient. Last, the authors review new, as well as, upcoming devices and measurements to better analyze the neurosurgical patient's bodily function and physiologic status as needed. The synthesis of methods contained herein may provide meaningful guidance for neurosurgeons in effectively monitoring and treating their patients while also helping to guide their future efforts in patient biophysiologic monitoring developments within neurosurgery.

Fascia Ecosystem: A Step Forward in Sleep Engineering and Research

Millions suffer from sleep disorders, and sleep clinics and research institutions seek improved sleep study methods. This paper proposes the Fascia Ecosystem for Sleep Engineering to improve traditional sleep studies. The Fascia Sleep Mask is more comfortable and accessible than overnight stays at a sleep center, and the Fascia Portal and Fascia Hub allow for home-based sleep studies with real-time intervention and data analysis capabilities.A study of 10 sleep experts found that the Fascia Portal is easy to access, navigate, and use, with 44.4% finding it very easy to access, 33.3% very easy to navigate, and 60% very easy to get used to. Most experts found the Fascia Portal reliable and easy to use.Moreover, the study analyzed physiological signals during various states of sleep and wakefulness in two subjects. The results demonstrated that the Fascia dataset captured higher amplitude spindles in N2 sleep (72.20 V and 109.87 V in frontal and parietal regions, respectively) and higher peak-to-peak amplitude slow waves in N3 sleep (93.51 V) compared to benchmark datasets. Fascia produced stronger and more consistent EOG signals during REM sleep, indicating its potential to improve sleep disorder diagnosis and treatment by providing a deeper understanding of sleep patterns.

Data Quality Degradation on Prediction Models Generated From Continuous Activity and Heart Rate Monitoring: Exploratory Analysis Using Simulation

BACKGROUND

Limited data accuracy is often cited as a reason for caution in the integration of physiological data obtained from consumer-oriented wearable devices in care management pathways. The effect of decreasing accuracy on predictive models generated from these data has not been previously investigated.

OBJECTIVE

The aim of this study is to simulate the effect of data degradation on the reliability of prediction models generated from those data and thus determine the extent to which lower device accuracy might or might not limit their use in clinical settings.

METHODS

Using the Multilevel Monitoring of Activity and Sleep in Healthy People data set, which includes continuous free-living step count and heart rate data from 21 healthy volunteers, we trained a random forest model to predict cardiac competence. Model performance in 75 perturbed data sets with increasing missingness, noisiness, bias, and a combination of all 3 perturbations was compared to model performance for the unperturbed data set.

RESULTS

The unperturbed data set achieved a mean root mean square error (RMSE) of 0.079 (SD 0.001) in predicting cardiac competence index. For all types of perturbations, RMSE remained stable up to 20%-30% perturbation. Above this level, RMSE started increasing and reached the point at which the model was no longer predictive at 80% for noise, 50% for missingness, and 35% for the combination of all perturbations. Introducing systematic bias in the underlying data had no effect on RMSE.

CONCLUSIONS

In this proof-of-concept study, the performance of predictive models for cardiac competence generated from continuously acquired physiological data was relatively stable with declining quality of the source data. As such, lower accuracy of consumer-oriented wearable devices might not be an absolute contraindication for their use in clinical prediction models.

On the development of low power wearable devices for assessment of physiological vital parameters: a systematic review

Aim

Smart wearable devices for continuous monitoring of health conditions have bbecome very important in the healthcare sector to acquire and assess the different physiological parameters. This paper reviews the nature of physiological signals, desired vital parameters, role of smart wearable devices, choices of wearable devices and design considerations for wearable devices for early detection of health conditions.

Subject and methods

This article provides designers with information to identify and develop smart wearable devices based on the data extracted from a literature survey on previously published research articles in the field of wearable devices for monitoring vital parameters.

Results

The key information available in this article indicates that quality signal acquisition, processing and longtime monitoring of vital parameters requires smart wearable devices. The development of smart wearable devices with the listed design criteria supports the developer to design a low power wearable device for continuous monitoring of patient health conditions.

Conclusion

The wide range of information gathered from the review indicates that there is a huge demand for smart wearable devices for monitoring health conditions at home. It further supports tracking heath status in the long term via monitoring the vital parameters with the support of wireless communication principles.

The Accuracy of Wrist-Worn Photoplethysmogram-Measured Heart and Respiratory Rates in Abdominal Surgery Patients: Observational Prospective Clinical Validation Study

BACKGROUND

Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established.

OBJECTIVE

This study aimed to assess the accuracy of heart rate (HR) and respiratory rate (RR) measures obtained via a wearable photoplethysmography (PPG) wristband in a cohort of postoperative patients.

METHODS

The accuracy of the wrist-worn PPG sensor was assessed in 62 post-abdominal surgery patients (mean age 55, SD 15 years; median BMI 34, IQR 25-40 kg/m²). The wearable obtained HR and RR measurements were compared to those of the reference monitor in the postanesthesia or intensive care unit. Bland-Altman and Clarke error grid analyses were performed to determine agreement and clinical accuracy.

RESULTS

Data were collected for a median of 1.2 hours per patient. With a coverage of 94% for HR and 34% for RR, the device was able to provide accurate measurements for the large majority of the measurements as 98% and 93% of the measurements were within 5 bpm or 3 rpm of the reference signal. Additionally, 100% of the HR and 98% of the RR measurements were clinically acceptable on Clarke error grid analysis.

CONCLUSIONS

The wrist-worn PPG device is able to provide measurements of HR and RR that can be seen as sufficiently accurate for clinical applications. Considering the coverage, the device was able to continuously monitor HR and report RR when measurements of sufficient quality were obtained.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03923127; https://www.clinicaltrials.gov/ct2/show/NCT03923127.

Agreement between standard and continuous wireless vital sign measurements after major abdominal surgery: a clinical comparison study

Objective. Continuous wireless monitoring outside the post-anesthesia or intensive care units may enable early detection of patient deterioration, but good accuracy of measurements is required. We aimed to assess the agreement between vital signs recorded by standard and novel wireless devices in postoperative patients.Approach. In 20 patients admitted to the post-anesthesia care unit, we compared heart rate (HR), respiratory rate (RR), peripheral oxygen saturation (SpO₂), and systolic and diastolic blood pressure (SBP and DBP) as paired data. The primary outcome measure was the agreement between standard wired and wireless monitoring, assessed by mean bias and 95% limits of agreement (LoA). LoA was considered acceptable for HR and PR, if within ±5 beats min^-1(bpm), while RR, SpO2, and BP were deemed acceptable if within ±3 breaths min^-1(brpm), ±3%-points, and ±10 mmHg, respectively.Main results.The mean bias between standard versus wireless monitoring was -0.85 bpm (LoA -6.2 to 4.5 bpm) for HR, -1.3 mmHg (LoA -19 to 17 mmHg) for standard versus wireless SBP, 2.9 mmHg (LoA -17 to 22) for standard versus wireless DBP, and 1.7% (LoA -1.4 mmHg to 4.8 mmHg) for SpO₂, comparing standard versus wireless monitoring. The mean bias of arterial blood gas analysis versus wireless SpO₂measurements was 0.02% (LoA -0.02% to 0.06%), while the mean bias of direct observation of RR compared to wireless measurements was 0.0 brpm (LoA -2.6 brpm to 2.6 brpm). 80% of all values compared were within predefined clinical limits.Significance.The agreement between wired and wireless HR, RR, and PR recordings in postoperative patients was acceptable, whereas the agreement for SpO₂recordings (standard versus wireless) was borderline. Standard wired and wireless BP measurements may be used interchangeably in the clinical setting.

