Wearable, battery-free, wireless multiplexed printed sensors for heat stroke prevention with mussel-inspired bio-adhesive membranes.

Wearable technologies are becoming pervasive in our society, and their development continues to accelerate the untapped potential of continuous and ubiquitous sensing, coupled with big data analysis and interpretation, has only just begun to unfold. However, existing wearable devices are still bulky (mainly due to batteries and electronics) and have suboptimal skin contact. In this work, we propose a novel approach based on a sensor network produced through inkjet printing of nanofunctional inks onto a semipermeable substrate. This network enables real-time monitoring of critical physiological parameters, including temperature, humidity, and muscle contraction. Remarkably, our system operates under battery-free and wireless near-field communication (NFC) technology for data readout via smartphones. Moreover, two of the three sensors were integrated onto a naturally adhesive bioinspired membrane. This membrane, developed using an eco-friendly, high-throughput process, draws inspiration from the remarkable adhesive properties of mussel-inspired molecules. The resulting ultra-conformable membrane adheres effortlessly to the skin, ensuring reliable and continuous data collection. The urgency of effective monitoring systems cannot be overstated, especially in the context of rising heat stroke incidents attributed to climate change and high-risk occupations. Heat stroke manifests as elevated skin temperature, lack of sweating, and seizures. Swift intervention is crucial to prevent progression to coma or fatality. Therefore, our proposed system holds immense promise for the monitoring of these parameters on the field, benefiting both the general population and high-risk workers, such as firefighters.

Unveiling wearables: exploring the global landscape of biometric applications and vital signs and behavioral impact.

The development of neuroscientific techniques enabling the recording of brain and peripheral nervous system activity has fueled research in cognitive science. Recent technological advancements offer new possibilities for inducing behavioral change, particularly through cost-effective Internet-based interventions. However, limitations in laboratory equipment volume have hindered the generalization of results to real-life contexts. The advent of Internet of Things (IoT) devices, such as wearables, equipped with sensors and microchips, has ushered in a new era in behavior change techniques. Wearables, including smartwatches, electronic tattoos, and more, are poised for massive adoption, with an expected annual growth rate of 55% over the next five years. These devices enable personalized instructions, leading to increased productivity and efficiency, particularly in industrial production. Additionally, the healthcare sector has seen a significant demand for wearables, with over 80% of global consumers willing to use them for health monitoring. This research explores the primary biometric applications of wearables and their impact on users' well-being, focusing on the integration of behavior change techniques facilitated by IoT devices. Wearables have revolutionized health monitoring by providing real-time feedback, personalized interventions, and gamification. They encourage positive behavior changes by delivering immediate feedback, tailored recommendations, and gamified experiences, leading to sustained improvements in health. Furthermore, wearables seamlessly integrate with digital platforms, enhancing their impact through social support and connectivity. However, privacy and data security concerns must be addressed to maintain users' trust. As technology continues to advance, the refinement of IoT devices' design and functionality is crucial for promoting behavior change and improving health outcomes. This study aims to investigate the effects of behavior change techniques facilitated by wearables on individuals' health outcomes and the role of wearables in promoting a healthier lifestyle.

A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being.

This research paper delves into the effectiveness and impact of behavior change techniques fostered by information technologies, particularly wearables and Internet of Things (IoT) devices, within the realms of engineering and computer science. By conducting a comprehensive review of the relevant literature sourced from the Scopus database, this study aims to elucidate the mechanisms and strategies employed by these technologies to facilitate behavior change and their potential benefits to individuals and society. Through statistical measurements and related works, our work explores the trends over a span of two decades, from 2000 to 2023, to understand the evolving landscape of behavior change techniques in wearable and IoT technologies. A specific focus is placed on a case study examining the application of behavior change techniques (BCTs) for monitoring vital signs using wearables, underscoring the relevance and urgency of further investigation in this critical intersection of technology and human behavior. The findings shed light on the promising role of wearables and IoT devices for promoting positive behavior modifications and improving individuals' overall well-being and highlighting the need for continued research and development in this area to harness the full potential of technology for societal benefit.

Validation of a sleep staging classification model for healthy adults based on two combinations of a single-channel EEG headband and wrist actigraphy.

