Wearable Health Devices in Health Care: Narrative Systematic Review

Digital health in pharmacy education: Elective practical course integrating wearable devices and their generated health data

The widespread adoption of wearable devices (wearables) for monitoring vital signs, including blood pressure and glucose levels, has experienced a considerable surge in recent times. This surge has led to the generation of a substantial amount of health data, accessible to pharmacists during patient consultations as the healthcare sector advances in digitalization. To enhance the digital competencies of future pharmacists required by the rapidly changing digital health landscape, the Institute of Clinical Pharmacy and Pharmacotherapy, Heinrich Heine University (HHU) Duesseldorf has developed an innovative elective practical course aimed to bolster pharmacy students' competencies in handling wearables and the health data generated. The three-week practical elective course employed wearables FreeStyle Libre® 3 (Continuous Glucose Monitoring, CGM) and Aktiia (Cuffless Blood Pressure Monitoring). The hands-on activities allowed participants to obtain and interpret wearable-generated health-related data and acquainted them with simulated patient cases. Final-year pharmacy students' subjective assessments before and after the course depicted the increased knowledge and competence regarding analysing wearables data.

Correlation between psychological traits and the use of smart medical services in young and middle-aged adults: An observational study

BACKGROUND

Psychological problems affect economic development. However, there is a huge gap between mental health service resources and mental health service needs. Existing mental health service technology and platforms cannot meet all the diverse mental health needs of people. Smart medicine is a new medical system based online that can effectively improve the quality and efficiency of medical services and make mental health services accessible.

AIM

To explore the level of intelligent medical use among young and middle-aged people and its correlation with psychological factors.

METHODS

Convenience sampling was used to select 200 young and middle-aged patients with medical experience at the Third People's Hospital of Chengdu between January 2022 and January 2023 as the research subjects. The general condition Questionnaire, Eysenck Personality Questionnaire, Symptom Checklist-90, General Health Questionnaire, and Smart Medical Service Use Intention Questionnaire were used to collect data. Pearson’s correlation was used to analyze the correlation between the participants’ willingness to use smart medical services and their personality characteristics, psychological symptoms, and mental health.

RESULTS

The results revealed that the mental health of young and middle-aged people was poor, and some had psychological problems such as anxiety, depression, and physical discomfort. Familiarity, acceptance, and usage of smart healthcare in this population are at a medium level, and these levels correlate with psychological characteristics. Acceptance was positively correlated with E, and negatively correlated with P, anxiety, fear, anxiety/insomnia, and social dysfunction. The degree of use was negatively correlated with P, obsessive-compulsive symptoms, depression, anxiety, hostility, paranoia, and somatic symptoms.

CONCLUSION

The familiarity, acceptance, and usage of smart medical services among the middle-aged and young groups are related to various psychological characteristics.

Study of Postacute Sequelae of COVID-19 Using Digital Wearables: Protocol for a Prospective Longitudinal Observational Study

BACKGROUND

Postacute sequelae of COVID-19 (PASC) remain understudied in nonhospitalized patients. Digital wearables allow for a continuous collection of physiological parameters such as respiratory rate and oxygen saturation that have been predictive of disease trajectories in hospitalized patients.

OBJECTIVE

This protocol outlines the design and procedures of a prospective, longitudinal, observational study of PASC that aims to identify wearables-collected physiological parameters that are associated with PASC in patients with a positive diagnosis.

METHODS

This is a single-arm, prospective, observational study of a cohort of 550 patients, aged 18 to 65 years, male or female, who own a smartphone or a tablet that meets predetermined Bluetooth version and operating system requirements, speak English, and provide documentation of a positive COVID-19 test issued by a health care professional within 5 days before enrollment. The primary end point is long COVID-19, defined as ≥1 symptom at 3 weeks beyond the first symptom onset or positive diagnosis, whichever comes first. The secondary end point is chronic COVID-19, defined as ≥1 symptom at 12 weeks beyond the first symptom onset or positive diagnosis. Participants must be willing and able to consent to participate in the study and adhere to study procedures for 6 months.

RESULTS

The first patient was enrolled in October 2021. The estimated year for publishing the study results is 2025.

CONCLUSIONS

This is a fully decentralized study investigating PASC using wearable devices to collect physiological parameters and patient-reported outcomes. The study will shed light on the duration and symptom manifestation of PASC in nonhospitalized patient subgroups and is an exemplar of the use of wearables as population-level monitoring health tools for communicable diseases.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04927442; https://clinicaltrials.gov/study/NCT04927442.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/57382.

Use of activity trackers to improve blood pressure in young people at risk for cardiovascular disease: a pilot randomized controlled trial

BACKGROUND

Promoting physical activity among young individuals with cardiovascular disease (CVD) risk factors such as hypertension, diabetes, or chronic kidney disease can lower systolic blood pressure (BP). We sought to determine whether a 6-month intervention using a physical activity tracker was feasible and effective, compared with usual care.

