Acceptance of Digital Sports: A Study Showing the Rising Acceptance of Digital Health Activities Due to the SARS-CoV-19 Pandemic

In pandemic times, the possibilities for conventional sports activities are severely limited; many sports facilities are closed or can only be used with restrictions. To counteract this lack of health activities and social exchange, people are increasingly adopting new digital sports solutions—a behavior change that had already started with the trend towards fitness apps and activity trackers. Existing research suggests that digital solutions increase the motivation to move and stay active. This work further investigates the potentials of digital sports incorporating the dimensions gender and preference for team sports versus individual sports. The study focuses on potential users, who were mostly younger professionals and academics. The results show that the SARS-CoV-19 pandemic had a significant negative impact on sports activity, particularly on persons preferring team sports. To compensate, most participants use more digital sports than before, and there is a positive correlation between the time spent physically active during the pandemic and the increase in motivation through digital sports. Nevertheless, there is still considerable skepticism regarding the potential of digital sports solutions to increase the motivation to do sports, increase performance, or raise a sense of team spirit when done in groups.

Fatigue Monitoring Through Wearables: A State-of-the-Art Review

The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems represent highly promising solutions for fatigue monitoring as they enable continuous, long-term monitoring of biomedical signals in unattended settings, with the required comfort and non-intrusiveness. This is a p rerequisite for the development of accurate models for fatigue monitoring in real-time. However, monitoring fatigue through wearable devices imposes unique challenges. To provide an overview of the current state-of-the-art in monitoring variables associated with fatigue via wearables and to detect potential gaps and pitfalls in current knowledge, a systematic review was performed. The Scopus and PubMed databases were searched for articles published in English since 2015, having the terms "fatigue," "drowsiness," "vigilance," or "alertness" in the title, and proposing wearable device-based systems for non-invasive fatigue quantification. Of the 612 retrieved articles, 60 satisfied the inclusion criteria. Included studies were mainly of short duration and conducted in laboratory settings. In general, researchers developed fatigue models based on motion (MOT), electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), galvanic skin response (GSR), electromyogram (EMG), skin temperature (T_sk), eye movement (EYE), and respiratory (RES) data acquired by wearable devices available in the market. Supervised machine learning models, and more specifically, binary classification models, are predominant among the proposed fatigue quantification approaches. These models were considered to perform very well in detecting fatigue, however, little effort was made to ensure the use of high-quality data during model development. Together, the findings of this review reveal that methodological limitations have hindered the generalizability and real-world applicability of most of the proposed fatigue models. Considerably more work is needed to fully explore the potential of wearables for fatigue quantification as well as to better understand the relationship between fatigue and changes in physiological variables.

Accuracy and reliability of a wireless vital signs monitor for hospitalized patients in a low-resource setting

Objective

The purpose of this study was to evaluate the accuracy and reliability of neoGuard in comparison to a conventional bedside monitor on patients in a low-resource clinical setting.

Design

This was a single-arm methods comparison study involving the use of a wearable vital signs monitor (neoGuardTM) versus a conventional bedside monitor (Edan iM8).

Setting

The study was conducted at Jinja Regional Referral Hospital, a tertiary care hospital situated in Eastern Uganda.

Participants

Thirty patients (10 male, 20 female) were enrolled from the adult recovery ward at JRRH. Participants were eligible for the study if they were at least 18 years of age, had 2 sets of normal vital sign measurements obtained 1 h apart, and were able and willing to provide informed consent.

Main Outcome and Measures

The primary outcome measures were (i) bias (mean deviation) and (ii) limits of agreement [95% CI]. Bland-Altman plots were generated to illustrate the level of agreement between the neoGuardTM technology and the Edan iM8 monitor.

Results

Bland-Altman analysis was performed for 24 participants; datasets from six participants were excluded due to missing or invalid measurements. Findings showed a moderate level of agreement for measurement of SpO2, PR, and RR, with >80% of subject means falling within the predefined acceptability limits. However, there was also notable variation in accuracy between subjects, with large standard deviations observed for measurement of all four parameters. While the level of agreement for measurement of temperature was low, this is partly explained by limitations in the comparison method.