STUDY OBJECTIVES: The aim of this study was to develop a sleep staging classification model capable of accurately performing on different wearable devices. METHODS: Twenty-three healthy participants underwent a full-night type I polysomnography and used two device combinations: (A) flexible single-channel electroencephalogram (EEG) headband + actigraphy (n = 12) and (B) rigid single-channel EEG headband + actigraphy (n = 11). The signals were segmented into 30-second epochs according to polysomnographic stages (scored by a board-certified sleep technologist; model ground truth) and 18 frequency and time features were extracted. The model consisted of an ensemble of bagged decision trees. Bagging refers to bootstrap aggregation to reduce overfitting and improve generalization. To evaluate the model, a training dataset under 5-fold cross-validation and an 80-20% dataset split was used. The headbands were also evaluated without the actigraphy feature. Participants also completed a usability evaluation (comfort, pain while sleeping, and sleep disturbance). RESULTS: Combination A had an F1-score of 98.4% and the flexible headband alone of 97.7% (error rate for N1: combination A = 9.8%; flexible headband alone = 15.7%). Combination B had an F1-score of 96.9% and the rigid headband alone of 95.3% (error rate for N1: combination B = 17.0%; rigid headband alone = 27.7%); in both, N1 was more confounded with N2. CONCLUSIONS: We developed an accurate sleep classification model based on a single-channel EEG device, and actigraphy was not an important feature of the model. Both headbands were found to be useful, with the rigid one being more disruptive to sleep. Future research can improve our results by applying the developed model in a population with sleep disorders. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: Actigraphy, Wearable EEG Band and Smartphone for Sleep Staging; URL: https://clinicaltrials.gov/study/NCT04943562; Identifier: NCT04943562. CITATION: Melo MC, Vallim JRS, Garbuio S, et al. Validation of a sleep staging classification model for healthy adults based on 2 combinations of a single-channel EEG headband and wrist actigraphy. J Clin Sleep Med. 2024;20(6):983-990.

Guidelines for the development, performance evaluation and validation of new sleep technologies (DEVSleepTech guidelines) - a protocol for a Delphi consensus study.

New sleep technologies are being developed, refined and delivered at a fast pace. However, there are serious concerns about the validation and accuracy of new sleep-related technologies being made available, as many of them, especially consumer-sleep technologies, have not been tested in comparison with gold-standard methods or have been approved by health regulatory agencies. The importance of proper validation and performance evaluation of new sleep technologies has already been discussed in previous studies and some recommendations have already been published, but most of them do not employ standardized methodology and are not able to cover all aspects of new sleep technologies. The current protocol describes the methods of a Delphi consensus study to create guidelines for the development, performance evaluation and validation of new sleep devices and technologies. The resulting recommendations are not intended to be used as a quality assessment tool to evaluate individual articles, but rather to evaluate the overall procedures, studies and experiments performed to develop, evaluate performance and validate new technologies. We hope these guidelines can be helpful for researchers who work with new sleep technologies on the appraisal of their reliability and validation, for companies who are working on the development and refinement of new sleep technologies, and by regulatory agencies to evaluate new technologies that are looking for registration, approval or inclusion on health systems.

Next-generation of smart dressings: Integrating multiplexed sensors and theranostic functions.

Non-healing wounds represent a significant burden for healthcare systems and society, giving rise to severe economic and human issues. Currently, the use of dressings and visual assessment represent the primary and standard care for wounds. Conventional dressings, like cotton gauze, provide only passive physical protection. Besides, they end up paradoxically hampering the wound-healing process by producing tissue damage and pain when removed during routine check-ups. In response to these limitations, researchers, engineers, and technologists are developing innovative dressings that incorporate advanced diagnostic and therapeutic functionalities, coined as "smart dressings". Now, the maturation of smart dressing is bringing them closer to real-life applications, leading to an exciting new generation of these devices. The next generation of smart dressings is capable of monitoring in real-time multiple biomarkers while including pro-healing capabilities in a single platform. Such multiplexed and theranostic smart dressings are expected to offer a timely biomarker-directed diagnosis of non-healing wounds while enabling rapid, automated, and personalized treatments of infection and chronicity. Herein, we provide an insightful overview of these advantageous devices, delving into the diverse spectrum of possible engineering strategies. This encompasses the use of electrochemical and optical platforms with diverse multiplexing architectures, such as multi-zone sensing arrays and multi-layered devices. Open or closed-loop theranostic mechanisms using various stimuli-responsive materials that could be internally or externally controlled are also included. Finally, a critical discussion on the main challenges and future directions of smart dressings is also offered.

