Wearable technologies for developing sleep and circadian biomarkers: a summary of workshop discussions

The "International Biomarkers Workshop on Wearables in Sleep and Circadian Science" was held at the 2018 SLEEP Meeting of the Associated Professional Sleep Societies. The workshop brought together experts in consumer sleep technologies and medical devices, sleep and circadian physiology, clinical translational research, and clinical practice. The goals of the workshop were: (1) characterize the term "wearable" for use in sleep and circadian science and identify relevant sleep and circadian metrics for wearables to measure; (2) assess the current use of wearables in sleep and circadian science; (3) identify current barriers for applying wearables to sleep and circadian science; and (4) identify goals and opportunities for wearables to advance sleep and circadian science. For the purposes of biomarker development in the sleep and circadian fields, the workshop included the terms "wearables," "nearables," and "ingestibles." Given the state of the current science and technology, the limited validation of wearable devices against gold standard measurements is the primary factor limiting large-scale use of wearable technologies for sleep and circadian research. As such, the workshop committee proposed a set of best practices for validation studies and guidelines regarding how to choose a wearable device for research and clinical use. To complement validation studies, the workshop committee recommends the development of a public data repository for wearable data. Finally, sleep and circadian scientists must actively engage in the development and use of wearable devices to maintain the rigor of scientific findings and public health messages based on wearable technology.

Flexible and Transparent Cellulose-Based Ionic Film as a Humidity Sensor

A transparent and flexible cellulose/KOH composite ionic film (CKF) is fabricated as a humidity sensor. CKF exhibits high optical transmittance (87.14% at 550 nm), which has rarely been reported among humidity sensors as a result of the small pore size of the cellulose matrix caused by water-evaporation-induced dense packing and uniform distribution of amorphous KOH via simply soaking-drying. CKF also possesses flexibility and robust mechanical property. The conductive CKF shows fast and reversible real-time response to relative humidity (RH) in the 11.3-97.3% RH range with conductance varying over 200 times, response/recovery times of 6.0/10.8 s, which are shorter than the majority of the reported values, as well as a hysteresis error of 0.57%, which is significantly less than that reported in the literature. Furthermore, CKF is insensitive to both the temperature (10-70 °C) and pressure (0-120 kPa), indicating high selectivity as humidity sensors. In both the non-contact fingertip moisture detection and breathing rate detection, the flexible and transparent CKF-based humidity sensor responds favorably to RH change. Moreover, a flexible and transparent CKF-based wearable skin moisture detector is assembled to measure the moisture of human skin in different situations, whose measurement is very close to the commercial detector. The results offer real-time moisture information on human skin and demonstrate the potential of a CKF-based moisture detector as a promising modular component in integrated intelligent wearable equipment.

Effect of wearables on sleep in healthy individuals: a randomized crossover trial and validation study

STUDY OBJECTIVES

The purpose of this study was to determine whether a wearable sleep-tracker improves perceived sleep quality in healthy participants and to test whether wearables reliably measure sleep quantity and quality compared with polysomnography.

METHODS

This study included a single-center randomized crossover trial of community-based participants without medical conditions or sleep disorders. A wearable device (WHOOP, Inc.) was used that provided feedback regarding sleep information to the participant for 1 week and maintained sleep logs versus 1 week of maintained sleep logs alone. Self-reported daily sleep behaviors were documented in sleep logs. Polysomnography was performed on 1 night when wearing the wearable. The Patient-Reported Outcomes Measurement Information System sleep disturbance sleep scale was measured at baseline, day 7 and day 14 of study participation.

RESULTS

In 32 participants (21 women; 23.8 ± 5 years), wearables improved nighttime sleep quality (Patient-Reported Outcomes Measurement Information System sleep disturbance: B = -1.69; 95% confidence interval, -3.11 to -0.27; P = .021) after adjusting for age, sex, baseline, and order effect. There was a small increase in self-reported daytime naps when wearing the device (B = 3.2; SE, 1.4; P = .023), but total daily sleep remained unchanged (P = .43). The wearable had low bias (13.8 minutes) and precision (17.8 minutes) errors for measuring sleep duration and measured dream sleep and slow wave sleep accurately (intraclass coefficient, 0.74 ± 0.28 and 0.85 ± 0.15, respectively). Bias and precision error for heart rate (bias, -0.17%; precision, 1.5%) and respiratory rate (bias, 1.8%; precision, 6.7%) were very low compared with that measured by electrocardiogram and inductance plethysmography during polysomnography.

CONCLUSIONS

In healthy people, wearables can improve sleep quality and accurately measure sleep and cardiorespiratory variables.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Name: Assessment of Sleep by WHOOP in Ambulatory Subjects; Identifier: NCT03692195.

Development and Validation of an Objective, Passive Dietary Assessment Method for Estimating Food and Nutrient Intake in Households in Low- and Middle-Income Countries: A Study Protocol

Malnutrition is a major concern in low- and middle-income countries (LMIC), but the full extent of nutritional deficiencies remains unknown largely due to lack of accurate assessment methods. This study seeks to develop and validate an objective, passive method of estimating food and nutrient intake in households in Ghana and Uganda. Household members (including under-5s and adolescents) are assigned a wearable camera device to capture images of their food intake during waking hours. Using custom software, images captured are then used to estimate an individual's food and nutrient (i.e., protein, fat, carbohydrate, energy, and micronutrients) intake. Passive food image capture and assessment provides an objective measure of food and nutrient intake in real time, minimizing some of the limitations associated with self-reported dietary intake methods. Its use in LMIC could potentially increase the understanding of a population's nutritional status, and the contribution of household food intake to the malnutrition burden. This project is registered at clinicaltrials.gov (NCT03723460).

An Overview of Fiber-Shaped Batteries with a Focus on Multifunctionality, Scalability, and Technical Difficulties

Flexible and wearable energy storage devices are receiving increasing attention with the ever-growing market of wearable electronics. Fiber-shaped batteries display a unique 1D architecture with the merits of superior flexibility, miniaturization potential, adaptability to deformation, and compatibility with the traditional textile industry, which are especially advantageous for wearable applications. In the recent research frontier in the field of fiber-shaped batteries, in addition to higher performance, advances in multifunctional, scalable, and integrable systems are also the main themes. However, many difficulties exist, including difficult encapsulation and installation of separators, high internal resistance, and poor durability. Herein, the design principles (e.g., electrode preparation and battery assembly) and device performance (e.g., electrochemical and mechanical properties) of fiber-shaped batteries, including lithium-based batteries, zinc-based batteries, and some other representative systems, are summarized, with a focus on multifunctional devices with environmental adaptability, stimuli-responsive properties, and scalability up to energy textiles, with the hope of enlightening future research directions. Finally, technical challenges in the realistic wearable application of these batteries are also discussed with the aim of providing possible solutions and new insights for further improvement.

Wearable Emotion Recognition Using Heart Rate Data from a Smart Bracelet

Emotion recognition and monitoring based on commonly used wearable devices can play an important role in psychological health monitoring and human-computer interaction. However, the existing methods cannot rely on the common smart bracelets or watches for emotion monitoring in daily life. To address this issue, our study proposes a method for emotional recognition using heart rate data from a wearable smart bracelet. A 'neutral + target' pair emotion stimulation experimental paradigm was presented, and a dataset of heart rate from 25 subjects was established, where neutral plus target emotion (neutral, happy, and sad) stimulation video pairs from China's standard Emotional Video Stimuli materials (CEVS) were applied to the recruited subjects. Normalized features from the data of target emotions normalized by the baseline data of neutral mood were adopted. Emotion recognition experiment results approved the effectiveness of 'neutral + target' video pair simulation experimental paradigm, the baseline setting using neutral mood data, and the normalized features, as well as the classifiers of Adaboost and GBDT on this dataset. This method will promote the development of wearable consumer electronic devices for monitoring human emotional moods.