A physiological and biomechanical investigation of three passive upper-extremity exoskeletons during simulated overhead work

The objective of this study was to evaluate three passive upper-extremity exoskeletons relative to a control condition. Twelve subjects performed an hour-long, simulated occupational task in a laboratory setting. Independent measures of exoskeleton, exertion height (overhead, head height), time, and their interactions were assessed. Dependent measures included changes in tissue oxygenation (ΔTSI) in the anterior deltoid and middle trapezius, peak resultant lumbar spine loading, and subjective discomfort in various body regions. A statistically significant reduction in ΔTSI between exoskeleton and control was only observed in one instance. Additionally, neither increases in spinal loading nor increases in subjective discomfort ratings were observed for any of the exoskeletons. Ultimately, the exoskeletons offered little to no physiological benefit for the conditions tested. However, the experimental task was not highly fatiguing to the subjects, denoted by low ΔTSI values across conditions. Results may vary for tasks requiring constant arm elevation or higher force demands. Practitioner summary This study quantified the benefits of upper-extremity exoskeletons using NIRS, complementary to prior studies using EMG. The exoskeletons offered little to no physiological benefit for the conditions tested. However, the experimental task was not highly fatiguing, and results may vary for an experimental task with greater demand on the shoulders. Abbreviations: WMSD: work-related musculoskeletal disorder; EMG: electromyography; NIRS: near-infrared spectroscopy; NIR: near-infrared; Hb: haemoglobin; Mb: myoglobin; TSI: tissue saturation index; ATT: adipose tissue thickness.

Owner's Perception of Seizure Detection Devices in Idiopathic Epileptic Dogs

Accurate knowledge of seizure frequency is key to optimising treatment. New methods for detecting epileptic seizures are currently investigated in humans, which rely on changes in biomarkers, also called seizure detection devices. Critical to device development, is understanding user needs and requirements. No information on this subject has been published in veterinary medicine. Many dog health collars are currently on the market, but none has proved to be a promising seizure detector. An online survey was created and consisted of 27 open, closed, and scaled questions divided over two parts: part one focused on general questions related to signalment and seizure semiology, the second part focused specifically on the use of seizure detection devices. Two hundred and thirty-one participants caring for a dog with idiopathic epilepsy, were included in the study. Open questions were coded using descriptive coding by two of the authors independently. Data was analysed using descriptive statistics and binary logistic regression. Our results showed that the unpredictability of seizures plays a major part in the management of canine epilepsy and dog owners have a strong desire to know when a seizure occurs. Nearly all dog owners made changes in their daily life, mainly focusing on intensifying supervision. Owners believed seizure detection devices would improve their dog's seizure management, including a better accuracy of seizure frequency and the ability to administer emergency drugs more readily. Owners that were already keeping track of their dog's seizures were 4.2 times more likely to show confidence in using seizure detection devices to manage their pet's seizures, highlighting the need for better monitoring systems. Our results show that there is a receptive market for wearable technology as a new management strategy in canine epilepsy and this topic should be further explored.

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

Flexible Plasmonic Biosensors for Healthcare Monitoring: Progress and Prospects

The noble metal nanoparticle has been widely utilized as a plasmonic unit to enhance biosensors, by leveraging its electric and/or optical properties. Integrated with the "flexible" feature, it further enables opportunities in developing healthcare products in a conformal and adaptive fashion, such as wrist pulse tracers, body temperature trackers, blood glucose monitors, etc. In this work, we present a holistic review of the recent advance of flexible plasmonic biosensors for the healthcare sector. The technical spectrum broadly covers the design and selection of a flexible substrate, the process to integrate flexible and plasmonic units, the exploration of different types of flexible plasmonic biosensors to monitor human temperature, blood glucose, ions, gas, and motion indicators, as well as their applications for surface-enhanced Raman scattering (SERS) and colorimetric detections. Their fundamental working principles and structural innovations are scoped and summarized. The challenges and prospects are articulated regarding the critical importance for continued progress of flexible plasmonic biosensors to improve living quality.