Digital measures in epilepsy in low-resourced environments.

INTRODUCTION: Digital measures and digital health-care delivery have been rarely implemented in lower-and-middle-income countries (LMICs), contributing to worsening global disparities and inequities. Sustainable ways to implement and use digital approaches will help to improve time to access, management, and quality of life in persons with epilepsy, goals that remain unreachable in under-resourced communities. As under-resourced environments differ in human and economic resources, no one approach will be appropriate to all LMICs. AREAS COVERED: Digital health and tools to monitor and measure digital endpoints and metrics of quality of life will need to be developed or adapted to the specific needs of under-resourced areas. Portable technologies may partially address the urban-rural divide. Careful delineation of stakeholders and their engagement and alignment in all efforts is critically important if these initiatives are to be successfully sustained. Privacy issues, neglected in many regions globally, must be purposefully addressed. EXPERT OPINION: Epilepsy care in under-resourced environments has been limited by the lack of relevant technologies for diagnosis and treatment. Digital biomarkers, and investigative technological advances, may finally make it feasible to sustainably improve care delivery and ultimately quality of life including personalized epilepsy care.

Wearables for Stress Management: A Scoping Review.

In recent years, wearable devices have been increasingly used to monitor people's health. This has helped healthcare professionals provide timely interventions to support their patients. In this study, we investigated how wearables help people manage stress. We conducted a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) standard to address this question. We searched studies in Scopus, IEEE Explore, and Pubmed databases. We included studies reporting user evaluations of wearable-based strategies, reporting their impact on health or usability outcomes. A total of 6259 studies were identified, of which 40 met the inclusion criteria. Based on our findings, we identified that 21 studies report using commercial wearable devices; the most common are smartwatches and smart bands. Thirty-one studies report significant stress reduction using different interventions and interaction modalities. Finally, we identified that the interventions are designed with the following aims: (1) to self-regulate during stress episodes, (2) to support self-regulation therapies for long-term goals, and (3) to provide stress awareness for prevention, consisting of people's ability to recall, recognize and understand their stress.

Measurement of Physical Activity by Actigraphy in Infants and Young Children with Pulmonary Arterial Hypertension.

OBJECTIVE: To evaluate the feasibility, tolerability, and adherence with wearable actigraphy devices among infants and children with pulmonary arterial hypertension (PAH). STUDY DESIGN: This multicenter, prospective, observational study included children ages 0-6 years with and without PAH. Participants wore the ActiGraph wGT3X-BT on the hip and FitBit Inspire on the wrist during waking hours for 14 days. Steps, vector magnitude counts per minute, activity intensity, heart rate, and heart rate variability were compared between groups. RESULTS: Forty-seven participants (18 PAH, 29 control) were enrolled from 10 North American sites. PAH patients were mostly functional class II (n = 16, 89%) and treated with oral medications at the time of enrollment. The number of wear days was not significantly different between the groups (ActiGraph: 10 [95% CI: 5.5, 12.2] in PAH vs 8 [4, 12] in control, P = .20; FitBit 13 [10, 13.8] in PAH vs 12 [8, 14] in control, P = .87). Complete data were obtained in 81% of eligible ActiGraph participants and 72% of FitBit participants. PAH participants demonstrated fewer steps, lower vector magnitude counts per minute, more sedentary activity, and less intense physical activity at all levels compared with control participants. No statistically significant differences in heart rate variability were demonstrated between the 2 groups. CONCLUSIONS: Measurement of physical activity and other end points using wearable actigraphy devices was feasible in young children with PAH. Larger studies should determine associations between physical activity and disease severity in young patients with PAH to identify relevant end points for pediatric clinical trials.

Consumer sleep technology for the screening of obstructive sleep apnea and snoring: current status and a protocol for a systematic review and meta-analysis of diagnostic test accuracy.