METHODS

Participants were recruited at a single academic medical center. Those aged 8-30 years were randomized in a 2:1 ratio to either the intervention (use of a Fitbit physical activity tracker coupled with feedback regarding the participant's step count) or usual care. The primary feasibility outcomes were screening-to-enrollment ratio and 6-month retention rates; the primary clinical outcome was a change in systolic BP from 0-6 months.

RESULTS

Sixty-three participants were enrolled (57% male; mean age: 18 ± 4 years). The screening-to-enrollment ratio was 1.8:1. Six-month retention was 62% in the intervention group and 86% in the control group (p = 0.08). Mean change in systolic BP in the intervention group was not significantly different from the control group at 6 months (- 2.3 mmHg; 95% CI - 6.5, 1.8 vs. 3.0 mmHg; 95% CI - 2.5, 8.4, respectively, p = 0.12).

CONCLUSIONS

Among children and young adults at elevated CVD risk, the use of a physical activity tracker coupled with tailored feedback regarding their step count progress was feasible but not sustained over time. Physical activity tracker use did not have a statistically significant effect on BP after 6 months. Augmented strategies to mitigate risk in young patients at high risk for early-onset CVD should be explored. This trial is registered at ClinicalTrials.gov (NCT03325426).

QRS detection in single-lead, telehealth electrocardiogram signals: Benchmarking open-source algorithms

BACKGROUND AND OBJECTIVES

A key step in electrocardiogram (ECG) analysis is the detection of QRS complexes, particularly for arrhythmia detection. Telehealth ECGs present a new challenge for automated analysis as they are noisier than traditional clinical ECGs. The aim of this study was to identify the best-performing open-source QRS detector for use with telehealth ECGs.

METHODS

The performance of 18 open-source QRS detectors was assessed on six datasets. These included four datasets of ECGs collected under supervision, and two datasets of telehealth ECGs collected without clinical supervision. The telehealth ECGs, consisting of single-lead ECGs recorded between the hands, included a novel dataset of 479 ECGs collected in the SAFER study of screening for atrial fibrillation (AF). Performance was assessed against manual annotations.

RESULTS

A total of 12 QRS detectors performed well on ECGs collected under clinical supervision (F1 score ≥0.96). However, fewer performed well on telehealth ECGs: five performed well on the TELE ECG Database; six performed well on high-quality SAFER data; and performance was poorer on low-quality SAFER data (three QRS detectors achieved F1 of 0.78-0.84). The presence of AF had little impact on performance.

CONCLUSIONS

The Neurokit and University of New South Wales QRS detectors performed best in this study. These performed sufficiently well on high-quality telehealth ECGs, but not on low-quality ECGs. This demonstrates the need to handle low-quality ECGs appropriately to ensure only ECGs which can be accurately analysed are used for clinical decision making.

Using Wearable Technologies to Monitor Physical Activity and Exercise in Patients: A Narrative Review

ABSTRACT

With an increasing prevalence of sedentary lifestyles driving a prominent public health crisis, digital health tools such as wearable technologies are revolutionizing clinicians' ability to track physical activity and exercise. Despite their ubiquity in the consumer market, these technologies have not yet been fully incorporated into clinical practice. Though these tools promise efficacy and accessibility, a careful review of the current literature is important to understand the challenges and future promise of clinical implementation. Important considerations of implementation include health maintenance and disease prevention, ease of use by patients and providers, incorporation into the electronic health record, cost considerations, safety, privacy, and ethical considerations. This narrative review describes the recent literature on the implementation of wearable technologies in the prescription of physical activity and exercise. Application of these technologies is promising for this field's future.

Patterns of Ownership and Usage of Wearable Devices in the United States, 2020-2022: Survey Study

BACKGROUND

Although wearable technology has become increasingly common, comprehensive studies examining its ownership across different sociodemographic groups are limited.

OBJECTIVE

The aims of this study were to (1) measure wearable device ownership by sociodemographic characteristics in a cohort of US consumers and (2) investigate how these devices are acquired and used for health-related purposes.

METHODS

Data from the Rock Health Digital Health Consumer Adoption Survey collected from 2020 to 2022 with 23,974 US participants were analyzed. The sample was US Census-matched for demographics, including age, race/ethnicity, gender, and income. The relationship between sociodemographic factors and wearable ownership was explored using descriptive analysis and multivariate logistic regression.