Evaluation of physical health status beyond daily step count using a wearable activity sensor

Physical health status defines an individual's ability to perform normal activities of daily living and is usually assessed in clinical settings by questionnaires and/or by validated tests, e.g. timed walk tests. These measurements have relatively low information content and are usually limited in frequency. Wearable sensors, such as activity monitors, enable remote measurement of parameters associated with physical activity but have not been widely explored beyond measurement of daily step count. Here we report on results from a cohort of 22 individuals with Pulmonary Arterial Hypertension (PAH) who were provided with a Fitbit activity monitor (Fitbit Charge HR^®) between two clinic visits (18.4 ± 12.2 weeks). At each clinical visit, a maximum of 26 measurements were recorded (19 categorical and 7 continuous). From analysis of the minute-to-minute step rate and heart rate we derive several metrics associated with physical activity and cardiovascular function. These metrics are used to identify subgroups within the cohort and to compare to clinical parameters. Several Fitbit metrics are strongly correlated to continuous clinical parameters. Using a thresholding approach, we show that many Fitbit metrics result in statistically significant differences in clinical parameters between subgroups, including those associated with physical status, cardiovascular function, pulmonary function, as well as biomarkers from blood tests. These results highlight the fact that daily step count is only one of many metrics that can be derived from activity monitors.

Agreement between two photoplethysmography-based wearable devices for monitoring heart rate during different physical activity situations: a new analysis methodology

Wearables are being increasingly used to monitor heart rate (HR). However, their usefulness for analyzing continuous HR in research or at clinical level is questionable. The aim of this study is to analyze the level of agreement between different wearables in the measurement of HR based on photoplethysmography, according to different body positions and physical activity levels, and compared to a gold-standard ECG. The proposed method measures agreement among several time scales since different wearables obtain HR at different sampling rates. Eighteen university students (10 men, 8 women; 22 ± 2.45 years old) participated in a laboratory study. Participants simultaneously wore an Apple Watch and a Polar Vantage watch. ECG was measured using a BIOPAC system. HR was recorded continuously and simultaneously by the three devices, for consecutive 5-min periods in 4 different situations: lying supine, sitting, standing and walking at 4 km/h on a treadmill. HR estimations were obtained with the maximum precision offered by the software of each device and compared by averaging in several time scales, since the wearables obtained HR at different sampling rates, although results are more detailed for 5 s and 30 s epochs. Bland–Altman (B-A) plots show that there is no noticeable difference between data from the ECG and any of the smartwatches while participants were lying down. In this position, the bias is low when averaging in both 5 s and 30 s. Differently, B-A plots show that there are differences when the situation involves some level of physical activity, especially for shorter epochs. That is, the discrepancy between devices and the ECG was greater when walking on the treadmill and during short time scales. The device showing the biggest discrepancy was the Polar Watch, and the one with the best results was the Apple Watch. We conclude that photoplethysmography-based wearable devices are suitable for monitoring HR averages at regular intervals, especially at rest, but their feasibility is debatable for a continuous analysis of HR for research or clinical purposes, especially when involving some level of physical activity. An important contribution of this work is a new methodology to synchronize and measure the agreement against a gold standard of two or more devices measuring HR at different and not necessarily even paces.

The Role of Contemporary Wearable and Handheld Devices in the Diagnosis and Management of Cardiac Arrhythmias

Cardiac arrhythmias are associated with significant morbidity, mortality and economic burden on the health care system. Detection and surveillance of cardiac arrhythmias using medical grade non-invasive methods (electrocardiogram, Holter monitoring) is the accepted standard of care. Whilst their accuracy is excellent, significant limitations remain in terms of accessibility, ease of use, cost, and a suboptimal diagnostic yield (up to ∼50%) which is critically dependent on the duration of monitoring. Contemporary wearable and handheld devices that utilise photoplethysmography and the electrocardiogram present a novel opportunity for remote screening and diagnosis of arrhythmias. They have significant advantages in terms of accessibility and availability with the potential of enhancing the diagnostic yield of episodic arrhythmias. However, there is limited data on the accuracy and diagnostic utility of these devices and their role in therapeutic decision making in clinical practice remains unclear. Evidence is mounting that they may be useful in screening for atrial fibrillation, and anecdotally, for the diagnosis of other brady and tachyarrhythmias. Recently, there has been an explosion of patient uptake of such devices for self-monitoring of arrhythmias. Frequently, the clinician is presented such information for review and comment, which may influence clinical decisions about treatment. Further studies are needed before incorporation of such technologies in routine clinical practice, given the lack of systematic data on their accuracy and utility. Moreover, challenges with regulation of quality standards and privacy remain. This state-of-the-art review summarises the role of novel ambulatory, commercially available, heart rhythm monitors in the diagnosis and management of cardiac arrhythmias and their expanding role in the diagnostic and therapeutic paradigm in cardiology.

RP3MES: A Key to Minimize Infection Spreading

Healthcare facilities, especially in highly populated countries like India where patient to doctor ratio is very high, are under a huge burden. Thus, Remote Patient Physiological Parameter Monitoring using Embedded System (RP3MES) becomes essential to monitor a large number of people admitted in hospitals and also patients afflicted with infectious diseases. The design for RP3MES addresses the key issues of portability, cost-effectiveness, low power consumption, user-friendliness, high accuracy and remote communication to facilitate vital parameter(s), like heart rate and body temperature, measurements and emergency notification, keeping in mind, the health of the caregiver(s). ARM Cortex M3 embedded processor and low-cost sensors are used to achieve the cost-effectiveness and low power consumption. Alarming unit intimidates a remote caregiver regarding their patient’s health condition. The accuracy of the system measured data is 99.4% compared with the gold standard, which has been verified using Lin’s Concordance Correlation Coefficient and Bland–Altman analysis. A comparison of our system with other commercially available ones is also presented here. The proposed system has wireless connectivity which minimizes infection transmission among family members and caregivers of the patients. It may also reduce the burden on healthcare staffs in hospitals.

Stretchable and Self-Adhesive PEDOT:PSS Blend with High Sweat Tolerance as Conformal Biopotential Dry Electrodes

Dry epidermal electrodes that can always form conformal contact with skin can be used for continuous long-term biopotential monitoring, which can provide vital information for disease diagnosis and rehabilitation. But, this application has been limited by the poor contact of dry electrodes on wet skin. Herein, we report a biocompatible fully organic dry electrode that can form conformal contact with both dry and wet skin even during physical movement. The dry electrodes are prepared by drop casting an aqueous solution consisting of poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS), poly(vinyl alcohol) (PVA), tannic acid (TA), and ethylene glycol (EG). The electrodes can exhibit a conductivity of 122 S cm^-1 and a mechanical stretchability of 54%. Moreover, they are self-adhesive to not only dry skin but also wet skin. As a result, they can exhibit a lower contact impedance to skin than commercial Ag/AgCl gel electrodes on both dry and sweat skins. They can be used as dry epidermal electrodes to accurately detect biopotential signals including electrocardiogram (ECG) and electromyogram (EMG) on both dry and wet skins for the users at rest or during physical movement. This is the first time to demonstrate dry epidermal electrodes self-adhesive to wet skin for accurate biopotential detection.