There are concerns about the validation and accuracy of currently available consumer sleep technology for sleep-disordered breathing. The present report provides a background review of existing consumer sleep technologies and discloses the methods and procedures for a systematic review and meta-analysis of diagnostic test accuracy of these devices and apps for the detection of obstructive sleep apnea and snoring in comparison with polysomnography. The search will be performed in four databases (PubMed, Scopus, Web of Science, and the Cochrane Library). Studies will be selected in two steps, first by an analysis of abstracts followed by full-text analysis, and two independent reviewers will perform both phases. Primary outcomes include apnea-hypopnea index, respiratory disturbance index, respiratory event index, oxygen desaturation index, and snoring duration for both index and reference tests, as well as the number of true positives, false positives, true negatives, and false negatives for each threshold, as well as for epoch-by-epoch and event-by-event results, which will be considered for the calculation of surrogate measures (including sensitivity, specificity, and accuracy). Diagnostic test accuracy meta-analyses will be performed using the Chu and Cole bivariate binomial model. Mean difference meta-analysis will be performed for continuous outcomes using the DerSimonian and Laird random-effects model. Analyses will be performed independently for each outcome. Subgroup and sensitivity analyses will evaluate the effects of the types (wearables, nearables, bed sensors, smartphone applications), technologies (e.g., oximeter, microphone, arterial tonometry, accelerometer), the role of manufacturers, and the representativeness of the samples.

Wearable Inertial Sensor Approach for Postural Adjustment Assessments during Predictable Perturbations in Sport.

INTRODUCTION: Evidence supports the importance of efficient postural control to improve performance in sports. This involves the use of strategies such as anticipatory posture adjustments and compensatory adjustments. Technology makes analysis and assessments in sports cheaper, while being valid and reliable compared to the gold-standard assessment equipment. OBJECTIVES: This article aimed to test the validity and reliability of signals extracted from the sensor's accelerometer (Metamotion C), by comparing it to the data obtained from the gold-standard equipment (a three-dimensional video-motion-capture system). DESIGN: Observational, cross-sectional study. METHODS: We exposed 20 healthy young standing people to the pendulum impact paradigm, which consisted of predictable anteroposterior disturbances applied at the shoulder level. In order to measure this, we observed the acceleration of the center of mass in the anticipatory and compensatory phase of the disturbance and compared the signals of the two devices (Metamotion C and a motion-capture system). RESULTS: The validation results showed the significant linear correlation of all variables with a moderate to large correlation of r ≥ 0.5 between the devices. In contrast, the reliability results between sessions obtained by filming were all significant and above 0.75, indicating excellent reliability. The APAonset variable had a reasonable to high intra-class correlation in the anticipatory phase. In the compensatory phase, the CPAtime variable showed an excellent correlation. CONCLUSIONS: Metamotion C proved reasonably valid and highly reliable in measuring the center of mass acceleration compared to the camera system in both the anticipatory and compensatory phases.

Wearables for Engagement Detection in Learning Environments: A Review.

Appropriate teaching-learning strategies lead to student engagement during learning activities. Scientific progress and modern technology have made it possible to measure engagement in educational settings by reading and analyzing student physiological signals through sensors attached to wearables. This work is a review of current student engagement detection initiatives in the educational domain. The review highlights existing commercial and non-commercial wearables for student engagement monitoring and identifies key physiological signals involved in engagement detection. Our findings reveal that common physiological signals used to measure student engagement include heart rate, skin temperature, respiratory rate, oxygen saturation, blood pressure, and electrocardiogram (ECG) data. Similarly, stress and surprise are key features of student engagement.

Wearable Devices for Physical Monitoring of Heart: A Review.

Cardiovascular diseases (CVDs) are the leading cause of death globally. An effective strategy to mitigate the burden of CVDs has been to monitor patients' biomedical variables during daily activities with wearable technology. Nowadays, technological advance has contributed to wearables technology by reducing the size of the devices, improving the accuracy of sensing biomedical variables to be devices with relatively low energy consumption that can manage security and privacy of the patient's medical information, have adaptability to any data storage system, and have reasonable costs with regard to the traditional scheme where the patient must go to a hospital for an electrocardiogram, thus contributing a serious option in diagnosis and treatment of CVDs. In this work, we review commercial and noncommercial wearable devices used to monitor CVD biomedical variables. Our main findings revealed that commercial wearables usually include smart wristbands, patches, and smartwatches, and they generally monitor variables such as heart rate, blood oxygen saturation, and electrocardiogram data. Noncommercial wearables focus on monitoring electrocardiogram and photoplethysmography data, and they mostly include accelerometers and smartwatches for detecting atrial fibrillation and heart failure. However, using wearable devices without healthy personal habits will cause disappointing results in the patient's health.