Bioinspired Triboelectric Nanosensors for Self-Powered Wearable Applications

The sustainable operation of wearable sensors plays an important role in continuous and longtime health monitoring. Conventional batteries, which are bulky and rigid, do not satisfy these requirements and, rather, cause additional economic burdens and environmental problems by regular replacement of power sources. This article provides a review on an alternative solution in the form of self-powered devices that can harvest energy from the surrounding environment to support the operation of the wearable sensor. The Review starts with an introduction of the self-powered triboelectric nanosensors (TENSs) and its two independent modules: the energy harvester and the sensing module. The Review continues with the TENS-related bioinspired designs for wearable applications, while providing a bird's-eye view of their characteristics and applications. The ongoing challenges and prospects for providing personal healthcare with self-powered TENS are presented and discussed.

Wristbands in Home-Based Rehabilitation-Validation of Heart Rate Measurement

The possibility of using a smartwatch as a rehabilitation tool to monitor patients’ heart rates during exercise has gained the attention of many researchers. This study aimed to evaluate the accuracy and precision of the HR measurement performed by two wrist monitors: the Fitbit Charge 4 and the Xiaomi Mi Band 5. Thirty-one healthy volunteers were asked to perform a stress test on a treadmill. Their heart rates were recorded simultaneously by the wristbands and an electrocardiogram (ECG) at 1 min intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC), and Bland–Altman analysis were calculated to compare the precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < 0.8. The overall MAPE and LCCC of the Fitbit were 10.19% (±11.79%) and 0.753 (95% CI: 0.717–0.785), respectively. The MAPE and LCCC of the Xiaomi were 6.89% (±9.75) and 0.903 (0.886–0.917), respectively. The precision and accuracy of both devices decreased with the increased exercise intensity. The accuracy of wearable wrist-worn heart rate monitors varies and depends on the intensity of training. Therefore, the decision to use such a device as a heart rate monitor during in-home rehabilitation should be made with caution.

Bioinspired design and optimization for thin film wearable and building cooling systems

In this work, we report a paradigmatic shift in bioinspired microchannel heat exchanger design toward its integration into thin film wearable devices, thermally active surfaces in buildings, photovoltaic devices, and other thermoregulating devices whose typical cooling fluxes are below 1 kW m^-2. The transparent thermoregulation device is fabricated by bonding a thin corrugated elastomeric film to the surface of a substrate to form a microchannel water-circuit with bioinspired unit cell geometry. Inspired by the dynamic scaling of flow systems in nature, we introduce empirically derived sizing rules and a novel numerical optimization method to maximize the thermoregulation performance of the microchannel network by enhancing the uniformity of flow distribution. The optimized network design results in a 25% to 37% increase in the heat flux compared to non-optimized designs. The study demonstrates the versatility of the presented design and architecture by fabricating and testing a scaled-up numerically optimized heat exchanger device for building-scale and wearable applications.

A non-invasive wearable sensory leg neuroprosthesis: mechanical, electrical and functional validation

OBJECTIVE

Lower limb amputees suffer from a variety of functional deficits related to the absence of sensory communication between the central nervous system and the lost extremity. Indeed, they experience high risk of falls, asymmetric walking and balance, and low prosthesis embodiment, that significantly decrease their quality of life. Presently, there are no commercially available devices able to provide sensory feedback to leg amputees. Recently, some invasive solutions (i.e. requiring a surgery) have been proposed by different research groups, however a non-invasive effective alternative exploitable in everyday life is still missing.

APPROACH

To address this need we developed and tested a lightweight, non-invasive, wearable technology (NeuroLegs) providing sensory (i.e. knee angle joint and tactile) feedback to the users through electro-cutaneous stimulation. A user-friendly GUI and mobile App have been developed to easily calibrate and control the system. Standard mechanical and electrical tests were performed to assess the safety and reliability of the technology.