Seasonal Variation in Physical Activity among Preoperative Patients with Lung Cancer Determined Using a Wearable Device

We aim to examine how season and temperature levels affect physical activity using a wearable device among patients scheduled to undergo surgical resection of lung cancer. Physical activity (PA) data from the wearable device were analyzed by seasons for 555 preoperative lung cancer patients from the CATCH-LUNG cohort study. The seasons were divided into spring, summer, autumn, and winter using the study enrollment date before surgery. The overall mean (SD) age was 61.1 (8.9) years, and the mean (SD) daily steps at each season were 11,438 (5922), 11,147 (5065), 10,404 (4403), and 8548 (4293), respectively. In the fully-adjusted models, patients in the winter season had 27.04% fewer daily steps (95% CI = -36.68%, -15.93%) and 35.22% less time spent performing moderate to vigorous physical activity (MVPA) compared to patients in the spring. The proportion of participants with over 8000 steps and duration of MVPA were significantly lower in the winter than the spring. In particular, daily steps had a negative linear association with wind chill temperature in patients who lived in Seoul. In conclusion, PA was significantly lower in the winter and it was more robust in patients who had a low cardiorespiratory function.

The Effectiveness of Wearable Upper Limb Assistive Devices in Degenerative Neuromuscular Diseases: A Systematic Review and Meta-Analysis

Background: This systematic review summarizes the current evidence about the effectiveness of wearable assistive technologies for upper limbs support during activities of daily living for individuals with neuromuscular diseases. Methods: Fourteen studies have been included in the meta-analysis, involving 184 participants. All included studies compared patients ability to perform functional tasks with and without assistive devices. Results: An overall effect size of 1.06 (95% CI = 0.76-1.36, p < 0.00001) was obtained, demonstrating that upper limbs assistive devices significantly improve the performance in activities of daily living in people with neuromuscular diseases. A significant interaction between studies evaluating functional improvement with externally-assessed outcome measures or self-perceived outcome measures has been detected. In particular, the effect size of the sub-group considering self-perceived scales was 1.38 (95% CI = 1.08-1.68), while the effect size of the other group was 0.77 (95% CI = 0.41-1.11), meaning that patients' perceived functional gain is often higher than the functional gain detectable through clinical scales. Conclusion: Overall, the quality of the evidence ranged from low to moderate, due to low number of studies and participants, limitations in the selection of participants and in the blindness of outcome assessors, and risk of publication bias. Significance: A large magnitude effect and a clear dose-response gradient were found, therefore, a strong recommendation, in favor of the use of assistive devices could be suggested.

Finger Twitches are More Frequent in REM Sleep Than in Non-REM Sleep

INTRODUCTION

Abnormal rapid eye movement (REM) sleep is often symptomatic of chronic disorders, however polysomnography, the gold standard method to measure REM sleep, is expensive and often impractical. Attempts to develop cost-effective ambulatory systems to measure REM sleep have had limited success. As elevated twitching is often observed during REM sleep in some distal muscles, the aim of this study was to assess the potential for a finger-mounted device to measure finger twitches, and thereby differentiate periods of REM and non-REM (NREM) sleep.

METHODS

One night of sleep data was collected by polysomnography from each of 18 (3f, 15m) healthy adults aged 23.2 ± 3.3 (mean ± SD) years. Finger movement was detected using a piezo-electric limb sensor taped to the index finger of each participant. Finger twitch densities were calculated for each stage of sleep.

RESULTS

Finger twitch density was greater in REM than in NREM sleep (p < 0.001). Each sleep stage had a unique finger twitch density, except for REM and stage N1 sleep which were similar. Finger twitch density was greater in late REM than in early REM sleep (p = 0.005), and there was a time-state interaction: the difference between finger twitch densities in REM and NREM sleep was greater in late sleep than in early sleep (p = 0.007).

CONCLUSION

Finger twitching is more frequent in REM sleep than in NREM sleep and becomes more distinguishable as sleep progresses. Finger twitches appear to be too infrequent to make definitive 30-second epoch determinations of sleep stage. However, an algorithm informed by measures of finger twitch density has the potential to detect periods of REM sleep and provide estimates of total REM sleep time and percentage.

Accuracy and Precision of Three Consumer-Grade Motion Sensors During Overground and Treadmill Walking in People With Parkinson Disease: Cross-Sectional Comparative Study

BACKGROUND

Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD.

OBJECTIVE

This study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD.

METHODS

A total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots.

RESULTS

Participants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0%), 8 (8/628, 1.3%), and 30 (30/628, 4.8%) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8%), 14.7 (14.7/620, 2.4%), and 74.4 (74.4/598, 12.4%) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (-0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking.

CONCLUSIONS

The waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.

Perspectives of People Who Are Overweight and Obese on Using Wearable Technology for Weight Management: Systematic Review

BACKGROUND

Obesity is a large contributor to preventable chronic diseases and health care costs. The efficacy of wearable devices for weight management has been researched; however, there is limited knowledge on how these devices are perceived by users.

OBJECTIVE

This study aimed to review user perspectives on wearable technology for weight management in people who are overweight and obese.

METHODS

We searched the online databases Pubmed, Scopus, Embase, and the Cochrane library for literature published from 2008 onward. We included all types of studies using a wearable device for delivering weight-loss interventions in adults who are overweight or obese, and qualitative data were collected about participants' perspectives on the device. We performed a quality assessment using criteria relevant to different study types. The Cochrane risk of bias tool was used for randomized controlled trials. The Risk of Bias in Non-randomized Studies - of Interventions (ROBINS-I) was used for nonrandomized studies. The Oxman and Guyatt Criteria were used for systematic reviews. We used the critical appraisal checklist for qualitative studies. Data were extracted into a data extraction sheet and thematically analyzed.

RESULTS

We included 19 studies: 5 randomized controlled trials, 6 nonrandomized studies, 5 qualitative studies, and 3 reviews. Mixed perceptions existed for different constructs of wearable technologies, which reflects the differences in the suitability of wearable technology interventions for different individuals in different contexts. This also indicates that interventions were not often tailored to participants' motivations. In addition, very few wearable technology interventions included a thorough qualitative analysis of the participants' view on important features of the intervention that made it successful.

CONCLUSIONS

This study highlights the importance of determining the type of intervention most suitable for an individual before the intervention is used. Our findings could help participants find a suitable intervention that is most effective for them. Further research needs to develop a user-centered tool for obtaining comprehensive user feedback.

TRIAL REGISTRATION

PROSPERO CRD42018096932; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=96932.

Fully-Textile, Wearable Chipless Tags for Identification and Tracking Applications

In this work, two fully-textile wearable devices, to be used as chipless identification tags in identification and tracking applications are presented. For the fabrication of the fully-textile tags, a layer of fleece was used as a substrate, while an adhesive non-woven conductive fabric was employed for the conductive parts. To allow radio-frequency identification of these chipless tags, two alternative techniques were used. One relies on associating a binary code with the resonance frequency of resonant devices: the presence/absence of the resonance peaks in the transmission scattering parameter, | S 21 | , of a set of resonators is used to encode a string of bits. The second technique for accomplishing radio-frequency identification of the chipless tags resorts to a frequency-shift coding technique, which is implemented by modifying the configuration of a hairpin resonator. The obtained numerical and experimental results confirm the suitability of the proposed strategies for obtaining entirely-textile, wearable chipless tags for identification and tracking purposes, which can be particularly useful, especially in the industrial sector. In this field, in fact, the proposed solutions would guarantee a seamless integration with clothes and would facilitate the user's interaction with the IoT infrastructure. In this regard, one of the envisaged application scenarios related to the tracking of hides in the leather industry is also presented.

[A Wearable System for Cervical Spondylosis Prevention Based on Artificial Intelligence]

Accompanied by changes in modern work and lifestyle, the incidence of cervical spondylosis has increased year by year. In view of the fact long-term fixed posture of the head and neck is one of the main causes of cervical spondylosis, a set of wearable cervical spondylosis prevention system is developed. The system comprises a head and neck movement collection module based on the acceleration sensor and a head and neck motion recognition module based on artificial intelligence. Experimental results showed that the system can accurately identify long-term posture of the head and neck, and guide users to complete effective exercise therapy under the supervision of motion recognition module. Using this system can be beneficial for the prevention of cervical spondylosis.