Patient Perceptions of Wearable and Smartphone Technologies for Remote Outcome Monitoring in Patients Who Have Hip Osteoarthritis or Arthroplasties.

BACKGROUND: Although there is interest in wearables and smartphone technologies for remote outcome monitoring, little is known regarding the willingness of hip osteoarthritis (OA) and/or total hip arthroplasty (THA) patients to authorize and adhere to such treatment. METHODS: We developed an Institutional Review Board-approved questionnaire to evaluate patient perceptions of remote monitoring technologies in a high-volume orthopedic center. Forty-seven THA patients (60% female; mean age: 66 years) and 50 nonoperative OA hip patients (52% female; mean age: 63 years) participated. Patient perceptions were compared using Pearson's chi-squared analyses. RESULTS: THA patients were similarly interested in the use of smartphone apps (91% vs 94%, P = .695) in comparison to nonoperative hip OA patients. THA patients were more receptive to using wearable sensors (94% vs 44%, P < .001) relative to their nonoperative counterparts. THA patients also expressed stronger interest in learning to use custom wearables (87% vs 32%, P < .001) vs nonoperative patients. Likewise, the majority of THA patients were willing to use Global Positioning System technology (74% vs 26%, P < .001). THA patients also expressed willingness to have their body movement (89%), balance (89%), sleep (87%), and cardiac output (91%) tracked using remote technology. CONCLUSION: Overall, we found that THA patients were highly receptive to using wearable technology in their treatments. Nonoperative OA hip patients were generally unreceptive to using smart technologies, with the exception of smartphone applications. This information may be useful as utilization of these technologies for patient care continues to evolve.

HRV Monitoring Using Commercial Wearable Devices as a Health Indicator for Older Persons during the Pandemic.

Remote monitoring platforms based on advanced health sensors have the potential to become important tools during the COVID-19 pandemic, supporting the reduction in risks for affected populations such as the elderly. Current commercially available wearable devices still have limitations to deal with heart rate variability (HRV), an important health indicator of human aging. This study analyzes the role of a remote monitoring system designed to support health services to older people during the complete course of the COVID-19 pandemic in Brazil, since its beginning in Brazil in March 2020 until November 2021, based on HRV. Using different levels of analysis and data, we validated HRV parameters by comparing them with reference sensors and tools in HRV measurements. We compared the results obtained for the cardiac modulation data in time domain using samples of 10 elderly people's HRV data from Fitbit Inspire HR with the results provided by Kubios for the same population using a cardiac belt, with the data divided into train and test, where 75% of the data were used for training the models, with the remaining 25% as a test set for evaluating the final performance of the models. The results show that there is very little difference between the results obtained by the remote monitoring system compared with Kubios, indicating that the data obtained from these devices might provide accurate results in evaluating HRV in comparison with gold standard devices. We conclude that the application of the methods and techniques used and reported in this study are useful for the creation and validation of HRV indicators in time series obtained by means of wearable devices based on photoplethysmography sensors; therefore, they can be incorporated into remote monitoring processes as seen during the pandemic.

Wearables and their applications for the rehabilitation of elderly people.

Globally, there has been a change in the population pyramid with an accelerated aging process. This increase requires a greater challenge to maintain autonomy and independence. Currently, there are technologies developed with a focus on health. This is given by the development of wearables and their areas of applications. As a general context, this technology is characterized by the research field in energy generation, the development of external devices for human control and monitoring, clothing, smart textiles, and electronics. The latter are classified into three areas of application: monitoring and safety; fabrics, perception, and physical activity; and rehabilitation. A literature review is conducted to identify the state-of-the-art in these fields within the last years. The progress in monitoring systems and intelligent textiles is evidenced, being able to highlight remote feedback, materials, and wearability both at a commercial and user level. A discussion is included to address the main challenges and future trends in the application of wearables in elderly people.

Remote Healthcare for Elderly People Using Wearables: A Review.