Novel wearable and contactless heart rate, respiratory rate, and oxygen saturation monitoring devices: a systematic review and meta-analysis

We performed a systematic review and meta-analysis to identify, classify and evaluate the body of evidence on novel wearable and contactless devices that measure heart rate, respiratory rate and oxygen saturations in the clinical setting. We included any studies of hospital inpatients, including sleep study clinics. Eighty-four studies were included in the final review. There were 56 studies of wearable devices and 29 of contactless devices. One study assessed both types of device. A high risk of patient selection and rater bias was present in proportionally more studies assessing contactless devices compared with studies assessing wearable devices (p = 0.023 and p < 0.0001, respectively). There was high but equivalent likelihood of blinding bias between the two types of studies (p = 0.076). Wearable device studies were commercially available devices validated in acute clinical settings by clinical staff and had more real-time data analysis (p = 0.04). Contactless devices were more experimental, and data were analysed post-hoc. Pooled estimates of mean (95%CI) heart rate and respiratory rate bias in wearable devices were 1.25 (-0.31-2.82) beats.min^-1 (pooled 95% limits of agreement -9.36-10.08) and 0.68 (0.05-1.32) breaths.min^-1 (pooled 95% limits of agreement -5.65-6.85). The pooled estimate for mean (95%CI) heart rate and respiratory rate bias in contactless devices was 2.18 (3.31-7.66) beats.min^-1 (pooled limits of agreement -6.71-10.88) and 0.30 (-0.26-0.87) breaths.min^-1 (pooled 95% limits of agreement -3.94-4.29). Only two studies of wearable devices measured S_p O₂ ; these reported mean measurement biases of 3.54% (limits of agreement -5.65-11.45%) and 2.9% (-7.4-1.7%). Heterogeneity was observed across studies, but absent when devices were grouped by measurement modality and reference standard. We conclude that, while studies of wearable devices were of slightly better quality than contactless devices, in general all studies of novel devices were of low quality, with small (< 100) patient datasets, typically not blinded and often using inappropriate statistical techniques. Both types of devices were statistically equivalent in accuracy and precision, but wearable devices demonstrated less measurement bias and more precision at extreme vital signs. The statistical variability in precision and accuracy between studies is partially explained by differences in reference standards.

Monitoring and Managing Lifestyle Behaviors Using Wearable Activity Trackers: Mixed Methods Study of Views From the Huntington Disease Community

Background

There are early indications that lifestyle behaviors, specifically physical activity and sleep, may be associated with the onset and progression of Huntington disease (HD). Wearable activity trackers offer an exciting opportunity to collect long-term activity data to further investigate the role of lifestyle, physical activity, and sleep in disease modification. Given how wearable devices rely on user acceptance and long-term adoption, it is important to understand users’ perspectives on how acceptable any device might be and how users might engage over the longer term.

Objective

This study aimed to explore the perceptions, motivators, and potential barriers relating to the adoption of wearable activity trackers by people with HD for monitoring and managing their lifestyle and sleep. This information intended to guide the selection of wearable activity trackers for use in a longitudinal observational clinical study.

Methods

We conducted a mixed methods study; this allowed us to draw on the potential strengths of both quantitative and qualitative methods. Opportunistic participant recruitment occurred at 4 Huntington’s Disease Association meetings, including 1 international meeting and 3 United Kingdom–based regional meetings. Individuals with HD, their family members, and carers were invited to complete a user acceptance questionnaire and participate in a focus group discussion. The questionnaire consisted of 35 items across 8 domains using a 0 to 4 Likert scale, along with some additional demographic questions. Average questionnaire responses were recorded as positive (score>2.5), negative (score<1.5), or neutral (score between 1.5 and 2.5) opinions for each domain. Differences owing to demographics were explored using the Kruskal-Wallis and Wilcoxon rank sum tests. Focus group discussions (conducted in English) were driven by a topic guide, a vignette scenario, and an item ranking exercise. The discussions were audio recorded and then analyzed using thematic analysis.

Results

A total of 105 completed questionnaires were analyzed (47 people with HD and 58 family members or carers). All sections of the questionnaire produced median scores >2.5, indicating a tendency toward positive opinions on wearable activity trackers, such as the devices being advantageous, easy and enjoyable to use, and compatible with lifestyle and users being able to understand the information from trackers and willing to wear them. People with HD reported a more positive attitude toward wearable activity trackers than their family members or caregivers (P=.02). A total of 15 participants participated in 3 focus groups. Device compatibility and accuracy, data security, impact on relationships, and the ability to monitor and self-manage lifestyle behaviors have emerged as important considerations in device use and user preferences.

Conclusions

Although wearable activity trackers were broadly recognized as acceptable for both monitoring and management, various aspects of device design and functionality must be considered to promote acceptance in this clinical cohort.

Wearable devices for continuous monitoring of biosignals: Challenges and opportunities

The ability for wearable devices to collect high-fidelity biosignals continuously over weeks and months at a time has become an increasingly sought-after characteristic to provide advanced diagnostic and therapeutic capabilities. Wearable devices for this purpose face a multitude of challenges such as formfactors with long-term user acceptance and power supplies that enable continuous operation without requiring extensive user interaction. This review summarizes design considerations associated with these attributes and summarizes recent advances toward continuous operation with high-fidelity biosignal recording abilities. The review also provides insight into systematic barriers for these device archetypes and outlines most promising technological approaches to expand capabilities. We conclude with a summary of current developments of hardware and approaches for embedded artificial intelligence in this wearable device class, which is pivotal for next generation autonomous diagnostic, therapeutic, and assistive health tools.

Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit

Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent advances in non-invasive sensing technology, high throughput computing, and deep learning techniques are expected to transform the existing patient monitoring paradigm by enabling and streamlining granular and continuous monitoring of these crucial critical care measures. In this review, we highlight current approaches to pervasive sensing in critical care and identify limitations, future challenges, and opportunities in this emerging field.

Accuracy of wrist-worn wearable devices for determining exercise intensity

Objective

As an indicator of exercise intensity, heart rate can be measured in a timely manner using wrist-worn devices. No study has attempted to estimate a target exercise intensity using wearable devices. The objective of the study was to evaluate the validity of prescribing exercise intensity using wrist-worn devices.

Methods

Thirty healthy subjects completed a maximal cardiopulmonary exercise test. Their heart rates were recorded using an electrocardiogram and two devices—Apple Watch Series 6 and Garmin Forerunner 945. Exercise intensity with the target heart rate was defined as resting heart rate + (maximal heart rate − resting heart rate) * n% ( n%: 40–60% for moderate-intensity exercise and 60–89% for vigorous-intensity exercise). Heart rate was analyzed at the lower and upper limits of each exercise intensity (HR40, HR60, and HR89). The mean absolute percentage error and concordance correlation coefficient were calculated, and Bland–Altman plots and scatterplots were constructed.

Results

Both devices showed a low mean absolute error (1.16–1.48 bpm for Apple and 1.35–2.25 for Garmin) and mean absolute percentage error (<1% for Apple and 1.16–1.39% for Garmin) in all intensities. A substantial correlation with electrocardiogram-measured heart rate was observed for moderate to vigorous intensity with concordance correlation coefficient > 0.95 for both devices, except that Garmin showed moderate correlation at the upper limit of vigorous activity with concordance correlation coefficient = 0.936. Moreover, Bland–Altman plots and scatterplots demonstrated a strong correlation without systematic error when the values obtained via the two devices were compared with electrocardiogram measurements.

Conclusions

Our findings indicate the high validity of exercise prescriptions based on the heart rate measured by the two devices. Additional research should explore other populations to confirm these findings.

Detection of Clenbuterol-Induced Changes in Heart Rate Using At-Home Recorded Smartwatch Data: Randomized Controlled Trial

BACKGROUND

Although electrocardiography is the gold standard for heart rate (HR) recording in clinical trials, the increasing availability of smartwatch-based HR monitors opens up possibilities for drug development studies. Smartwatches allow for inexpensive, unobtrusive, and continuous HR estimation for potential detection of treatment effects outside the clinic, during daily life.

OBJECTIVE

The aim of this study is to evaluate the repeatability and sensitivity of smartwatch-based HR estimates collected during a randomized clinical trial.

METHODS

The data were collected as part of a multiple-dose, investigator-blinded, randomized, placebo-controlled, parallel-group study of 12 patients with Parkinson disease. After a 6-day baseline period, 4 and 8 patients were treated for 7 days with an ascending dose of placebo and clenbuterol, respectively. Throughout the study, the smartwatch provided HR and sleep state estimates. The HR estimates were quantified as the 2.5th, 50th, and 97.5th percentiles within awake and asleep segments. Linear mixed models were used to calculate the following: (1) the intraclass correlation coefficient (ICC) of estimated sleep durations, (2) the ICC and minimum detectable effect (MDE) of the HR estimates, and (3) the effect sizes of the HR estimates.