Objectively Monitoring Amyotrophic Lateral Sclerosis Patient Symptoms During Clinical Trials With Sensors: Observational Study

Background

Objective symptom monitoring of patients with Amyotrophic Lateral Sclerosis (ALS) has the potential to provide an important source of information to evaluate the impact of the disease on aspects of real-world functional capacity and activities of daily living in the home setting, providing useful objective outcome measures for clinical trials.

Objective

This study aimed to investigate the feasibility of a novel digital platform for remote data collection of multiple symptoms—physical activity, heart rate variability (HRV), and digital speech characteristics—in 25 patients with ALS in an observational clinical trial setting to explore the impact of the devices on patients’ everyday life and to record tolerability related to the devices and study procedures over 48 weeks.

Methods

In this exploratory, noncontrolled, nondrug study, patients attended a clinical site visit every 3 months to perform activity reference tasks while wearing a sensor, to conduct digital speech tests and for conventional ALS monitoring. In addition, patients wore the sensor in their daily life for approximately 3 days every month for the duration of the study.

Results

The amount and quality of digital speech data captured at the clinical sites were as intended, and there were no significant issues. All the home monitoring sensor data available were propagated through the system and were received as expected. However, the amount and quality of physical activity home monitoring data were lower than anticipated. A total of 3 or more days (or partial days) of data were recorded for 65% of protocol time points, with no data collected for 24% of time points. At baseline, 24 of 25 patients provided data, reduced to 13 of 18 patients at Week 48. Lower-than-expected quality HRV data were obtained, likely because of poor contact between the sensor and the skin. In total, 6 of 25 patients had mild or moderate adverse events (AEs) in the skin and subcutaneous tissue disorders category because of skin irritation caused by the electrode patch. There were no reports of serious AEs or deaths. Most patients found the sensor comfortable, with no or minimal impact on daily activities.

Conclusions

The platform can measure physical activity in patients with ALS in their home environment; patients used the equipment successfully, and it was generally well tolerated. The quantity of home monitoring physical activity data was lower than expected, although it was sufficient to allow investigation of novel physical activity end points. Good-quality in-clinic speech data were successfully captured for analysis. Future studies using objective patient monitoring approaches, combined with the most current technological advances, may be useful to elucidate novel digital biomarkers of disease progression.

Concurrent Validity of a Commercial Wireless Trunk Triaxial Accelerometer System for Gait Analysis

CONTEXT

Wearable sensor devices have notable advantages, such as cost-effectiveness, easy to use, and real-time feedback. Wirelessness ensures full-body motion, which is required during movement in a challenging environment such as during sports. Research on the reliability and validity of commercially available systems, however, is indispensable.

OBJECTIVE

To confirm the test-retest reliability and concurrent validity of a commercially available body-worn sensor-BTS G-WALK® sensor system-for spatiotemporal gait parameters with the GAITRite® walkway system as golden standard.

DESIGN

Reliability and concurrent validity study.

SETTING

Laboratory setting.

PARTICIPANTS

Thirty healthy subjects.

MAIN OUTCOME MEASURES

Spatiotemporal parameters: speed, cadence, stride length, stride duration, stance duration, swing duration, double support, and single support.

RESULTS

In terms of test-retest reliability of the BTS G-WALK® sensor system, intraclass correlation coefficient values for both the spatial and temporal parameters were excellent between consecutive measurements on the same day with intraclass correlation coefficient values ranging from .85 to .99. In terms of validity, intraclass correlation coefficient values between measurement systems showed excellent levels of agreement for speed, cadence, stride length, and stride duration (range = .88-.97), and showed poor to moderate levels of agreement (range = .12-.47) for single/double support and swing/stance duration. Bland-Altman plots showed overall percentage bias values equal to or smaller than 3% with limits of agreement ≤15% (speed, cadence, stride length, stride duration, swing duration, and stance duration). Only for single and double support, the limits of agreement were higher with, respectively, -15.4% to 19.5% and -48.0% to 51.4%.

CONCLUSION

The BTS G-WALK® sensor system is reliable for all measured spatiotemporal parameters. In terms of validity, excellent concurrent validity was shown for speed, cadence, stride length, and stride duration. Cautious interpretation is necessary for temporal parameters based on final foot contact (stance, swing, and single/double support time).

Wireless, Skin-Mountable EMG Sensor for Human-Machine Interface Application

The development of advanced technologies for wireless data collection and the analysis of quantitative data, with application to a human–machine interface (HMI), is of growing interest. In particular, various wearable devices related to HMIs are being developed. These devices require a customization process that considers the physical characteristics of each individual, such as mounting positions of electrodes, muscle masses, and so forth. Here, the authors report device and calculation concepts for flexible platforms that can measure electrical signals changed through electromyography (EMG). This soft, flexible, and lightweight EMG sensor can be attached to curved surfaces such as the forearm, biceps, back, legs, etc., and optimized biosignals can be obtained continuously through post-processing. In addition to the measurement of EMG signals, the application of the HMI has stable performance and high accuracy of more than 95%, as confirmed by 50 trials per case. The result of this study shows the possibility of application to various fields such as entertainment, the military, robotics, and healthcare in the future.

Mobile Health Access and Use Among Individuals With or At Risk for Cardiovascular Disease: 2018 Health Information National Trends Survey (HINTS)

Background Mobile health (mHealth) technologies can deliver interventions to prevent and manage cardiovascular disease (CVD), but mHealth uptake among those with or at risk for CVD remains incompletely explored. Therefore, in this group, we assessed the prevalence of mHealth access and usage, and the association between CVD risk and mHealth uptake. Methods and Results Data were from 3248 adults in the 2018 Health Information National Trends Survey. We defined CVD risk as reporting a heart condition, diabetes mellitus, hypertension, and/or current smoking (n=1903). Multivariable logistic regression, adjusting for demographics, was used to assess the relationship between CVD risk and mHealth uptake. Most individuals with CVD risk owned a smartphone (73%, 95% CI: 69%-76%) and 48% (95% CI: 44%-52%) had a health app. Among men, those with CVD risk were more likely to use a wearable device (odds ratio 2.43, 95% CI: 1.44-4.10) than those without CVD risk, while there was no difference among women. In both sexes, CVD risk was associated with sharing information from a smartphone/wearable with a clinician (odds ratio 1.63, 95% CI 1.12-2.35 in women; odds ratio 3.99, 95% CI 2.30-6.95 in men). However, there was no difference in the odds of using mHealth to track health progress, make health decisions, aid healthcare discussions, or text a clinician. Conclusions In a nationally representative sample, there was high prevalence of smartphone ownership but incomplete mHealth uptake. Having CVD or its risk factors was associated with sharing information from smartphone/wearables, suggesting potential to leverage clinically validated mHealth interventions for CVD prevention.

Design and verification of 5-channel 1.5T knee joint receiving coil based on wearable technology

BACKGROUND

Over the past 20 years, magnetic resonance receiving coil technology has developed rapidly. The traditional, commercial knee joint coil has a fixed mechanical structure. To meet the imaging needs of most patients, it is necessary to ensure that the mechanical geometry of the coil is as large as possible. Therefore, different quality images can be obtained by filling coefficients under loads of knees of different sizes. Lufkin et al. [1] have demonstrated that the signal-to-noise ratio (SNR) of coil imaging is directly proportional to its filling coefficient, which is S/N≈QL*η. Thus, the pursuit of an optimal coil filling coefficient is an important way to improve the coil imaging quality.

OBJECTIVE

This study combines wearable concepts and coil development techniques and applies flexible and elastic materials to coil designs.

METHODS

We used an elastic material instead of the traditional fixed mechanical structure to develop a 1.5T 5-channel knee joint receiving coil that can be attached to knee joints of different sizes within a certain range, allowing the coil to achieve a maximum filling coefficient under the loads of knees of different sizes.