The growth of health care spending on older adults with chronic diseases faces major concerns that require effective measures to be adopted worldwide. Among the main concerns is whether recent technological advances now offer the possibility of providing remote health care for the aging population. The benefits of suitable prevention and adequate monitoring of chronic diseases by using emerging technological paradigms such as wearable devices and the Internet of Things (IoT) can increase the detection rates of health risks to raise the quality of life for the elderly. Specifically, on the subject of remote health monitoring in older adults, a first approach is required to review devices, sensors, and wearables that serve as tools for obtaining and measuring physiological parameters in order to identify progress, limitations, and areas of opportunity in the development of health monitoring schemes. For these reasons, a review of articles on wearable devices was presented in the first instance to identify whether the selected articles addressed the needs of aged adults. Subsequently, the direct review of commercial and prototype wearable devices with the capability to read physiological parameters was presented to identify whether they are optimal or usable for health monitoring in older adults.

The use of wearable technology as an assessment tool to identify between-limb differences during functional tasks following ACL reconstruction. A scoping review.

OBJECTIVE: To report how wearable sensors have been used to identify between-limb deficits during functional tasks following ACL reconstruction and critically examine the methods used. METHODS: We performed a scoping review of studies including participants with ACL reconstruction as the primary surgical procedure, who were assessed using wearable sensors during functional movement tasks (e.g., balance, walking or running, jumping and landing) at all postsurgical time frames. RESULTS: Eleven studies met the inclusion criteria. The majority examined jumping-landing tasks and reported kinematic and kinetic differences between limbs (involved vs. unninvolved) and groups (injured vs. controls). Excellent reliability and moderate-strong agreement with laboratory protocols was indicated, with IMU sensors providing an accurate estimation of kinetics, but the number of studies and range of tasks used were limited. Methodological differences were present including, sensor placement, sampling rate, time post-surgery and type of assessment which appear to affect the outcome. CONCLUSIONS: Wearable sensors consistently identified between-limb and group deficits following ACL reconstruction. Preliminary evidence suggests these technologies could be used to monitor knee function during rehabilitation, but further research is needed including, validation against criterion measures. Practitioners should also consider how the methods used can affect the accuracy of the outcome.

Experimental Analysis of the Relationship between Textile Structure, Tensile Strength and Comfort in 3D Printed Structured Fabrics.

In this article, an experimental investigation was conducted to study the effects of 3D printed structured fabrics on the tensile strength of two additive manufacturing technologies: (i) fused deposition modeling (FDM); and (ii) stereolithography (SLA). Three types of structured fabrics were designed in a linked fabric structure, which resembled the main characteristics of a conventional textile. Through computer-aided design (CAD), the textile structures were sketched, which, in a STL format, were transferred to 3D printing software, and consequently, they were printed. The specimens were subjected to tensile tests to analyse the behaviour of the linked structures under tensile loads. The results obtained indicated that the elements structured in a linked fabric pattern showed a statistically significant effect between the design of the 3D printed structured fabric and its tensile strength. Some important properties in textiles, fabric areal density, fineness (tex) and fabric flexibility were also analysed. This study opens an important field of research on the mechanical resistance of textile structures manufactured by 3D printing, oriented for applications in wearables that have a promising future in the fields of medicine, aerospace, sports, fashion, etc.

A Review of Commercial and Non-Commercial Wearables Devices for Monitoring Motor Impairments Caused by Neurodegenerative Diseases.

Neurodegenerative diseases (NDDs) are among the 10 causes of death worldwide. The effects of NDDs, including irreversible motor impairments, have an impact not only on patients themselves but also on their families and social environments. One strategy to mitigate the pain of NDDs is to early identify and remotely monitor related motor impairments using wearable devices. Technological progress has contributed to reducing the hardware complexity of mobile devices while simultaneously improving their efficiency in terms of data collection and processing and energy consumption. However, perhaps the greatest challenges of current mobile devices are to successfully manage the security and privacy of patient medical data and maintain reasonable costs with respect to the traditional patient consultation scheme. In this work, we conclude: (1) Falls are most monitored for Parkinson's disease, while tremors predominate in epilepsy and Alzheimer's disease. These findings will provide guidance for wearable device manufacturers to strengthen areas of opportunity that need to be addressed, and (2) Of the total universe of commercial wearables devices that are available on the market, only a few have FDA approval, which means that there is a large number of devices that do not safeguard the integrity of the users who use them.