RESULTS

Sleep duration was moderately repeatable (ICC=0.64) and was not significantly affected by study day (P=.83), clenbuterol (P=.43), and study day by clenbuterol (P=.73). Clenbuterol-induced changes were detected in the asleep HR as of the first night (+3.79 beats per minute [bpm], P=.04) and in the awake HR as of the third day (+8.79 bpm, P=.001). The median HR while asleep had the highest repeatability (ICC=0.70). The MDE (N=12) was found to be smaller when patients were asleep (6.8 bpm to 11.7 bpm) than while awake (10.7 bpm to 22.1 bpm). Overall, the effect sizes for clenbuterol-induced changes were higher while asleep (0.49 to 2.75) than while awake (0.08 to 1.94).

CONCLUSIONS

We demonstrated the feasibility of using smartwatch-based HR estimates to detect clenbuterol-induced changes during clinical trials. The asleep HR estimates were most repeatable and sensitive to treatment effects. We conclude that smartwatch-based HR estimates obtained during daily living in a clinical trial can be used to detect and track treatment effects.

TRIAL REGISTRATION

Netherlands Trials Register NL8002; https://www.trialregister.nl/trial/8002.

Creating a Digital Toolkit to Reduce Fatigue and Promote Quality of Life in Multiple Sclerosis: Participatory Design and Usability Study

Background

Fatigue is one of the most common and debilitating symptoms of multiple sclerosis (MS), experienced by more than 80% of people with MS. FACETS (Fatigue: Applying Cognitive Behavioral and Energy Effectiveness Techniques to Lifestyle) is an evidence-based, face-to-face, 6-session group fatigue management program for people with MS. Homework tasks are an integral part of FACETS and are currently undertaken in a paper-based form. Feedback from a consultation undertaken with FACETS attendees and health care professionals with experience in delivering the FACETS program suggested that being able to complete the homework tasks digitally would be desirable, potentially enhancing engagement and adherence and enabling on-the-go access to fit into busy lifestyles. Relative to other long-term conditions, there are few apps specifically for MS and, of those available, many have been developed with little or no input from people with MS.

Objective

The purpose of this mixed methods study was to create a digital toolkit comprising the homework tasks (eg, activity diary, goal planner, thought diary) of the FACETS program for people with MS, considering end users’ unique requirements throughout the design, build, prototyping, and testing stages.

Methods

Phase 1 involved the elicitation of detailed user requirements for the toolkit via 2 focus groups with previous attendees of FACETS (n=3 and n=6) and wireframing. Phase 2 involved supervised usability testing with people with MS (n=11) with iterative prototyping. The usability sessions involved going through test scenarios using the FACETS toolkit on an Android test phone with video capture and concurrent think-aloud followed by completion of the System Usability Scale (SUS) and a semistructured interview collecting feedback about design, content, and functionality.

Results

The mean SUS score for the digital toolkit was 74.3 (SD 16.8, 95% CI 63.2-85.6; range 37.5-95), which equates to an adjective rating of good and a B grade (70th-79th percentile range) on the Sauro-Lewis curved grading scale. A number of usability and design issues (such as simplifying overall screen flow to better meet users’ needs) and suggestions for improvements (such as using location-based services and displaying personalized information and progress via a central dashboard) were addressed and implemented during the usability testing cycle.

Conclusions

This work highlights the importance of the participation of people with MS across the entire development cycle, working to a human-centered design methodology to enable a considered and MS-centered solution to be developed. Continued horizon scanning for emergent technological enhancements will enable us to identify opportunities for further improvements to the FACETS toolkit prior to launch. The toolkit supports self-monitoring and management of fatigue and has potential applicability to other long-term conditions where fatigue is a significant issue.

Using smartwatches to observe changes in activity during recovery from critical illness following COVID-19: a 1 year multi-centre observational study. (Preprint)

Background

As a sequela of the COVID-19 pandemic, a large cohort of critical illness survivors have had to recover in the context of ongoing societal restrictions.

Objective

We aimed to use smartwatches (Fitbit Charge 3; Fitbit LLC) to assess changes in the step counts and heart rates of critical care survivors following hospital admission with COVID-19, use these devices within a remote multidisciplinary team (MDT) setting to support patient recovery, and report on our experiences with this.

Methods

We conducted a prospective, multicenter observational trial in 8 UK critical care units. A total of 50 participants with moderate or severe lung injury resulting from confirmed COVID-19 were recruited at discharge from critical care and given a smartwatch (Fitbit Charge 3) between April and June 2020. The data collected included step counts and daily resting heart rates. A subgroup of the overall cohort at one site—the MDT site (n=19)—had their smartwatch data used to inform a regular MDT meeting. A patient feedback questionnaire and direct feedback from the MDT were used to report our experience. Participants who did not upload smartwatch data were excluded from analysis.

Results

Of the 50 participants recruited, 35 (70%) used and uploaded data from their smartwatch during the 1-year period. At the MDT site, 74% (14/19) of smartwatch users uploaded smartwatch data, whereas 68% (21/31) of smartwatch users at the control sites uploaded smartwatch data. For the overall cohort, we recorded an increase in mean step count from 4359 (SD 3488) steps per day in the first month following discharge to 7914 (SD 4146) steps per day at 1 year (P=.003). The mean resting heart rate decreased from 79 (SD 7) beats per minute in the first month to 69 (SD 4) beats per minute at 1 year following discharge (P<.001). The MDT subgroup’s mean step count increased more than that of the control group (176% increase vs 42% increase, respectively; +5474 steps vs +2181 steps, respectively; P=.04) over 1 year. Further, 71% (10/14) of smartwatch users at the MDT site and 48% (10/21) of those at the control sites strongly agreed that their Fitbit motivated them to recover, and 86% (12/14) and 48% (10/21), respectively, strongly agreed that they aimed to increase their activity levels over time.

Conclusions

This is the first study to use smartwatch data to report on the 1-year recovery of patients who survived a COVID-19 critical illness. This is also the first study to report on smartwatch use within a post–critical care MDT. Future work could explore the role of smartwatches as part of a randomized controlled trial to assess clinical and economic effectiveness.

International Registered Report Identifier (IRRID)

RR2-10.12968/ijtr.2020.0102

Validation of Heart Rate Extracted From Wrist-Based Photoplethysmography in the Perioperative Setting: Prospective Observational Study

Background

Measurement of heart rate (HR) through an unobtrusive, wrist-worn optical HR monitor (OHRM) could enable earlier recognition of patient deterioration in low acuity settings and enable timely intervention.

Objective

The goal of this study was to assess the agreement between the HR extracted from the OHRM and the gold standard 5-lead electrocardiogram (ECG) connected to a patient monitor during surgery and in the recovery period.

Methods

In patients undergoing surgery requiring anesthesia, the HR reported by the patient monitor’s ECG module was recorded and stored simultaneously with the photopletysmography (PPG) from the OHRM attached to the patient’s wrist. The agreement between the HR reported by the patient’s monitor and the HR extracted from the OHRM’s PPG signal was assessed using Bland-Altman analysis during the surgical and recovery phase.

Results

A total of 271.8 hours of data in 99 patients was recorded simultaneously by the OHRM and patient monitor. The median coverage was 86% (IQR 65%-95%) and did not differ significantly between surgery and recovery (Wilcoxon paired difference test P=.17). Agreement analysis showed the limits of agreement (LoA) of the difference between the OHRM and the ECG HR were within the range of 5 beats per minute (bpm). The mean bias was –0.14 bpm (LoA between –3.08 bpm and 2.79 bpm) and –0.19% (LoA between –5 bpm to 5 bpm) for the PPG- measured HR compared to the ECG-measured HR during surgery; during recovery, it was –0.11 bpm (LoA between –2.79 bpm and 2.59 bpm) and –0.15% (LoA between –3.92% and 3.64%).