MAIN RESULTS

No mechanical failures, stable communication among system parts and a long-lasting battery (>23h) were demonstrated. The NeuroLegs system was then verified in terms of accuracy in measuring relevant gait parameters in healthy participants. A high temporal reliability was found when detecting stride features (important for the real-time configuration) with a correct match to the walking cadence, in all assessed walking conditions. The effectiveness of the NeuroLegs system at improving walking of three transfemoral amputees was then verified in movement laboratory tests. Increased temporal gait symmetry and augmented confidence were found. Stepping outside from the lab, Neurolegs was successfully exploited by a transfemoral amputee in CYBATHLON Global Edition 2020 in several challenging situations related to daily-living activities.

SIGNIFICANCE

Our results demonstrate that the NeuroLegs system provides the user with useful sensory information that can be successfully exploited in different walking conditions of daily life.

An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study

Background

Several app-based studies share similar characteristics of a light touch approach that recruit, enroll, and onboard via a smartphone app and attempt to minimize burden through low-friction active study tasks while emphasizing the collection of passive data with minimal human contact. However, engagement is a common challenge across these studies, reporting low retention and adherence.

Objective

This study aims to describe an alternative to a light touch digital health study that involved a participant-centric design including high friction app-based assessments, semicontinuous passive data from wearable sensors, and a digital engagement strategy centered on providing knowledge and support to participants.

Methods

The Stress and Recovery in Frontline COVID-19 Health Care Workers Study included US frontline health care workers followed between May and November 2020. The study comprised 3 main components: (1) active and passive assessments of stress and symptoms from a smartphone app, (2) objective measured assessments of acute stress from wearable sensors, and (3) a participant codriven engagement strategy that centered on providing knowledge and support to participants. The daily participant time commitment was an average of 10 to 15 minutes. Retention and adherence are described both quantitatively and qualitatively.

Results

A total of 365 participants enrolled and started the study, and 81.0% (n=297) of them completed the study for a total study duration of 4 months. Average wearable sensor use was 90.6% days of total study duration. App-based daily, weekly, and every other week surveys were completed on average 69.18%, 68.37%, and 72.86% of the time, respectively.

Conclusions

This study found evidence for the feasibility and acceptability of a participant-centric digital health study approach that involved building trust with participants and providing support through regular phone check-ins. In addition to high retention and adherence, the collection of large volumes of objective measured data alongside contextual self-reported subjective data was able to be collected, which is often missing from light touch digital health studies.

Trial Registration

ClinicalTrials.gov NCT04713111; https://clinicaltrials.gov/ct2/show/NCT04713111

The Application of Wearable Glucose Sensors in Point-of-Care Testing

Diabetes and its complications have become a worldwide concern that influences human health negatively and even leads to death. The real-time and convenient glucose detection in biofluids is urgently needed. Traditional glucose testing is detecting glucose in blood and is invasive, which cannot be continuous and results in discomfort for the users. Consequently, wearable glucose sensors toward continuous point-of-care glucose testing in biofluids have attracted great attention, and the trend of glucose testing is from invasive to non-invasive. In this review, the wearable point-of-care glucose sensors for the detection of different biofluids including blood, sweat, saliva, tears, and interstitial fluid are discussed, and the future trend of development is prospected.

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

BACKGROUND

The ubiquity of mobile phones and increasing use of wearable fitness trackers offer a wide-ranging window into people's health and well-being. There are clear advantages in using remote monitoring technologies to gain an insight into health, particularly under the shadow of the COVID-19 pandemic.

OBJECTIVE

Covid Collab is a crowdsourced study that was set up to investigate the feasibility of identifying, monitoring, and understanding the stratification of SARS-CoV-2 infection and recovery through remote monitoring technologies. Additionally, we will assess the impacts of the COVID-19 pandemic and associated social measures on people's behavior, physical health, and mental well-being.

METHODS

Participants will remotely enroll in the study through the Mass Science app to donate historic and prospective mobile phone data, fitness tracking wearable data, and regular COVID-19-related and mental health-related survey data. The data collection period will cover a continuous period (ie, both before and after any reported infections), so that comparisons to a participant's own baseline can be made. We plan to carry out analyses in several areas, which will cover symptomatology; risk factors; the machine learning-based classification of illness; and trajectories of recovery, mental well-being, and activity.