RESULTS

Compared to commercial 8-channel knee coils, the phantom test and clinical knee joint imaging demonstrated that the SNR of the developed coil increased by four times in the shallow layer and two times in the deep layer, under different load conditions.

CONCLUSION

This high SNR performance demonstrates potential for the realization of high resolution and fast imaging sequences in knee imaging.

Cuffless Blood Pressure Monitoring from an Array of Wrist Bio-Impedance Sensors Using Subject-Specific Regression Models: Proof of Concept

Continuous and beat-to-beat monitoring of blood pressure (BP), compared to office-based BP measurement, provides significant advantages in predicting future cardiovascular disease. Traditional BP measurement methods are based on a cuff, which is bulky, obtrusive and not applicable to continuous monitoring. Measurement of pulse transit time (PTT) is one of the prominent cuffless methods for continuous BP monitoring. PTT is the time taken by the pressure pulse to travel between two points in an arterial vessel, which is correlated with the BP. In this paper, we present a new cuffless BP method using an array of wrist-worn bio-impedance sensors placed on the radial and the ulnar arteries of the wrist to monitor the arterial pressure pulse from the blood volume changes at each sensor site. BP is accurately estimated by using AdaBoost regression model based on selected arterial pressure pulse features such as transit time, amplitude and slope of the pressure pulse, which are dependent on the cardiac activity and the vascular properties of the wrist arteries. A separate model is developed for each subject based on calibration data to capture the individual variations of BP parameters. In this pilot study, data was collected from 10 healthy participants with age ranges from 18 to 30 years after exercising using our custom low-noise bio-impedance sensing hardware. Post-exercise BP was accurately estimated with an average correlation coefficient and root mean square error (RMSE) of 0.77 and 2.6 mmHg for the diastolic BP and 0.86 and 3.4 mmHg for the systolic BP.

Accuracy of Wristband Fitbit Models in Assessing Sleep: Systematic Review and Meta-Analysis

BACKGROUND

Wearable sleep monitors are of high interest to consumers and researchers because of their ability to provide estimation of sleep patterns in free-living conditions in a cost-efficient way.

OBJECTIVE

We conducted a systematic review of publications reporting on the performance of wristband Fitbit models in assessing sleep parameters and stages.

METHODS

In adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we comprehensively searched the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane, Embase, MEDLINE, PubMed, PsycINFO, and Web of Science databases using the keyword Fitbit to identify relevant publications meeting predefined inclusion and exclusion criteria.

RESULTS

The search yielded 3085 candidate articles. After eliminating duplicates and in compliance with inclusion and exclusion criteria, 22 articles qualified for systematic review, with 8 providing quantitative data for meta-analysis. In reference to polysomnography (PSG), nonsleep-staging Fitbit models tended to overestimate total sleep time (TST; range from approximately 7 to 67 mins; effect size=-0.51, P<.001; heterogenicity: I2=8.8%, P=.36) and sleep efficiency (SE; range from approximately 2% to 15%; effect size=-0.74, P<.001; heterogenicity: I2=24.0%, P=.25), and underestimate wake after sleep onset (WASO; range from approximately 6 to 44 mins; effect size=0.60, P<.001; heterogenicity: I2=0%, P=.92) and there was no significant difference in sleep onset latency (SOL; P=.37; heterogenicity: I2=0%, P=.92). In reference to PSG, nonsleep-staging Fitbit models correctly identified sleep epochs with accuracy values between 0.81 and 0.91, sensitivity values between 0.87 and 0.99, and specificity values between 0.10 and 0.52. Recent-generation Fitbit models that collectively utilize heart rate variability and body movement to assess sleep stages performed better than early-generation nonsleep-staging ones that utilize only body movement. Sleep-staging Fitbit models, in comparison to PSG, showed no significant difference in measured values of WASO (P=.25; heterogenicity: I2=0%, P=.92), TST (P=.29; heterogenicity: I2=0%, P=.98), and SE (P=.19) but they underestimated SOL (P=.03; heterogenicity: I2=0%, P=.66). Sleep-staging Fitbit models showed higher sensitivity (0.95-0.96) and specificity (0.58-0.69) values in detecting sleep epochs than nonsleep-staging models and those reported in the literature for regular wrist actigraphy.

CONCLUSIONS

Sleep-staging Fitbit models showed promising performance, especially in differentiating wake from sleep. However, although these models are a convenient and economical means for consumers to obtain gross estimates of sleep parameters and time spent in sleep stages, they are of limited specificity and are not a substitute for PSG.

Development and testing of a wearable wrist-to-forearm posture measurement system for hand-tool design evaluation

This study reports on the development and testing of a wearable wrist-to-forearm angle-measurement system for flexion/extension and radial/ulnar deviation of the wrist, and pronation/supination of the forearm. The system is based on inertial sensors and a microcontroller mounted on a glove and a forearm pad. The developed system was tested through the comparison of two off-the-shelf screwdrivers, one long and one short. Twelve male subjects participated in a within-subject experimental design test and performed a horizontal and a vertical screwing task for each screwdriver. Results indicated that the use of a long screwdriver causes significantly higher ulnar deviation of the wrist in both set-ups, while the short screwdriver promotes higher wrist extension in both set-ups. Clarity of the obtained results indicates that the proposed system is adequate for ergonomics studies on hand-tool design evaluation, while it addresses common pitfalls of other motion-capture methods.

Wearable Fall Detector Using Recurrent Neural Networks

Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices allow the implementation of continuous and ubiquitous monitoring systems. The effectiveness for analyzing temporal signals with low energy consumption is one of the most relevant characteristics of these devices. Recurrent neural networks (RNNs) have demonstrated a great accuracy in some problems that require analyzing sequential inputs. However, getting appropriate response times in low power microcontrollers remains a difficult task due to their limited hardware resources. This work shows a feasibility study about using RNN-based deep learning models to detect both falls and falls’ risks in real time using accelerometer signals. The effectiveness of four different architectures was analyzed using the SisFall dataset at different frequencies. The resulting models were integrated into two different embedded systems to analyze the execution times and changes in the model effectiveness. Finally, a study of power consumption was carried out. A sensitivity of 88.2% and a specificity of 96.4% was obtained. The simplest models reached inference times lower than 34 ms, which implies the capability to detect fall events in real-time with high energy efficiency. This suggests that RNN models provide an effective method that can be implemented in low power microcontrollers for the creation of autonomous wearable fall detection systems in real-time.

Wearable, Stretchable, Transparent All-in-One Soft Sensor Formed from Supersonically Sprayed Silver Nanowires

The demand for wearable, stretchable soft electronics for human-machine interface applications continues to grow given the potential of these devices in humanoid robotics, prosthetics, and health-monitoring devices. We demonstrate fabrication of multifunctional sensors with simultaneous temperature-, pressure-, proximity-, and strain (or bending)-sensing capabilities, combined with heating and UV-protection features. These multifunctional sensors are flexible, light, and transparent and are thus body-attachable. Silver nanowires are supersonically sprayed on a large-scale transparent and flexible roll-to-roll substrate. The junctions between nanowires are physically fused by a strong impact resulting from supersonic spraying, which promotes adhesion and efficient deposition of the nanowire network. Accordingly, nanowires are strongly interconnected, facilitating efficient propagation of electric signals through the fused nanowire network, which allows simultaneous operation of such sensors while maintaining significant transparency. These multifunctional sensors are mechanically durable and retain long-term stability. A theoretical discussion is provided to explain the respective mechanisms of heating and proximity, pressure, and strain sensing.