Conclusions

This study shows that an OHRM equipped with a PPG sensor can measure HR within the ECG reference standard of –5 bpm to 5 bpm or –10% to 10% in the perioperative setting when the PPG signal is of sufficient quality. This implies that an OHRM can be considered clinically acceptable for HR monitoring in low acuity hospitalized patients.

Evaluating the Validity and Utility of Wearable Technology for Continuously Monitoring Patients in a Hospital Setting: Systematic Review

BACKGROUND

The term posthospital syndrome has been used to describe the condition in which older patients are transiently frail after hospitalization and have a high chance of readmission. Since low activity and poor sleep during hospital stay may contribute to posthospital syndrome, the continuous monitoring of such parameters by using affordable wearables may help to reduce the prevalence of this syndrome. Although there have been systematic reviews of wearables for physical activity monitoring in hospital settings, there are limited data on the use of wearables for measuring other health variables in hospitalized patients.

OBJECTIVE

This systematic review aimed to evaluate the validity and utility of wearable devices for monitoring hospitalized patients.

METHODS

This review involved a comprehensive search of 7 databases and included articles that met the following criteria: inpatients must be aged >18 years, the wearable devices studied in the articles must be used to continuously monitor patients, and wearables should monitor biomarkers other than solely physical activity (ie, heart rate, respiratory rate, blood pressure, etc). Only English-language studies were included. From each study, we extracted basic demographic information along with the characteristics of the intervention. We assessed the risk of bias for studies that validated their wearable readings by using a modification of the Consensus-Based Standards for the Selection of Health Status Measurement Instruments.

RESULTS

Of the 2012 articles that were screened, 14 studies met the selection criteria. All included articles were observational in design. In total, 9 different commercial wearables for various body locations were examined in this review. The devices collectively measured 7 different health parameters across all studies (heart rate, sleep duration, respiratory rate, oxygen saturation, skin temperature, blood pressure, and fall risk). Only 6 studies validated their results against a reference device or standard. There was a considerable risk of bias in these studies due to the low number of patients in most of the studies (4/6, 67%). Many studies that validated their results found that certain variables were inaccurate and had wide limits of agreement. Heart rate and sleep were the parameters with the most evidence for being valid for in-hospital monitoring. Overall, the mean patient completion rate across all 14 studies was >90%.

CONCLUSIONS

The included studies suggested that wearable devices show promise for monitoring the heart rate and sleep of patients in hospitals. Many devices were not validated in inpatient settings, and the readings from most of the devices that were validated in such settings had wide limits of agreement when compared to gold standards. Even some medical-grade devices were found to perform poorly in inpatient settings. Further research is needed to determine the accuracy of hospitalized patients' digital biomarker readings and eventually determine whether these wearable devices improve health outcomes.

Demonstrating the Applicability of Smartwatches in PM2.5 Health Impact Assessment

Smartwatches are being increasingly used in research to monitor heart rate (HR). However, it is debatable whether the data from smartwatches are of high enough quality to be applied in assessing the health impacts of air pollutants. The objective of this study was to assess whether smartwatches are useful complements to certified medical devices for assessing PM_2.5 health impacts. Smartwatches and medical devices were used to measure HR for 7 and 2 days consecutively, respectively, for 49 subjects in 2020 in Taiwan. Their associations with PM_2.5 from low-cost sensing devices were assessed. Good correlations in HR were found between smartwatches and certified medical devices (r_s > 0.6, except for exercise, commuting, and worshipping). The health damage coefficients obtained from smartwatches (0.282% increase per 10 μg/m³ increase in PM_2.5) showed the same direction, with a difference of only 8.74% in magnitude compared to those obtained from certified medical devices. Additionally, with large sample sizes, the health impacts during high-intensity activities were assessed. Our work demonstrates that smartwatches are useful complements to certified medical devices in PM_2.5 health assessment, which can be replicated in developing countries.

Reliability of heart rate and respiration rate measurements with a wireless accelerometer in postbariatric recovery

Recognition of early signs of deterioration in postoperative course could be improved by continuous monitoring of vital parameters. Wearable sensors could enable this by wireless transmission of vital signs. A novel accelerometer-based device, called Healthdot, has been designed to be worn on the skin to measure the two key vital parameters respiration rate (RespR) and heart rate (HeartR). The goal of this study is to assess the reliability of heart rate and respiration rate measured by the Healthdot in comparison to the gold standard, the bedside patient monitor, during the postoperative period in bariatric patients. Data were collected in a consecutive group of 30 patients who agreed to wear the device after their primary bariatric procedure. Directly after surgery, a Healthdot was attached on the patients’ left lower rib. Vital signs measured by the accelerometer based Healthdot were compared to vital signs collected with the gold standard patient monitor for the period that the patient stayed at the post-anesthesia care unit. Over all patients, a total of 22 hours of vital signs obtained by the Healthdot were recorded simultaneously with the bedside patient monitor data. 87.5% of the data met the pre-defined bias of 5 beats per minute for HeartR and 92.3% of the data met the pre-defined bias of 5 respirations per minute for RespR. The Healthdot can be used to accurately derive heart rate and respiration rate in postbariatric patients. Wireless continuous monitoring of key vital signs has the potential to contribute to earlier recognition of complications in postoperative patients. Future studies should focus on the ability to detect patient deterioration in low-care environments and at home after discharge from the hospital.

Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network

Assessing vital signs such as heart rate (HR) by wearable devices in a lifestyle-related environment provides widespread opportunities for public health related research and applications. Commonly, consumer wearable devices assessing HR are based on photoplethysmography (PPG), where HR is determined by absorption and reflection of emitted light by the blood. However, methodological differences and shortcomings in the validation process hamper the comparability of the validity of various wearable devices assessing HR. Towards Intelligent Health and Well-Being: Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables assessing HR by PPG. The recommendations were developed through the following multi-stage process: (1) a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, (2) an unstructured review of the wider literature pertaining to factors that may introduce bias during the validation of these devices and (3) evidence-informed expert opinions of the INTERLIVE Network. A total of 44 articles were deemed eligible and retrieved through our systematic literature review. Based on these studies, a wider literature review and our evidence-informed expert opinions, we propose a validation framework with standardised recommendations using six domains: considerations for the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis. As such, this paper presents recommendations to standardise the validity testing and reporting of PPG-based HR wearables used by consumers. Moreover, checklists are provided to guide the validation protocol development and reporting. This will ensure that manufacturers, consumers, healthcare providers and researchers use wearables safely and to its full potential.

Noninvasive Continuous Monitoring of Vital Signs With Wearables: Fit for Medical Use?

BACKGROUND

Wearables (= wearable computer) enable continuous and noninvasive monitoring of a range of vital signs. Mobile and cost-effective devices, combined with powerful data analysis tools, open new dimensions in assessing body functions ("digital biomarkers").

METHODS

To answer the question whether wearables are ready for use in the medical context, a PubMed literature search and analysis for their clinical-scientific use using publications from the years 2008 to 2018 was performed.

RESULTS

A total of 79 out of 314 search hits were publications on clinical trials with wearables, of which 16 were randomized controlled trials. Motion sensors were most frequently used to measure defined movements, movement disorders, or general physical activity. Approximately 20% of the studies used sensors to detect cardiovascular parameters. As for the sensor location, the wrist was chosen in most studies (22.8%).

CONCLUSION

Wearables can be used in a precisely defined medical context, when taking into account complex influencing factors.