RESULTS

As of June 2021, there are over 17,000 participants-largely from the United Kingdom-and enrollment is ongoing.

CONCLUSIONS

This paper introduces a crowdsourced study that will include remotely enrolled participants to record mobile health data throughout the COVID-19 pandemic. The data collected may help researchers investigate a variety of areas, including COVID-19 progression; mental well-being during the pandemic; and the adherence of remote, digitally enrolled participants.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/32587.

Quantifying jumps and external load in netball using VERT inertial measurement units

This study assesses the relationship between an inexpensive and an established inertial measurement device for the measurement of movement and jumps in netball. Twenty-five female netballers participated in this study (11 elite and 14 sub-elite). Two inertial measurement devices (Catapult ClearSky T6 and VERT Classic) were worn simultaneously during a training session. The 'Kinetic Energy' output provided by the VERT device was compared to the total PlayerLoad collected by the ClearSky T6 device. Automated total jump counts were also compared across devices. A correlation of r = 0.76 (95% confidence interval [CI]; 0.52 to 0.89) was identified between total PlayerLoad and 'Kinetic Energy'. Similarly, a correlation of r = 0.81 (95% CI; 0.61 to 0.91) was identified for the relationship between ClearSky T6 jump count and VERT jump count. Mean bias of 1.7 jumps (95% CI; -2.5 to 5.8) with 95% limits of agreement (-17.9 to 21.3) were found when comparing the jump counts between the ClearSky T6 and VERT devices. The correlations found in this study indicate that the VERT devices may be an accessible alternative for sub-elite athletes; however, the wide confidence intervals and limits of agreement warrant caution.

The E-Textile for Biomedical Applications: A Systematic Review of Literature

The use of e-textile technologies spread out in the scientific research with several applications in both medical and nonmedical world. In particular, wearable technologies and miniature electronics devices were implemented and tested for medical research purposes. In this paper, a systematic review regarding the use of e-textile for clinical applications was conducted: the Scopus and Pubmed databases were investigate by considering research studies from 2010 to 2020. Overall, 262 papers were found, and 71 of them were included in the systematic review. Of the included studies, 63.4% focused on information and communication technology studies, while the other 36.6% focused on industrial bioengineering applications. Overall, 56.3% of the research was published as an article, while the remainder were conference papers. Papers included in the review were grouped by main aim into cardiological, muscular, physical medicine and orthopaedic, respiratory, and miscellaneous applications. The systematic review showed that there are several types of applications regarding e-textile in medicine and several devices were implemented as well; nevertheless, there is still a lack of validation studies on larger cohorts of subjects since the majority of the research only focuses on developing and testing the new device without considering a further extended validation.

A Wearable Metasurface for High Efficiency, Free-Positioning Omnidirectional Wireless Power Transfer

We introduce a design principle of metasurfaces that can form any desired distribution of magnetic field for high-efficiency wireless power transfer centered at 200 kHz, which can be used to efficiently charge implanted medical devices. This metasurface can improve the power transfer efficiency for both single-user and multi-user cases by over tenfold compared to those without the metasurface. Our design enables a robust field distribution to the positions of the transmitting and receiving coils, as well as the geometric distortions of the metasurface itself, demonstrating feasibilities as a wearable device. With our design, the field distribution and subsequent power division among the multiple users can be readily controlled from equal distribution to any selective user(s). When incorporating a three-dimensional unit cell of the metasurface, we theoretically demonstrate an omnidirectional control of the field orientation to achieve a high-efficiency wireless power transfer for multiple users.

A Flexible Metamaterial Based Printed Antenna for Wearable Biomedical Applications

This paper presents a microstrip antenna based on metamaterials (MTM). The proposed antenna showed several resonances around the BAN and ISM frequency bands. The antenna showed a suitable gain for short and medium wireless communication systems of about 1 dBi, 1.24 dBi, 1.48 dBi, 2.05 dBi, and 4.11 dBi at 403 MHz, 433 MH, 611 Mz, 912 MHz, and 2.45 GHz, respectively. The antenna was printed using silver nanoparticle ink on a polymer substrate. The antenna size was reduced to 20 × 10 mm² to suit the different miniaturized wireless biomedical devices. The fabricated prototype was tested experimentally on the human body. The main novelty with this design is its ability to suppress the surface wave from the patch edges, significantly reducing the back radiation toward the human body when used close to it. The antenna was located on the human head to specify the specific absorption rate (SAR). It was found in all cases that the proposed antenna showed low SAR effects on the human body.