RESULTS

Of the 23,974 respondents, 10,679 (44.5%) owned wearables. Ownership was higher among younger individuals, those with higher incomes and education levels, and respondents living in urban areas. Compared to those aged 18-24 years, respondents 65 years and older had significantly lower odds of wearable ownership (odds ratio [OR] 0.18, 95% CI 0.16-0.21). Higher annual income (≥US $200,000; OR 2.27, 95% CI 2.01-2.57) and advanced degrees (OR 2.23, 95% CI 2.01-2.48) were strong predictors of ownership. Living in rural areas reduced ownership odds (OR 0.65, 95% CI 0.60-0.72). There was a notable difference in ownership based on gender and health insurance status. Women had slightly higher ownership odds than men (OR 1.10, 95% CI 1.04-1.17). Private insurance increased ownership odds (OR 1.28, 95% CI 1.17-1.40), whereas being uninsured (OR 0.41, 95% CI 0.36-0.47) or on Medicaid (OR 0.75, 95% CI 0.68-0.82) decreased the odds of ownership. Interestingly, minority groups such as non-Hispanic Black (OR 1.14, 95% CI 1.03-1.25) and Hispanic/Latine (OR 1.20, 95% CI 1.10-1.31) respondents showed slightly higher ownership odds than other racial/ethnic groups.

CONCLUSIONS

Our findings suggest that despite overall growth in wearable ownership, sociodemographic divides persist. The data indicate a need for equitable access strategies as wearables become integral to clinical and public health domains.

Automated Detection of In-Home Activities with Ultra-Wideband Sensors

As Canada's population of older adults rises, the need for aging-in-place solutions is growing due to the declining quality of long-term-care homes and long wait times. While the current standards include questionnaire-based assessments for monitoring activities of daily living (ADLs), there is an urgent need for advanced indoor localization technologies that ensure privacy. This study explores the use of Ultra-Wideband (UWB) technology for activity recognition in a mock condo in the Glenrose Rehabilitation Hospital. UWB systems with built-in Inertial Measurement Unit (IMU) sensors were tested, using anchors set up across the condo and a tag worn by patients. We tested various UWB setups, changed the number of anchors, and varied the tag placement (on the wrist or chest). Wrist-worn tags consistently outperformed chest-worn tags, and the nine-anchor configuration yielded the highest accuracy. Machine learning models were developed to classify activities based on UWB and IMU data. Models that included positional data significantly outperformed those that did not. The Random Forest model with a 4 s data window achieved an accuracy of 94%, compared to 79.2% when positional data were excluded. These findings demonstrate that incorporating positional data with IMU sensors is a promising method for effective remote patient monitoring.

Research on the Human Motion Recognition Method Based on Wearable

The accurate analysis of human dynamic behavior is very important for overcoming the limitations of movement diversity and behavioral adaptability. In this paper, a wearable device-based human dynamic behavior recognition method is proposed. The method collects acceleration and angular velocity data through a six-axis sensor to identify information containing specific behavior characteristics in a time series. A human movement data acquisition platform, the DMP attitude solution algorithm, and the threshold algorithm are used for processing. In this experiment, ten volunteers wore wearable sensors on their bilateral forearms, upper arms, thighs, calves, and waist, and movement data for standing, walking, and jumping were collected in school corridors and laboratory environments to verify the effectiveness of this wearable human movement recognition method. The results show that the recognition accuracy for standing, walking, and jumping reaches 98.33%, 96.67%, and 94.60%, respectively, and the average recognition rate is 96.53%. Compared with similar methods, this method not only improves the recognition accuracy but also simplifies the recognition algorithm and effectively saves computing resources. This research is expected to provide a new perspective for the recognition of human dynamic behavior and promote the wider application of wearable technology in the field of daily living assistance and health management.

Digital solutions and health sciences

Digitalization is the conversion of analog data and information to a digital format based on bits. Digitalization allows information to be managed in a simple and standardized way. Digital health solutions are technologies that use the digitalization of data and information to improve the health sector in various aspects, such as prevention, diagnosis, treatment, monitoring, research, innovation, training, management and evaluation of health services. These technologies range from mobile applications and telemedicine to artificial intelligence and blockchain, with advantages, barriers, and risks for their application in health care.

Use of Smart Glasses (Assisted Reality) for Western Australian X-ray Operators' Continuing Professional Development: A Pilot Study

Previous studies have explored use of smart glasses in telemedicine, but no study has investigated its use in teleradiography. The purpose of this study was to implement a six-month pilot program for Western Australian X-ray operators (XROs) to use smart glasses to obtain assisted reality support in their radiography practice from their supervising radiographers, and evaluate its effectiveness in terms of XROs' competence improvement and equipment usability. Pretest-posttest design with evaluation of the XROs' competence (including their X-ray image quality) and smart glasses usability by XROs in two remote centers and their supervising radiographers from two sites before and after the program using four questionnaire sets and X-ray image quality review was employed in this experimental study. Paired t-test was used for comparing mean values of the pre- and post-intervention pairs of 11-point scale questionnaire and image quality review items to determine any XROs' radiography competence improvements. Content analysis was used to analyze open questions about the equipment usability. Our study's findings based on 13 participants (11 XROs and 2 supervising radiographers) and 2053 X-ray images show that the assisted reality support helped to improve the XROs' radiography competence (specifically X-ray image quality), with mean post-intervention competence values of 6.16-7.39 (out of 10) and statistical significances (p < 0.001-0.05), and the equipment was considered effective for this purpose but not easy to use.