Preliminary study a non-invasion method on early cardiac energy defect based on Hilbert Huang Transform

Statistics released by the World Health Organization in 2018 show that the total death of people is 56.9 million worldwide in 2016. The first one is cardiovascular diseases, including ischemic heart disease and stroke, which accounted for 17.65 million people (31%) [1]. Treadmill Exercise Test is suitable for measuring the changes in Electrocardiography (ECG) initial, middle, and after exercise [2]. They are using it to distinguish chest pain without apparent causes, judging the severity of coronary artery disease, and screening personnel with coronary artery disease risk factors. The most important contribution of this study is to use the Hilbert Huang Transform (HHT) [3], a non-invasive method, to decompose the original ECG signals of inspectors through the Empirical Mode Decomposition (EMD) [4-7], not the commonly used of 12-lead ECG detection method. There is a total of 49 participants in 24 pseudo-positive persons; 4 were re-judged into positive, reducing 83.3% pseudo-positive persons who need to do the follow-up testing, significantly reducing the consumption of medical and time.

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management

Ambulatory monitoring is increasingly important for cardiovascular care but is often limited by the unpredictability of cardiovascular events, the intermittent nature of ambulatory monitors and the variable clinical significance of recorded data in patients. Technological advances in computing have led to the introduction of novel physiological biosignals that can increase the frequency at which abnormalities in cardiovascular parameters can be detected, making expert-level, automated diagnosis a reality. However, use of these biosignals for diagnosis also raises numerous concerns related to accuracy and actionability within clinical guidelines, in addition to medico-legal and ethical issues. Analytical methods such as machine learning can potentially increase the accuracy and improve the actionability of device-based diagnoses. Coupled with interoperability of data to widen access to all stakeholders, seamless connectivity (an internet of things) and maintenance of anonymity, this approach could ultimately facilitate near-real-time diagnosis and therapy. These tools are increasingly recognized by regulatory agencies and professional medical societies, but several technical and ethical issues remain. In this Review, we describe the current state of cardiovascular monitoring along the continuum from biosignal acquisition to the identification of novel biosensors and the development of analytical techniques and ultimately to regulatory and ethical issues. Furthermore, we outline new paradigms for cardiovascular monitoring.

Advances in cardiovascular monitoring technologies have resulted in an influx of consumer-targeted wearable sensors that have the potential to detect numerous heart conditions. In this Review, Krittanawong and colleagues describe processes involved in biosignal acquisition and analysis of cardiovascular monitors, as well as their associated ethical, regulatory and legal challenges.

Advances in the use of cardiovascular monitoring technologies, such as the development of novel portable sensors and machine learning algorithms that can provide near-real-time diagnosis, have the potential to provide personalized care.

Wearable sensor technologies can detect numerous biosignals, such as cardiac output, blood-pressure levels and heart rhythm, and can integrate multiple modalities.

The use of novel biosignals for diagnosis raises concerns regarding accuracy and actionability within clinical guidelines, in addition to medical, legal and ethical issues.

Machine learning-based interpretation of biosensor data can facilitate rapid evaluation of the haemodynamic consequences of heart failure or arrhythmias, but is limited by the presence of noise and training data that might not be representative of the real-world clinical setting.

The use of data derived from cardiovascular monitoring devices is associated with numerous challenges, such as data security, accessibility and ownership, in addition to other ethical and regulatory concerns.

Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review

Background

Consumer-wearable activity trackers are small electronic devices that record fitness and health-related measures.

Objective

The purpose of this systematic review was to examine the validity and reliability of commercial wearables in measuring step count, heart rate, and energy expenditure.

Methods

We identified devices to be included in the review. Database searches were conducted in PubMed, Embase, and SPORTDiscus, and only articles published in the English language up to May 2019 were considered. Studies were excluded if they did not identify the device used and if they did not examine the validity or reliability of the device. Studies involving the general population and all special populations were included. We operationalized validity as criterion validity (as compared with other measures) and construct validity (degree to which the device is measuring what it claims). Reliability measures focused on intradevice and interdevice reliability.

Results

We included 158 publications examining nine different commercial wearable device brands. Fitbit was by far the most studied brand. In laboratory-based settings, Fitbit, Apple Watch, and Samsung appeared to measure steps accurately. Heart rate measurement was more variable, with Apple Watch and Garmin being the most accurate and Fitbit tending toward underestimation. For energy expenditure, no brand was accurate. We also examined validity between devices within a specific brand.

Conclusions

Commercial wearable devices are accurate for measuring steps and heart rate in laboratory-based settings, but this varies by the manufacturer and device type. Devices are constantly being upgraded and redesigned to new models, suggesting the need for more current reviews and research.

Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study

Background

Frailty has detrimental health impacts on older home care clients and is associated with increased hospitalization and long-term care admission. The prevalence of frailty among home care clients is poorly understood and ranges from 4.0% to 59.1%. Although frailty screening tools exist, their inconsistent use in practice calls for more innovative and easier-to-use tools. Owing to increases in the capacity of wearable devices, as well as in technology literacy and adoption in Canadian older adults, wearable devices are emerging as a viable tool to assess frailty in this population.

Objective

The objective of this study was to prove that using a wearable device for assessing frailty in older home care clients could be possible.

Methods

From June 2018 to September 2019, we recruited home care clients aged 55 years and older to be monitored over a minimum of 8 days using a wearable device. Detailed sociodemographic information and patient assessments including degree of comorbidity and activities of daily living were collected. Frailty was measured using the Fried Frailty Index. Data collected from the wearable device were used to derive variables including daily step count, total sleep time, deep sleep time, light sleep time, awake time, sleep quality, heart rate, and heart rate standard deviation. Using both wearable and conventional assessment data, multiple logistic regression models were fitted via a sequential stepwise feature selection to predict frailty.

Results

A total of 37 older home care clients completed the study. The mean age was 82.27 (SD 10.84) years, and 76% (28/37) were female; 13 participants were frail, significantly older (P<.01), utilized more home care service (P=.01), walked less (P=.04), slept longer (P=.01), and had longer deep sleep time (P<.01). Total sleep time (r=0.41, P=.01) and deep sleep time (r=0.53, P<.01) were moderately correlated with frailty. The logistic regression model fitted with deep sleep time, step count, age, and education level yielded the best predictive performance with an area under the receiver operating characteristics curve value of 0.90 (Hosmer-Lemeshow P=.88).

Conclusions

We proved that a wearable device could be used to assess frailty for older home care clients. Wearable data complemented the existing assessments and enhanced predictive power. Wearable technology can be used to identify vulnerable older adults who may benefit from additional home care services.

Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy

Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data.

Reliability of the Polar Vantage M Sports Watch when Measuring Heart Rate at Different Treadmill Exercise Intensities

Background: Usage of wrist-worn activity monitors has rapidly increased in recent years, and these devices are being used by both fitness enthusiasts and in clinical populations. We, therefore, assessed the test–retest reliability of the Polar Vantage M (PVM) watch when measuring heart rate (HR) during various treadmill exercise intensities. Methods: HR was measured every 30 s (simultaneous electrocardiography (ECG) and PVM). Test–retest reliability was determined using an intraclass correlation coefficient (ICC) with 95% confidence intervals (CIs). Standard error of measurement (SEM) and smallest real difference (SRD) were used to determine measurement variability. Results: A total of 29 participants completed the trials. ICC values for PVM during stages 1, 2 and 5 demonstrated good to excellent test–retest reliability (0.78, 0.78 and 0.92; 95% CI (0.54–0.90, 0.54–0.9, 0.79–0.97)). For PVM during stages 0 (rest), 3 and 4, the ICC values indicated poor to good reliability (0.42, 0.68 and 0.58; 95% CI (−0.27–0.73, 0.32–0.85, 0.14–0.80)). Conclusion: This study identified that the test–retest reliability of the PVM was comparable at low and high exercise intensities; however, it revealed a poor to good test–retest reliability at moderate intensities. The PVM should not be used in a clinical setting where monitoring of an accurate HR is crucial to the patients’ safety.