A Research Roadmap: Connected Health as an Enabler of Cancer Patient Support

The evidence that quality of life is a positive variable for the survival of cancer patients has prompted the interest of the health and pharmaceutical industry in considering that variable as a final clinical outcome. Sustained improvements in cancer care in recent years have resulted in increased numbers of people living with and beyond cancer, with increased attention being placed on improving quality of life for those individuals. Connected Health provides the foundations for the transformation of cancer care into a patient-centric model, focused on providing fully connected, personalized support and therapy for the unique needs of each patient. Connected Health creates an opportunity to overcome barriers to health care support among patients diagnosed with chronic conditions. This paper provides an overview of important areas for the foundations of the creation of a new Connected Health paradigm in cancer care. Here we discuss the capabilities of mobile and wearable technologies; we also discuss pervasive and persuasive strategies and device systems to provide multidisciplinary and inclusive approaches for cancer patients for mental well-being, physical activity promotion, and rehabilitation. Several examples already show that there is enthusiasm in strengthening the possibilities offered by Connected Health in persuasive and pervasive technology in cancer care. Developments harnessing the Internet of Things, personalization, patient-centered design, and artificial intelligence help to monitor and assess the health status of cancer patients. Furthermore, this paper analyses the data infrastructure ecosystem for Connected Health and its semantic interoperability with the Connected Health economy ecosystem and its associated barriers. Interoperability is essential when developing Connected Health solutions that integrate with health systems and electronic health records. Given the exponential business growth of the Connected Health economy, there is an urgent need to develop mHealth (mobile health) exponentially, making it both an attractive and challenging market. In conclusion, there is a need for user-centered and multidisciplinary standards of practice to the design, development, evaluation, and implementation of Connected Health interventions in cancer care to ensure their acceptability, practicality, feasibility, effectiveness, affordability, safety, and equity.

Flexible, High-Power Density, Wearable Thermoelectric Nanogenerator and Self-Powered Temperature Sensor

We propose a flexible and wearable thermoelectric nanogenerator (FTEG) made from Bi₂Te₃, which allows high voltage and output power density. The proposed FTEG works as a thermopile with the end-to-end connection of 126 thermoelectric legs, and which is fabricated through magnetron sputtering Cu conductor on polyethylene terephthalate film. Bi, Te, Sb, and Se alloys are used to prepare thermoelectric materials by doping in a fixed proportion and zone melting, and nickel plating on the surface mitigates the deterioration of thermoelectric properties caused by the diffusion of Cu atoms or Cu⁺ ions. The thermoelectric figure of merit is stable and maintained above 0.7, up to 1.02. More flexibility is allowed by employing double sinusoidal serpentine connecting wires, and no significant property changes are observed even after being folded 200 times. When the temperature difference reaches 50 K, the output voltage of the FTEG will be no less than 520 mV, and the power density will reach 11.14 mW·cm^-2. By integration of a low-power, low-threshold voltage boost circuit on the back end of the FTEG, the electronic watch with a liquid crystal display screen can be easily powered to work properly. Furthermore, the FTEG is temperature-sensitive and, thus, can be used for temperature measurement with a resolution of 0.5 K. This work may have important prospects in flexible wearable physical sensors and individualized medical care.

A Review of Force Myography Research and Development

Information about limb movements can be used for monitoring physical activities or for human-machine-interface applications. In recent years, a technique called Force Myography (FMG) has gained ever-increasing traction among researchers to extract such information. FMG uses force sensors to register the variation of muscle stiffness patterns around a limb during different movements. Using machine learning algorithms, researchers are able to predict many different limb activities. This review paper presents state-of-art research and development on FMG technology in the past 20 years. It summarizes the research progress in both the hardware design and the signal processing techniques. It also discusses the challenges that need to be solved before FMG can be used in an everyday scenario. This paper aims to provide new insight into FMG technology and contribute to its advancement.

Practical and Durable Flexible Strain Sensors Based on Conductive Carbon Black and Silicone Blends for Large Scale Motion Monitoring Applications

Presented is a flexible capacitive strain sensor, based on the low cost materials silicone (PDMS) and carbon black (CB), that was fabricated by casting and curing of successive silicone layers—a central PDMS dielectric layer bounded by PDMS/CB blend electrodes and packaged by exterior PDMS films. It was effectively characterized for large flexion-angle motion wearable applications, with strain sensing properties assessed over large strains (50%) and variations in temperature and humidity. Additionally, suitability for monitoring large tissue deformation was established by integration with an in vitro digestive model. The capacitive gauge factor was approximately constant at 0.86 over these conditions for the linear strain range (3 to 47%). Durability was established from consistent relative capacitance changes over 10,000 strain cycles, with varying strain frequency and elongation up to 50%. Wearability and high flexion angle human motion detection were demonstrated by integration with an elbow band, with clear detection of motion ranges up 90°. The device’s simple structure and fabrication method, low-cost materials and robust performance, offer promise for expanding the availability of wearable sensor systems.

Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface

Brain-computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) machines and computers are usually required to acquire EEG signal and translate them into control commands, respectively. The sizes of the above machines are usually large, and this increases the limitation for daily applications. Moreover, conventional EEG electrodes also require conductive gels to improve the EEG signal quality. This causes discomfort and inconvenience of use, while the conductive gels may also encounter the problem of drying out during prolonged measurements. In order to improve the above issues, a wearable headset with steady-state visually evoked potential (SSVEP)-based BCI is proposed in this study. Active dry electrodes were designed and implemented to acquire a good EEG signal quality without conductive gels from the hairy site. The SSVEP BCI algorithm was also implemented into the designed field-programmable gate array (FPGA)-based BCI module to translate SSVEP signals into control commands in real time. Moreover, a commercial tablet was used as the visual stimulus device to provide graphic control icons. The whole system was designed as a wearable device to improve convenience of use in daily life, and it could acquire and translate EEG signal directly in the front-end headset. Finally, the performance of the proposed system was validated, and the results showed that it had excellent performance (information transfer rate = 36.08 bits/min).

Recent Advances in Skin Chemical Sensors

This review summarizes the latest developments in the field of skin chemical sensors, in particular wearable ones. Five major applications are covered in the present work: (i) sweat analysis, (ii) skin hydration, (iii) skin wounds, (iv) perspiration of volatile organic compounds, and (v) general skin conditions. For each application, the detection of the most relevant analytes is described in terms of transduction principles and sensor performances. Special attention is paid to the biological fluid collection and storage and devices are also analyzed in terms of reusability and lifetime. This review highlights the existing gaps between current performances and those needed to promote effective commercialization of sensors; future developments are also proposed.

INSPEX: Optimize Range Sensors for Environment Perception as a Portable System

Environment perception is crucial for the safe navigation of vehicles and robots to detect obstacles in their surroundings. It is also of paramount interest for navigation of human beings in reduced visibility conditions. Obstacle avoidance systems typically combine multiple sensing technologies (i.e., LiDAR, radar, ultrasound and visual) to detect various types of obstacles under different lighting and weather conditions, with the drawbacks of a given technology being offset by others. These systems require powerful computational capability to fuse the mass of data, which limits their use to high-end vehicles and robots. INSPEX delivers a low-power, small-size and lightweight environment perception system that is compatible with portable and/or wearable applications. This requires miniaturizing and optimizing existing range sensors of different technologies to meet the user’s requirements in terms of obstacle detection capabilities. These sensors consist of a LiDAR, a time-of-flight sensor, an ultrasound and an ultra-wideband radar with measurement ranges respectively of 10 m, 4 m, 2 m and 10 m. Integration of a data fusion technique is also required to build a model of the user’s surroundings and provide feedback about the localization of harmful obstacles. As primary demonstrator, the INSPEX device will be fixed on a white cane.

Heart Rate Measures From Wrist-Worn Activity Trackers in a Laboratory and Free-Living Setting: Validation Study

Background

Wrist-worn activity trackers are popular, and an increasing number of these devices are equipped with heart rate (HR) measurement capabilities. However, the validity of HR data obtained from such trackers has not been thoroughly assessed outside the laboratory setting.

Objective

This study aimed to investigate the validity of HR measures of a high-cost consumer-based tracker (Polar A370) and a low-cost tracker (Tempo HR) in the laboratory and free-living settings.