Design of a Novel Wearable System for Foot Clearance Estimation

Trip-related falls are one of the major causes of injury among seniors in Canada and can be attributable to an inadequate Minimum Toe Clearance (MTC). Currently, motion capture systems are the gold standard for measuring MTC; however, they are expensive and have a restricted operating area. In this paper, a novel wearable system is proposed that can estimate different foot clearance parameters accurately using only two Time-of-Flight (ToF) sensors located at the toe and heel of the shoe. A small-scale preliminary study was conducted to investigate the feasibility of foot clearance estimation using the proposed wearable system. We recruited ten young, healthy females to walk at three self-selected speeds (normal, slow, and fast) while wearing the system. Our data analysis showed an average correlation coefficient of 0.94, 0.94, 0.92 for the normal, slow, and fast speed, respectively, when comparing the ToF signals with motion capture. The ANOVA analysis confirmed these results further by revealing no statistically significant differences between the ToF signals and motion capture data for most of the gait parameters after applying the newly proposed foot angle and offset compensation. In addition, the proposed system can measure the MTC with an average Mean Error (ME) of −0.08 ± 3.69 mm, −0.12 ± 4.25 mm, and −0.10 ± 6.57 mm for normal, slow, and fast walking speeds, respectively. The proposed affordable wearable system has the potential to perform real-time MTC estimation and contribute to future work focused on minimizing tripping risks.

Remote Monitoring of the Performance Status and Burden of Symptoms of Patients With Gastrointestinal Cancer Via a Consumer-Based Activity Tracker: Quantitative Cohort Study

BACKGROUND

The number of older patients with gastrointestinal cancer is increasing due to an aging global population. Minimizing reliance on an in-clinic patient performance status test to determine a patient's prognosis and course of treatment can improve resource utilization. Further, current performance status measurements cannot capture patients' constant changes. These measurements also rely on self-reports, which are subjective and subject to bias. Real-time monitoring of patients' activities may allow for a more accurate assessment of patients' performance status while minimizing resource utilization.

OBJECTIVE

This study investigates the validity of consumer-based activity trackers for monitoring the performance status of patients with gastrointestinal cancer.

METHODS

A total of 27 consenting patients (63% male, median age 58 years) wore a consumer-based activity tracker 7 days before chemotherapy and 14 days after receiving their first treatment. The provider assessed patients using the Eastern Cooperative Oncology Group Performance Status (ECOG-PS) scale and Memorial Symptom Assessment Scale-Short Form (MSAS-SF) before and after chemotherapy visits. The statistical correlations between ECOG-PS and MSAS-SF scores and patients' daily step counts were assessed.

RESULTS

The daily step counts yielded the highest correlation with the patients' ECOG-PS scores after chemotherapy (P<.001). The patients with higher ECOG-PS scores experienced a higher fluctuation in their step counts. The patients who walked more prechemotherapy (mean 6071 steps per day) and postchemotherapy (mean 5930 steps per day) had a lower MSAS-SF score (lower burden of symptoms) compared to patients who walked less prechemotherapy (mean 5205 steps per day) and postchemotherapy (mean 4437 steps per day).

CONCLUSIONS

This study demonstrates the feasibility of using inexpensive, consumer-based activity trackers for the remote monitoring of performance status in the gastrointestinal cancer population. The findings need to be validated in a larger population for generalizability.