Hardware Prototype for Wrist-Worn Simultaneous Monitoring of Environmental, Behavioral, and Physiological Parameters

We designed a low-cost wrist-worn prototype for simultaneously measuring environmental, behavioral, and physiological domains of influencing factors in healthcare. Our prototype continuously monitors ambient elements (sound level, toxic gases, ultraviolet radiation, air pressure, temperature, and humidity), personal activity (motion tracking and body positioning using gyroscope, magnetometer, and accelerometer), and vital signs (skin temperature and heart rate). An innovative three-dimensional hardware, based on the multi-physical-layer approach is introduced. Using board-to-board connectors, several physical hardware layers are stacked on top of each other. All of these layers consist of integrated and/or add-on sensors to measure certain domain (environmental, behavioral, or physiological). The prototype includes centralized data processing, transmission, and visualization. Bi-directional communication is based on Bluetooth Low Energy (BLE) and can connect to smartphones as well as smart cars and smart homes for data analytic and adverse-event alerts. This study aims to develop a prototype for simultaneous monitoring of the all three areas for monitoring of workplaces and chronic obstructive pulmonary disease (COPD) patients with a concentration on technical development and validation rather than clinical investigation. We have implemented 6 prototypes which have been tested by 5 volunteers. We have asked the subjects to test the prototype in a daily routine in both indoor (workplaces and laboratories) and outdoor. We have not imposed any specific conditions for the tests. All presented data in this work are from the same prototype. Eleven sensors measure fifteen parameters from three domains. The prototype delivers the resolutions of 0.1 part per million (PPM) for air quality parameters, 1 dB, 1 index, and 1 °C for sound pressure level, UV, and skin temperature, respectively. The battery operates for 12.5 h under the maximum sampling rates of sensors without recharging. The final expense does not exceed 133€. We validated all layers and tested the entire device with a 75 min recording. The results show the appropriate functionalities of the prototype for further development and investigations.

Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research

Researchers have increasingly begun to use consumer wearables or wrist-worn smartwatches and fitness monitors for measurement of cardiovascular psychophysiological processes related to mental and physical health outcomes. These devices have strong appeal because they allow for continuous, scalable, unobtrusive, and ecologically valid data collection of cardiac activity in "big data" studies. However, replicability and reproducibility may be hampered moving forward due to the lack of standardization of data collection and processing procedures, and inconsistent reporting of technological factors (e.g., device type, firmware versions, and sampling rate), biobehavioral variables (e.g., body mass index, wrist dominance and circumference), and participant demographic characteristics, such as skin tone, that may influence heart rate measurement. These limitations introduce unnecessary noise into measurement, which can cloud interpretation and generalizability of findings. This paper provides a brief overview of research using commercial wearable devices to measure heart rate, reviews literature on device accuracy, and outlines the challenges that non-standardized reporting pose for the field. We also discuss study design, technological, biobehavioral, and demographic factors that can impact the accuracy of the passive sensing of heart rate measurements, and provide guidelines and corresponding checklist handouts for future study data collection and design, data cleaning and processing, analysis, and reporting that may help ameliorate some of these barriers and inconsistencies in the literature.

Validity of Wrist-Worn photoplethysmography devices to measure heart rate: A systematic review and meta-analysis

Heart rate (HR), when combined with accelerometry, can dramatically improve estimates of energy expenditure and sleep. Advancements in technology, via the development and introduction of small, low-cost photoplethysmography devices embedded within wrist-worn consumer wearables, have made the collection of heart rate (HR) under free-living conditions more feasible. This systematic review and meta-analysis compared the validity of wrist-worn HR estimates to a criterion measure of HR (electrocardiography ECG or chest strap). Searches of PubMed/Medline, Web of Science, EBSCOhost, PsycINFO, and EMBASE resulted in a total of 44 articles representing 738 effect sizes across 15 different brands. Multi-level random effects meta-analyses resulted in a small mean difference (beats per min, bpm) of -0.40 bpm (95 confidence interval (CI) -1.64 to 0.83) during sleep, -0.01 bpm (-0.02 to 0.00) during rest, -0.51 bpm (-1.60 to 0.58) during treadmill activities (walking to running), while the mean difference was larger during resistance training (-7.26 bpm, -10.46 to -4.07) and cycling (-4.55 bpm, -7.24 to -1.87). Mean difference increased by 3 bpm (2.5 to 3.5) per 10 bpm increase of HR for resistance training. Wrist-worn devices that measure HR demonstrate acceptable validity compared to a criterion measure of HR for most common activities.

Is the future of leadership development wearable? Exploring self-tracking in leadership programs

This practice forum explores how the “quantified self movement” can contribute to developing leaders by offering new approaches to assessment and feedback. Often associated with wearable technologies (digital technologies worn on the body), self-tracking sensors and feedback systems help individuals assess how they interface with the world, automatically capturing and monitoring data for learning, growth, and change. The authors make the case that such tools can create ongoing opportunities for learning intrapersonal qualities relevant to leadership. In particular, they offer insights about using self-tracking to manage responses to stress and fatigue and for the delivery of verbal presentations. The exploration also notes concerns about the use of technological devices for development purposes. The authors conclude by offering a summary of six factors to consider before using self-tracking tools for leadership development, and by identifying four aspects of self-tracking approaches that would benefit from more I-O psychologist involvement.

Wearable devices for remote vital signs monitoring in the outpatient setting: an overview of the field

Early detection of physiological deterioration has been shown to improve patient outcomes. Due to recent improvements in technology, comprehensive outpatient vital signs monitoring is now possible. This is the first review to collate information on all wearable devices on the market for outpatient physiological monitoring.

A scoping review was undertaken. The monitors reviewed were limited to those that can function in the outpatient setting with minimal restrictions on the patient’s normal lifestyle, while measuring any or all of the vital signs: heart rate, ECG, oxygen saturation, respiration rate, blood pressure and temperature.

A total of 270 papers were included in the review. Thirty wearable monitors were examined: 6 patches, 3 clothing-based monitors, 4 chest straps, 2 upper arm bands and 15 wristbands. The monitoring of vital signs in the outpatient setting is a developing field with differing levels of evidence for each monitor. The most common clinical application was heart rate monitoring. Blood pressure and oxygen saturation measurements were the least common applications. There is a need for clinical validation studies in the outpatient setting to prove the potential of many of the monitors identified.

Research in this area is in its infancy. Future research should look at aggregating the results of validity and reliability and patient outcome studies for each monitor and between different devices. This would provide a more holistic overview of the potential for the clinical use of each device.

Enuretic children have a higher variability in REM sleep when comparing their sleep parameters with nonenuretic control children using a wearable sleep tracker at home

PURPOSE

That children with nocturnal enuresis ("bedwetting") are deep sleepers is a fact that their parents often state when asking for advice. However, until today no clear difference in sleep has been observed between children who do and do not wet the bed. This study investigates the difference in sleep parameters and heart rate variability (HRV) between enuretic and control children in their home setting by using a wearable sleep tracker during a long observation period.

METHODS

Twenty-one enuretic and 18 control children, aged 6 to 12 years old, slept with a wearable sleep tracker device, a Fitbit Charge 2, for 14 consecutive days. In addition, nocturnal urine production (voided volumes and/or weight of the diaper) were measured. The HRV was calculated using the standard time and frequency domain parameters. The Kruskal-Wallis test was applied to evaluate the differences in the sleep and HRV parameters between both groups.

RESULTS

Compared with healthy controls, enuretic children showed a higher standard deviation (P = .0209) of minutes spent in rapid eye movement (REM) sleep among the different nights. In addition, they showed the tendencies to fewer awakenings (P = .1161), although this was not significant. Analyzing the wet nights of the enuretic children, they showed higher autonomic activity, lower sleep efficiency and a higher restlessness compared with their dry nights and to the control group.

CONCLUSION

This 2-weeks sleep-study, using a wrist-worn sleep tracker device Fitbit Charge 2, in the normal home environment has shown that enuretic children have a larger variation in their REM sleep and sleepless efficiently during a wet night when compared with non-bedwetting children.