Methods

Participants underwent a laboratory-based cycling protocol while wearing the two trackers and the chest-strapped Polar H10, which acted as criterion. Participants also wore the devices throughout the waking hours of the following day during which they were required to conduct at least one 10-min bout of moderate-to-vigorous physical activity (MVPA) to ensure variability in the HR signal. We extracted 10-second values from all devices and time-matched HR data from the trackers with those from the Polar H10. We calculated intraclass correlation coefficients (ICCs), mean absolute errors, and mean absolute percentage errors (MAPEs) between the criterion and the trackers. We constructed decile plots that compared HR data from Tempo HR and Polar A370 with criterion measures across intensity deciles. We investigated how many HR data points within the MVPA zone (≥64% of maximum HR) were detected by the trackers.

Results

Of the 57 people screened, 55 joined the study (mean age 30.5 [SD 9.8] years). Tempo HR showed moderate agreement and large errors (laboratory: ICC 0.51 and MAPE 13.00%; free-living: ICC 0.71 and MAPE 10.20%). Polar A370 showed moderate-to-strong agreement and small errors (laboratory: ICC 0.73 and MAPE 6.40%; free-living: ICC 0.83 and MAPE 7.10%). Decile plots indicated increasing differences between Tempo HR and the criterion as HRs increased. Such trend was less pronounced when considering the Polar A370 HR data. Tempo HR identified 62.13% (1872/3013) and 54.27% (5717/10,535) of all MVPA time points in the laboratory phase and free-living phase, respectively. Polar A370 detected 81.09% (2273/2803) and 83.55% (9323/11,158) of all MVPA time points in the laboratory phase and free-living phase, respectively.

Conclusions

HR data from the examined wrist-worn trackers were reasonably accurate in both the settings, with the Polar A370 showing stronger agreement with the Polar H10 and smaller errors. Inaccuracies increased with increasing HRs; this was pronounced for Tempo HR.

Blending active and passive digital technology methods to improve symptom monitoring in early psychosis

AIMS

Psychotic symptoms fluctuate over time and effective and regular monitoring may contribute to relapse prevention and improve long-term outcomes. In this proof-of-concept study we test the feasibility, acceptability and potential usefulness of a novel digital method assessing the association between physiological signals and psychotic symptom distress.

METHODS

Fifteen participants with first episode psychosis were asked to use a self-assessment mobile phone application for psychotic symptom monitoring for 10 days while using a wrist worn device continuously recording heart rate variability (HRV) and electrodermal activity (EDA). We compared physiological activity when participants reported experiencing distressing and non-distressing psychotic symptoms.

RESULTS

Participants completed on average 76% of the mobile phone symptom assessments. When reporting distressing hallucinations and delusions participants had significantly higher EDA levels and non-significant lower HRV values compared to when these symptoms were non-distressing.

CONCLUSIONS

This study provides further evidence linking psychotic symptom's distress, as experienced in everyday life, and autonomic deregulation. This proof-of-concept study may lead to further longer-term efforts to identify relapse biosignatures using automated methods based on passive monitoring. This method may allow for earlier interventions, contribute to improve relapse prevention and reduce symptoms interfering with recovery.

Two-Dimensional Materials in Biosensing and Healthcare: From In Vitro Diagnostics to Optogenetics and Beyond

Since the isolation of graphene in 2004, there has been an exponentially growing number of reports on layered two-dimensional (2D) materials for applications ranging from protective coatings to biochemical sensing. Due to the exceptional, and often tunable, electrical, optical, electrochemical, and physical properties of these materials, they can serve as the active sensing element or a supporting substrate for diverse healthcare applications. In this review, we provide a survey of the recent reports on the applications of 2D materials in biosensing and other emerging healthcare areas, ranging from wearable technologies to optogenetics to neural interfacing. Specifically, this review provides (i) a holistic evaluation of relevant material properties across a wide range of 2D systems, (ii) a comparison of 2D material-based biosensors to the state-of-the-art, (iii) relevant material synthesis approaches specifically reported for healthcare applications, and (iv) the technological considerations to facilitate mass production and commercialization.

Wearable Inertial Sensors to Assess Standing Balance: A Systematic Review

Wearable sensors are de facto revolutionizing the assessment of standing balance. The aim of this work is to review the state-of-the-art literature that adopts this new posturographic paradigm, i.e., to analyse human postural sway through inertial sensors directly worn on the subject body. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 73 full-text articles, selecting 47 high-quality contributions. A good inter-rater reliability was obtained (Cohen's kappa = 0.79). This selection of papers was used to summarize the available knowledge on the types of sensors used and their positioning, the data acquisition protocols and the main applications in this field (e.g., "active aging", biofeedback-based rehabilitation for fall prevention, and the management of Parkinson's disease and other balance-related pathologies), as well as the most adopted outcome measures. A critical discussion on the validation of wearable systems against gold standards is also presented.

Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review

BACKGROUND

A growing number of wearable devices claim to provide accurate, cheap and easily applicable heart rate variability (HRV) indices. This is mainly accomplished by using wearable photoplethysmography (PPG) and/or electrocardiography (ECG), through simple and non-invasive techniques, as a substitute of the gold standard RR interval estimation through electrocardiogram. Although the agreement between pulse rate variability (PRV) and HRV has been evaluated in the literature, the reported results are still inconclusive especially when using wearable devices.

AIM

The purpose of this systematic review is to investigate if wearable devices provide a reliable and precise measurement of classic HRV parameters in rest as well as during exercise.

MATERIALS AND METHODS

A search strategy was implemented to retrieve relevant articles from MEDLINE and SCOPUS databases, as well as, through internet search. The 308 articles retrieved were reviewed for further evaluation according to the predetermined inclusion/exclusion criteria.

RESULTS

Eighteen studies were included. Sixteen of them integrated ECG - HRV technology and two of them PPG - PRV technology. All of them examined wearable devices accuracy in RV detection during rest, while only eight of them during exercise. The correlation between classic ECG derived HRV and the wearable RV ranged from very good to excellent during rest, yet it declined progressively as exercise level increased.

CONCLUSIONS

Wearable devices may provide a promising alternative solution for measuring RV. However, more robust studies in non-stationary conditions are needed using appropriate methodology in terms of number of subjects involved, acquisition and analysis techniques implied.

Normative Peak 30-Min Cadence (Steps per Minute) Values for Older Adults: NHANES 2005-2006

Walking cadence (steps per minute) is associated with the intensity of ambulatory behavior. This analysis provides normative values for peak 30-min cadence, an indicator of "natural best effort" during free-living behavior. A sample of 1,196 older adults (aged from 60 to 85+) with accelerometer data from the National Health and Nutrition Examination Survey 2005-2006 was used. Peak 30-min cadence was calculated for each individual. Quintile-defined values were computed, stratified by sex and age groups. Smoothed sex-specific centile curves across the age span were fitted using the LMS method. Peak 30-min cadence generally trended lower as age increased. The uppermost quintile value was >85 steps/min (men: 60-64 years), and the lowermost quintile value was <22 steps/min (women: 85+). The highest 95th centile value was 103 steps/min (men: 64-70 years), and the lowest 5th centile value was 15 steps/min (women: 85+). These normative values may be useful for evaluating older adults' "natural best effort" during free-living ambulatory behavior.

Realities of conducting digital health research: Challenges to consider

The health sector has been slow to adopt and integrate new technological advances into antiquated workflows and processes. The onset of smart health applications and devices has initiated a push for healthcare systems as well as physicians to incorporate and utilize such technology and the big data it collects. However, without considering the challenges experienced in large-scale trials, physicians and their clinics will run into similar barriers to implementation and uptake. Thoughtful implementation and preparation will make the use of such technological advances possible, palatable and effective in improving clinical care.