Tourist Experiences Recommender System Based on Emotion Recognition with Wearable Data

The collection of physiological data from people has been facilitated due to the mass use of cheap wearable devices. Although the accuracy is low compared to specialized healthcare devices, these can be widely applied in other contexts. This study proposes the architecture for a tourist experiences recommender system (TERS) based on the user's emotional states who wear these devices. The issue lies in detecting emotion from Heart Rate (HR) measurements obtained from these wearables. Unlike most state-of-the-art studies, which have elicited emotions in controlled experiments and with high-accuracy sensors, this research's challenge consisted of emotion recognition (ER) in the daily life context of users based on the gathering of HR data. Furthermore, an objective was to generate the tourist recommendation considering the emotional state of the device wearer. The method used comprises three main phases: The first was the collection of HR measurements and labeling emotions through mobile applications. The second was emotional detection using deep learning algorithms. The final phase was the design and validation of the TERS-ER. In this way, a dataset of HR measurements labeled with emotions was obtained as results. Among the different algorithms tested for ER, the hybrid model of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks had promising results. Moreover, concerning TERS, Collaborative Filtering (CF) using CNN showed better performance.

Lifestyle Modification Using a Wearable Biometric Ring and Guided Feedback Improve Sleep and Exercise Behaviors: A 12-Month Randomized, Placebo-Controlled Study

Purpose: Wearable biometric monitoring devices (WBMD) show promise as a cutting edge means to improve health and prevent disease through increasing accountability. By regularly providing real-time quantitative data regarding activity, sleep quality, and recovery, users may become more aware of the impact that their lifestyle has on their health. The purpose of this study was to examine the efficacy of a biometric tracking ring on improving sleep quality and increasing physical fitness over a one-year period. Methods: Fifty-six participants received a biometric tracking ring and were placed in one of two groups. One group received a 3-month interactive behavioral modification intervention (INT) that was delivered virtually via a smartphone app with guided text message feedback (GTF). The other received a 3-month non-directive wellness education control (CON). After three months, the INT group was divided into a long-term feedback group (LT-GTF) that continued to receive GTF for another nine months or short-term feedback group (ST-GTF) that stopped receiving GTF. Weight, body composition, and VO2max were assessed at baseline, 3months, and 12months for all participants and additionally at 6 and 9months for the ST-GTF and LT-GTF groups. To establish baseline measurements, sleep and physical activity data were collected daily over a 30-day period. Daily measurements were also conducted throughout the 12-month duration of the study. Results: Over the first 3months, the INT group had significant (p<0.001) improvements in sleep onset latency, daily step count, % time jogging, VO2max, body fat percentage, and heart rate variability (rMSSD HRV) compared to the CON group. Over the next 9months, the LT-GTF group continued to improve significantly (p<0.001) in sleep onset latency, daily step count, % time jogging, VO2max, and rMSSD HRV. The ST-GTF group neither improved nor regressed over the latter 9months except for a small increase in sleep latency. Conclusion: Using a WBMD concomitantly with personalized education, encouragement, and feedback, elicits greater change than using a WBMD alone. Additionally, the improvements achieved from a short duration of personalized coaching are largely maintained with the continued use of a WBMD.

Objective Measurements of Physical Activity and Sedentary Behavior Using Wearable Devices in Patients With Axial Spondyloarthritis: Protocol for a Systematic Review

Background

Axial spondyloarthritis (axSpA) is a subgroup of inflammatory rheumatic diseases. Practicing regular exercise is critical to manage pain and stiffness, reduce disease activity, and improve physical functioning, spinal mobility, and cardiorespiratory function. Accordingly, monitoring physical activity and sedentary behavior in patients with axSpA is relevant for clinical outcomes and disease management.

Objective

This review aims to determine which wearable devices, assessment methods, and associated metrics are commonly used to quantify physical activity or sedentary behavior in patients with axSpA.

Methods

The PubMed, Physiotherapy Evidence Database (PEDro), and Cochrane electronic databases will be searched, with no limit on publication date, to identify all the studies matching the inclusion criteria. Only original English-language articles published in a peer-reviewed journal will be included. The search strategy will include a combination of keywords related to the study population, wearable devices, physical activity, and sedentary behavior. We will use the Boolean operators “AND” and “OR” to combine keywords as well as Medical Subject Headings terms.