Heart Rate Extraction in a Headphone Using Infrared Thermometry

The heart rate is a vital indicator of the health state of an individual. By continuously monitoring it, the fitness and health of the cardiovascular system of a user can be analyzed and impending problematic health episodes could be addressed better. Existing techniques to measure heart rate, such as electrocardiogram or photoplethysmography, are either uncomfortable for the user, or are not low-power or sensitive to motion artifacts. Infrared thermography is a non-contact technique with improved user comfort and low power consumption. In this paper, we have analyzed, built, and tested a novel system that uses infrared differential thermometry to detect the heart rate in the auricle. The sensor system was fitted into a commercial headphone since this paper is a first step into integration of the system in a Bluetooth headset. To the best of our knowledge, there has been no previous work on the detection of the heart rate signal in the ear using infrared thermometry. Positive results have been obtained after extraction of the frequency features of the bioheat transfer signal on test persons in rest.

Validation of a wearable biosensor device for vital sign monitoring in septic emergency department patients in Rwanda

Objective

Critical care capabilities needed for the management of septic patients, such as continuous vital sign monitoring, are largely unavailable in most emergency departments (EDs) in low- and middle-income country (LMIC) settings. This study aimed to assess the feasibility and accuracy of using a wireless wearable biosensor device for continuous vital sign monitoring in ED patients with suspected sepsis in an LMIC setting.

Methods

This was a prospective observational study of pediatric (≥2 mon) and adult patients with suspected sepsis at the Kigali University Teaching Hospital ED. Heart rate, respiratory rate and temperature measurements were continuously recorded using a wearable biosensor device for the duration of the patients’ ED course and compared to intermittent manually collected vital signs.

Results

A total of 42 patients had sufficient data for analysis. Mean duration of monitoring was 32.8 h per patient. Biosensor measurements were strongly correlated with manual measurements for heart rate (r = 0.87, p < 0.001) and respiratory rate (r = 0.75, p < 0.001), although were less strong for temperature (r = 0.61, p < 0.001). Mean (SD) differences between biosensor and manual measurements were 1.2 (11.4) beats/min, 2.5 (5.5) breaths/min and 1.4 (1.0)°C. Technical or practical feasibility issues occurred in 12 patients (28.6%) although were minor and included biosensor detachment, connectivity problems, removal for a radiologic study or exam, and patient/parent desire to remove the device.

Conclusions

Wearable biosensor devices can be feasibly implemented and provide accurate continuous heart rate and respiratory rate monitoring in acutely ill pediatric and adult ED patients with sepsis in an LMIC setting.

Comparison of a Wearable Tracker with Actigraph for Classifying Physical Activity Intensity and Heart Rate in Children

Introduction: To examine the validity and reliability of the Fitbit Charge HR (FCH), wrist-worn ActiGraph (AG) accelerometers were used for assessing the classification of physical activity (PA) into intensity categories in children. Methods: Forty-three children (n = 43) participated in the study. Each participant completed 3 min bouts of 12 PAs ranging from sedentary to vigorous intensity while simultaneously wearing FCH and AG on both hands, a Polar HR monitor, and a portable indirect calorimeter. Total time spent in different PA intensity levels measured by FCH and AG were compared to the indirect calorimetry. Results: The highest classification accuracy values of sedentary behavior was 81.1% for FCH. The highest classification (72.4%) of light intensity PA was observed with Crouter’s algorithm from the non-dominant wrist. Crouter’s algorithm also show the highest classification (81.8%) for assessing moderate to vigorous intensity PA compared to FCH (70.8%). Across the devices, a high degree of reliability was found in step measurements, ranging from an intra-class correlation (ICC) = 0.92 to an ICC = 0.94. The reliability of the AG and the FCH showed high agreement for each variable. Conclusion: The FCH shows better validity for estimating sedentary behavior and similar validity for assessing moderate to vigorous PA compared to the research-grade monitor. Across the devices, the reliability showed the strongest association.

Integration of Polypyrrole Electrode into Piezoelectric PVDF Energy Harvester with Improved Adhesion and Over-Oxidation Resistance

Smart textiles for wearable devices require flexibility and a lightweight, so in this study, a soft polypyrrole (PPy) electrode system was integrated into a piezoelectric polyvinylidenefluoride (PVDF) energy harvester. The PVDF energy harvester integrated with a PPy electrode had the piezoelectric output voltage of 4.24-4.56 V, while the PVDF energy harvester with an additional aluminum-foil electrode exhibited 2.57 V. Alkaline treatment and chemical vapor deposition with n-dodecyltrimethoxysilane (DTMS) were employed to improve the adhesion between the PVDF and PPy and the resistance to over-oxidation in aqueous solutions. The PVDF film modified by an alkaline treatment could have the improved adhesion via the introduction of polar functional groups to its surface, which was confirmed by the ultrasonication. The surface hydrophobicity of the PPy electrode was enhanced by the DTMS coating, resulting in the improvement of the resistance to over-oxidation with a water contact angle of 111°. Even with the hydrophobic coating, the electrodes remained electroconductive and continued to transfer an electric charge, maintaining the piezoelectricity of the PVDF film. The developed electrode-integrated energy harvester is expected to be applied to smart textiles because it offers the advantages of efficient piezoelectric generation, flexibility, and durability.

Digitizing a Face-to-Face Group Fatigue Management Program: Exploring the Views of People With Multiple Sclerosis and Health Care Professionals Via Consultation Groups and Interviews

BACKGROUND

Fatigue is one of the most common and debilitating symptoms of multiple sclerosis (MS) and is the main reason why people with MS stop working early. The MS Society in the United Kingdom funded a randomized controlled trial of FACETS-a face-to-face group-based fatigue management program for people with multiple sclerosis (pwMS)-developed by members of the research team. Given the favorable trial results and to help with implementation, the MS Society supported the design and printing of the FACETS manual and materials and the national delivery of FACETS training courses (designed by the research team) for health care professionals (HCPs). By 2015 more than 1500 pwMS had received the FACETS program, but it is not available in all areas and a face-to-face format may not be suitable for, or appeal to, everyone. For these reasons, the MS Society funded a consultation to explore an alternative Web-based model of service delivery.

OBJECTIVE

The aim of this study was to gather views about a Web-based model of service delivery from HCPs who had delivered FACETS and from pwMS who had attended FACETS.

METHODS

Telephone consultations were undertaken with FACETS-trained HCPs who had experience of delivering FACETS (n=8). Three face-to-face consultation groups were held with pwMS who had attended the FACETS program: London (n=4), Liverpool (n=4), and Bristol (n=7). The interviews and consultation groups were digitally recorded and transcribed. A thematic analysis was undertaken to identify key themes. Toward the end of the study, a roundtable meeting was held to discuss outcomes from the consultation with representatives from the MS Society, HCPs, and pwMS.

RESULTS

Key challenges and opportunities of designing and delivering an integrated Web-based version of FACETS and maintaining user engagement were identified across 7 themes (delivery, online delivery, design, group, engagement, interactivity, and HCP relationships). Particularly of interest were themes related to replicating the group dynamics and the lack of high-quality solutions that would support the FACETS' weekly homework tasks and symptom monitoring and management.

CONCLUSIONS

A minimum viable Web-based version of FACETS was suggested as the best starting point for a phased implementation, enabling a solution that could then be added to over time. It was also proposed that a separate study should look to create a free stand-alone digital toolkit focusing on the homework elements of FACETS. This study has commenced with a first version of the toolkit in development involving pwMS throughout the design and build stages to ensure a user-centered solution.

The Clinical Value of Heart Rate Monitoring Using an Apple Watch

Public interest in health monitoring devices has increased with the availability of wearable technologies or wearables such as the Apple Watch. These devices are collecting health data that may be useful to health professionals. Most studies to date have been conducted with a limited sample size and with healthy subjects. Recent studies have suggested the usefulness of long-term cardiac monitoring to reveal atrial fibrillation and prevent cryptogenic stroke. Wearable devices may become useful in cardiac monitoring, and further studies are needed.