Analysis of Sensitivity, Linearity, Hysteresis, Responsiveness, and Fatigue of Textile Knit Stretch Sensors

Wearable technology is widely used for collecting information about the human body and its movement by placing sensors on the body. This paper presents research into electronic textile strain sensors designed specifically for wearable applications which need to be lightweight, robust, and comfortable. In this paper, sixteen stretch sensors, each with different conductive stretch fabrics, are evaluated: EeonTex (Eeonyx Corporation), knitted silver-plated yarn, and knitted spun stainless steel yarn. The sensors’ performance is tested using a tensile tester while monitoring their resistance with a microcontroller. Each sensor was analyzed for its sensitivity, linearity, hysteresis, responsiveness, and fatigue through a series of dynamic and static tests. The findings show that for wearable applications a subset of the silver-plated yarn sensors had better ranked performance in terms of sensitivity, linearity, and steady state. EeonTex was found to be the most responsive, and the stainless steel yarn performed the worst, which may be due to the characteristics of the knit samples under test.

putEMG-A Surface Electromyography Hand Gesture Recognition Dataset

In this paper, we present a putEMG dataset intended for the evaluation of hand gesture recognition methods based on sEMG signal. The dataset was acquired for 44 able-bodied subjects and include 8 gestures (3 full hand gestures, 4 pinches and idle). It consists of uninterrupted recordings of 24 sEMG channels from the subject's forearm, RGB video stream and depth camera images used for hand motion tracking. Moreover, exemplary processing scripts are also published. The putEMG dataset is available under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). The dataset was validated regarding sEMG amplitudes and gesture recognition performance. The classification was performed using state-of-the-art classifiers and feature sets. An accuracy of 90% was achieved for SVM classifier utilising RMS feature and for LDA classifier using Hudgin's and Du's feature sets. Analysis of performance for particular gestures showed that LDA/Du combination has significantly higher accuracy for full hand gestures, while SVM/RMS performs better for pinch gestures. The presented dataset can be used as a benchmark for various classification methods, the evaluation of electrode localisation concepts, or the development of classification methods invariant to user-specific features or electrode displacement.

Low-Cost and Highly Sensitive Wearable Sensor Based on Napkin for Health Monitoring

The development of sensors with high sensitivity, good flexibility, low cost, and capability of detecting multiple inputs is of great significance for wearable electronics. Herein, we report a napkin-based wearable capacitive sensor fabricated by a novel, low-cost, and facile strategy. The capacitive sensor is composed of two pieces of electrode plates manufactured by spontaneous assembly of silver nanowires (NWs) on a polydimethylsiloxane (PDMS)-patterned napkin. The sensor possesses high sensitivity (>7.492 kPa⁻¹), low cost, and capability for simultaneous detection of multiple signals. We demonstrate that the capacitive sensor can be applied to identify a variety of human physiological signals, including finger motions, eye blinking, and minute wrist pulse. More interestingly, the capacitive sensor comfortably attached to the temple can simultaneously monitor eye blinking and blood pulse. The demonstrated sensor shows great prospects in the applications of human–machine interface, prosthetics, home-based healthcare, and flexible touch panels.

Continuously monitoring shoulder motion after total shoulder arthroplasty: maximum elevation and time spent above 90° of elevation are critical metrics to monitor

BACKGROUND

Traditional clinical shoulder range-of-motion (ROM) measurement methods (ie, goniometry) have limitations assessing ROM in total shoulder arthroplasty (TSA) patients. Inertial measurement units (IMUs) are superior; however, further work is needed using IMUs to longitudinally assess shoulder ROM before TSA and throughout post-TSA rehabilitation. Accordingly, the study aims were to prospectively capture shoulder elevation in TSA patients and to compare the results with healthy controls. We hypothesized that patients would have reduced maximum elevation before TSA compared with controls but would have improved ROM after TSA.

METHODS

A validated IMU-based shoulder elevation quantification method was used to continuously monitor 10 healthy individuals (4 men and 6 women; mean age, 69 ± 20 years) without shoulder pathology and 10 TSA patients (6 men and 4 women; mean age, 70 ± 8 years). Controls wore IMUs for 1 week. Patients wore IMUs for 1 week before TSA, for 6 weeks at 3 months after TSA, and for 1 week at 1 year after TSA. Shoulder elevation was calculated continuously, broken into 5° angle "bins" (0°-5°, 5°-10°, and so on), and converted to percentages. The main outcome measures were binned movement percentage, maximum elevation, and average elevation. Patient-reported outcome measures and goniometric ROM were also captured.

RESULTS

No demographic differences were noted between the cohorts. Average elevation was not different between the cohorts at any time. Control maximum elevation was greater than pre-TSA and post-TSA week 1 and week 2 values. Time under 30° and time above 90° were equal between the cohorts before TSA. After TSA, patients showed decreased time under 30° and increased time above 90°.

DISCUSSION

This study demonstrates that acute and chronic recovery after TSA can be assessed via maximum elevation and time above 90°, respectively. These results inform how healthy individuals and patients use their shoulders before and after TSA.

Assessment of signal quality measured with a smart 12-lead ECG acquisition T-shirt

BACKGROUND

Ambulatory ECG monitoring is typically achieved using portable devices with limited number of surface leads, autonomy, and length of recording. Smart garments with multiple conductive textile electrodes provide great promise to perform continuous and comfortable ECG monitoring.

METHODS

We evaluated the ECG signal quality measured on healthy subjects with a smart 12-lead ECG acquisition T-shirt or a 12-lead Holter recording. ECG signals were recorded during 3 min with both techniques in three resting positions (supine, seated, standing) and while walking. Three readers independently assessed ECG patterns and evaluated the denoising of the isoelectric line, the distinction of p waves, R peaks and RR intervals, and the possible appreciation of cardiac rhythm in at least 3 leads.

RESULTS

Thirty healthy subjects (70% males, 29.5 ± 7.8 years) were enrolled in the study. For all three resting conditions, cardiac rhythm was appreciated in 100% of recordings with distinction of p waves, R peaks, and isoelectric line in >97% of recordings. Appreciation of cardiac rhythm was lower in the walking conditions with both techniques (53.3% vs. 46.7%, Holter vs. smart T-shirt, p = .60) mainly due to difficulties to distinguish p waves. These results were consistent across both genders. All ECG parameters (heart rate, PR, QRS and QTC intervals) were comparable between both techniques. No skin irritation was seen with the textile electrodes.

CONCLUSIONS

A smart T-shirt with 13 textiles electrodes allows short-duration 12-lead ECG acquisition with quality levels comparable to Holter recordings. The novel device should now be evaluated for long-term non-invasive ECG monitoring.

All Paper-Based Flexible and Wearable Piezoresistive Pressure Sensor

Flexible and wearable pressure sensors are of paramount importance for the development of personalized medicine and electronic skin. However, the preparation of easily disposable pressure sensors is still facing pressing challenges. Herein, we have developed an all paper-based piezoresistive (APBP) pressure sensor through a facile, cost-effective, and environmentally friendly method. This pressure sensor was based on a tissue paper coated with silver nanowires (AgNWs) as a sensing material, a nanocellulose paper (NCP) as a bottom substrate for printing electrodes, and NCP as a top encapsulating layer. The APBP pressure sensor showed a high sensitivity of 1.5 kPa^-1 in the range of 0.03-30.2 kPa and retained excellent performance in the bending state. Furthermore, the APBP sensor has been mounted on the human skin to monitor physiological signals (such as arterial heart pulse and pronunciation from throat) and successfully applied as a soft electronic skin to respond to the external pressure. Due to the use of the common tissue paper, NCP, AgNWs, and conductive nanosilver ink only, the pressure sensor has advantages of low cost, facile craft, and fast preparation and can be disposed off easily by incineration. We believe that the developed sensor will propel the advancement of easily disposable pressure sensors and green paper-based flexible electronic devices.

Footstep Energy Harvesting with the Magnetostrictive Fiber Integrated Shoes

Wearable energy harvesting devices attract attention as the devices provide electrical power without inhibiting user mobility and independence. While the piezoelectric materials integrated shoes have been considered as wearable energy harvesting devices for a long time, they can lose their energy harvesting performance after being used several times due to their brittleness. In this study, we focused on Fe-Co magnetostrictive materials and fabricated Fe-Co magnetostrictive fiber integrated shoes. We revealed that Fe-Co magnetostrictive fiber integrated shoes are capable of generating 1.2 µJ from 1000 steps of usual walking by the Villari (inverse magnetostrictive) effect. It seems that the output energy is dependent on user habit on ambulation, not on their weight. From both a mechanical and functional point of view, Fe-Co magnetostrictive fiber integrated shoes demonstrated stable energy harvesting performance after being used many times. It is likely that Fe-Co magnetostrictive fiber integrated shoes are available as sustainable and wearable energy harvesting devices.