Results

Search strategy was completed in June 2020 with 23 records obtained. Data extraction and synthesis are currently ongoing. Dissemination of study results in peer-reviewed journals is expected at the end of 2021.

Conclusions

This review will provide a comprehensive and detailed synthesis of published studies that examine the use of wearable devices for objective assessment of physical activity and sedentary behavior in patients with axSpA.

Trial Registration

PROSPERO CRD42020182398; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=182398

International Registered Report Identifier (IRRID)

PRR1-10.2196/23359

Impact of the COVID-19 Pandemic on Objectively Measured Physical Activity and Sedentary Behavior Among Overweight Young Adults: Yearlong Longitudinal Analysis

BACKGROUND

The COVID-19 pandemic has impacted multiple aspects of daily living, including behaviors associated with occupation, transportation, and health. It is unclear how these changes to daily living have impacted physical activity and sedentary behavior.

OBJECTIVE

In this study, we add to the growing body of research on the health impact of the COVID-19 pandemic by examining longitudinal changes in objectively measured daily physical activity and sedentary behavior among overweight or obese young adults participating in an ongoing weight loss trial in San Diego, California.

METHODS

Data were collected from 315 overweight or obese (BMI: range 25.0-39.9 kg/m²) participants aged from 18 to 35 years between November 1, 2019, and October 30, 2020, by using the Fitbit Charge 3 (Fitbit LLC). After conducting strict filtering to find valid data on consistent wear (>10 hours per day for ≥250 days), data from 97 participants were analyzed to detect multiple structural changes in time series of physical activity and sedentary behavior. An algorithm was designed to detect multiple structural changes. This allowed for the automatic identification and dating of these changes in linear regression models with CIs. The number of breakpoints in regression models was estimated by using the Bayesian information criterion and residual sum of squares; the optimal segmentation corresponded to the lowest Bayesian information criterion and residual sum of squares. To quantify the changes in each outcome during the periods identified, linear mixed effects analyses were conducted. In terms of key demographic characteristics, the 97 participants included in our analyses did not differ from the 210 participants who were excluded.

RESULTS

After the initiation of the shelter-in-place order in California on March 19, 2021, there were significant decreases in step counts (-2872 steps per day; 95% CI -2734 to -3010), light physical activity times (-41.9 minutes; 95% CI -39.5 to -44.3), and moderate-to-vigorous physical activity times (-12.2 minutes; 95% CI -10.6 to -13.8), as well as significant increases in sedentary behavior times (+52.8 minutes; 95% CI 47.0-58.5). The decreases were greater than the expected declines observed during winter holidays, and as of October 30, 2020, they have not returned to the levels observed prior to the initiation of shelter-in-place orders.

CONCLUSIONS

Among overweight or obese young adults, physical activity times decreased and sedentary behavior times increased concurrently with the implementation of COVID-19 mitigation strategies. The health conditions associated with a sedentary lifestyle may be additional, unintended results of the COVID-19 pandemic.

Graphene-Based Multifunctional Textile for Sensing and Actuating

Textiles are materials that are extensively used in everyday life; textile-based sensors can, therefore, be regarded as ideal devices for a health monitor. However, previously reported textile sensors have limited prospects due to their single function or incompatibility. Traditional textile sensors generally focus on signal detection, which has not been able to be combined with an actuator to provide real-time health status feedback. Thus, to date, there are no well-established health monitoring systems based on intelligent textiles. Herein, we present a wearable batch-prepared graphene-based textile based on laser-scribing and thermal-transfer technology. Integrated with four functions of strain sensing, pressure sensing, physiological electrical sensing, and sound emitting, the GT is able to detect human body signals and transduce them to sound signals when the user is in an abnormal physical state. Moreover, the GT has high linearity for both strain and pressure sensing; the coefficients of determination exceed 99.3% and 98.2%, respectively. The performance of the device remains stable up to a pressure of 1000 kPa. The response time of the GT possession reaches as low as 85 ms at 4.2 Pa pressure. Therefore, due to their diversified functions and good performance, the research on GT is expected to extend to the fields of health monitoring, sports monitoring, and so forth.