Autonomic Nervous System Response during Light Physical Activity in Adolescents with Anorexia Nervosa Measured by Wearable Devices

Anorexia nervosa (AN) is associated with a wide range of disturbances of the autonomic nervous system. The aim of the present study was to monitor the heart rate (HR) and the heart rate variability (HRV) during light physical activity in a group of adolescent girls with AN and in age-matched controls using a wearable, minimally obtrusive device. For the study, we enrolled a sample of 23 adolescents with AN and 17 controls. After performing a 12-lead electrocardiogram and echocardiography, we used a wearable device to record a one-lead electrocardiogram for 5 min at baseline for 5 min during light physical exercise (Task) and for 5 min during recovery. From the recording, we extracted HR and HRV indices. Among subjects with AN, the HR increased at task and decreased at recovery, whereas among controls it did not change between the test phases. HRV features showed a different trend between the two groups, with an increased low-to-high frequency ratio (LF/HF) in the AN group due to increased LF and decreased HF, differently from controls that, otherwise, slightly increased their standard deviation of NN intervals (SDNN) and the root mean square of successive differences (RMSSD). The response in the AN group during the task as compared to that of healthy adolescents suggests a possible sympathetic activation or parasympathetic withdrawal, differently from controls. This result could be related to the low energy availability associated to the excessive loss of fat and lean mass in subjects with AN, that could drive to autonomic imbalance even during light physical activity.

The use of wearable technology to monitor physical activity in patients with COPD: a literature review

Background: Physical activity is an important predictor for survival in patients with COPD. Wearable technology, such as pedometer or accelerometer, may offer an opportunity to quantify physical activity and evaluate related health benefits in these patients.

Objectives: To assess the performance of wearable technology in monitoring and improving physical activity in COPD patients from published studies.

Methods: Literature search of Medline, Cochrane, Dare, Embase and PubMed databases was made to find relevant articles that used wearable technology to monitor physical activity in COPD patients.

Results: We identified 13 studies that used wearable technology, a pedometer or an accelerator, to monitor physical activity in COPD patients. Of these, six studies were randomized controlled trials (RCTs) which used the monitors as part of the intervention. Two studies reported the same outcomes and comparable units. They had measured the difference that the intervention makes on the number of steps taken daily by the patients. The results were highly heterogeneous with I²=92%. The random-effects model gave an effect outcome on the number of steps taken daily of 1,821.01 [−282.71; 3,924.74] in favor of the wearable technology. Four of the 13 studies have reported technical issues with the use of the wearable technology, including high signal-to-noise ratio, memory storage problems and inaccuracy of counts. While other studies did not mention any technical issues, it is not clear whether these did not experience them or chose not to report them.

Conclusions: Our literature search has shown that data on the use of wearable technology to monitor physical activity in COPD patients are limited by the small number of studies and their heterogeneous study design. Further research and better-designed RCTs are needed to provide reliable results before physical activity monitors can be implemented routinely for COPD patients.

Accuracy of mHealth Devices for Atrial Fibrillation Screening: Systematic Review

BACKGROUND

Mobile health (mHealth) devices can be used for the diagnosis of atrial fibrillation. Early diagnosis allows better treatment and prevention of secondary diseases like stroke. Although there are many different mHealth devices to screen for atrial fibrillation, their accuracy varies due to different technological approaches.

OBJECTIVE

We aimed to systematically review available studies that assessed the accuracy of mHealth devices in screening for atrial fibrillation. The goal of this review was to provide a comprehensive overview of available technologies, specific characteristics, and accuracy of all relevant studies.

METHODS

PubMed and Web of Science databases were searched from January 2014 until January 2019. Our systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses. We restricted the search by year of publication, language, noninvasive methods, and focus on diagnosis of atrial fibrillation. Articles not including information about the accuracy of devices were excluded.

RESULTS

We found 467 relevant studies. After removing duplicates and excluding ineligible records, 22 studies were included. The accuracy of mHealth devices varied among different technologies, their application settings, and study populations. We described and summarized the eligible studies.

CONCLUSIONS

Our systematic review identifies different technologies for screening for atrial fibrillation with mHealth devices. A specific technology's suitability depends on the underlying form of atrial fibrillation to be diagnosed. With the suitable use of mHealth, early diagnosis and treatment of atrial fibrillation are possible. Successful application of mHealth technologies could contribute to significantly reducing the cost of illness of atrial fibrillation.

Ambulatory Microdose PET: A Wearable PET Scanner for Neurologic Imaging

The ambulatory microdose PET scanner is an innovative machine that is advancing the field of nuclear medicine neurologic imaging. This scanner is a wearable helmet that allows neurologic PET imaging to be done while a subject is sitting upright or ambulating. It has the potential to tell researchers and physicians more about how the brain and movement are connected and give more insight on the deeper structures. The evolving design of the helmet has grown to show improvement in image quality and the ability to image the brain with useful information on different neurologic disorders and diseases. When the ambulatory microdose PET scanner is compared with a conventional PET scanner, it not only provides higher-resolution images and increased sensitivity while allowing the patient to have a greater range of motion but also allows for the introduction of newer radiotracers and lower radiation doses.

Graphene-Based Sensors for Human Health Monitoring

Since the desire for real-time human health monitoring as well as seamless human-machine interaction is increasing rapidly, plenty of research efforts have been made to investigate wearable sensors and implantable devices in recent years. As a novel 2D material, graphene has aroused a boom in the field of sensor research around the world due to its advantages in mechanical, thermal, and electrical properties. Numerous graphene-based sensors used for human health monitoring have been reported, including wearable sensors, as well as implantable devices, which can realize the real-time measurement of body temperature, heart rate, pulse oxygenation, respiration rate, blood pressure, blood glucose, electrocardiogram signal, electromyogram signal, and electroencephalograph signal, etc. Herein, as a review of the latest graphene-based sensors for health monitoring, their novel structures, sensing mechanisms, technological innovations, components for sensor systems and potential challenges will be discussed and outlined.

Validation of two watch-type wearable blood pressure monitors according to the ANSI/AAMI/ISO81060-2:2013 guidelines: Omron HEM-6410T-ZM and HEM-6410T-ZL

There is growing evidence of the clinical significance of daytime masked hypertension (MHT) and blood pressure (BP) variability (BPV). Recently, watch-type wearable devices for self-BP measurement have become available. Such devices might be promising tools to identify patients with daytime MHT or large BPV in their real-life conditions. The present study aimed to validate the accuracy of the Omron HEM-6410T-ZM and the Omron HEM-6410T-ZL, which are automatic watch-type wearable devices for self-BP measurement, according to the American National Standards Institute, Inc/Association for the Advancement of Medical Instrumentation/International Organization for Standardization (ANSI/AAMI/ISO) 81060-2:2013 guideline. Watches were held with the wrist at heart level. The mean differences between reference BPs and HEM-6410T-ZM readings were -0.9 ± 7.6/-1.1 ± 6.1 mm Hg for systolic BP (SBP)/diastolic BP (DBP) for criterion 1, and -0.9 ± 6.8/-1.1 ± 5.5 mm Hg for SBP/DBP for criterion 2. The mean differences between reference BPs and HEM-6410T-ZL readings were 2.4 ± 7.3/0.7 ± 7.0 mm Hg for SBP/DBP for criterion 1, and 2.4 ± 6.5/0.7 ± 6.5 mm Hg for SBP/DBP for criterion 2. The Omron HEM-6410T-ZM and the Omron HEM-6410T-ZL both fulfilled both validation criteria 1 and 2 of the ANSI/AAMI/ISO 81060-2:2013 guidelines.