Wearable Devices in Colorectal Surgery: A Scoping Review

Wearable devices are increasingly utilised to monitor patients perioperatively, allowing for continuous data collection and early complication detection. There is considerable variability in the types and usage settings of wearables, particularly within colorectal surgery. To address this, a scoping review was conducted to investigate current utilisation of wearable devices in colorectal surgery. A systematic search across MEDLINE and Embase was conducted following PRISMA Scoping Review guidelines. Results were synthesised narratively, categorised by perioperative phase (preoperative; postoperative; combination), and supplemented with descriptive statistics and tables. Out of 1525 studies initially identified, 20 were included, reporting data on 10 different wearable devices. Use of wearable devices varied across settings with those used preoperatively tending to focus on baseline physical status or prehabilitation, while postoperative use centred around monitoring and identification of complications. Wearable devices can enhance perioperative monitoring, enable proactive interventions, and promote personalised care for improved patient outcomes in colorectal surgery.

Effects of Peer- or Professional-Led Support in Enhancing Adherence to Wearable Monitoring Devices Among Community-Dwelling Older Adults: Systematic Review of Randomized Controlled Trials

BACKGROUND

Despite the well-documented health benefits associated with wearable monitoring devices (WMDs), adherence among community-dwelling older adults remains low. By providing guidance on the purpose and benefits of using WMDs, facilitating goal-setting aligned with the device's features, promoting comprehension of the health data captured by the device, and assisting in overcoming technological challenges, peers and health care professionals can potentially enhance older adults' adherence to WMDs. However, the effectiveness of such support mechanisms in promoting adherence to WMDs among older adults remains poorly understood.

OBJECTIVE

The aims of this systematic review were to examine the effects of peer- or professional-led intervention programs designed to improve adherence to WMDs among community-dwelling older adults and to identify the intervention components that may positively influence the effects of the intervention.

METHODS

We conducted a comprehensive search across 7 electronic databases (Cochrane Central Register of Controlled Trials [CENTRAL], PubMed, EMBASE, PsycINFO, British Nursing Index, Web of Science, and CINAHL) to identify articles published between January 1, 2010, and June 26, 2023. We specifically targeted randomized controlled trials that examined the impact of peer- or professional-led interventions on enhancing adherence to WMDs among individuals aged 60 years and older residing in the community. Two independent reviewers extracted data from the included studies and assessed the potential risk of bias in accordance with the Cochrane Risk of Bias tool for randomized trials, version 2.

RESULTS

A total of 10,511 studies were identified through the database search. Eventually, we included 3 randomized controlled trials involving 154 community-dwelling older adults. The participants had a mean age of 65 years. Our review revealed that increasing awareness of being monitored and implementing the SystemCHANGE approach, a habit change tool focusing on personal goals and feedback, were effective strategies for enhancing adherence to WMDs among older adults. All of the included studies exhibited a low risk of bias.

CONCLUSIONS

By collaboratively designing specific goals related to WMDs with health care professionals, including nurses and physicians, older adults exhibited a higher likelihood of adhering to the prescribed use of WMDs. These goal-setting tools provided a framework for structure and motivation, facilitating the seamless integration of WMDs into their daily routines. Researchers should prioritize interventions that target awareness and goal-setting as effective approaches to enhance adherence to WMDs among older adults, thereby maximizing the realization of associated health benefits.

From wearable sensor data to digital biomarker development: ten lessons learned and a framework proposal

Wearable sensor technologies are becoming increasingly relevant in health research, particularly in the context of chronic disease management. They generate real-time health data that can be translated into digital biomarkers, which can provide insights into our health and well-being. Scientific methods to collect, interpret, analyze, and translate health data from wearables to digital biomarkers vary, and systematic approaches to guide these processes are currently lacking. This paper is based on an observational, longitudinal cohort study, BarKA-MS, which collected wearable sensor data on the physical rehabilitation of people living with multiple sclerosis (MS). Based on our experience with BarKA-MS, we provide and discuss ten lessons we learned in relation to digital biomarker development across key study phases. We then summarize these lessons into a guiding framework (DACIA) that aims to informs the use of wearable sensor data for digital biomarker development and chronic disease management for future research and teaching.

Study Protocol for the Artificial Intelligence-Driven Evaluation of Structural Heart Diseases Using Wearable Electrocardiogram (ID-SHD)

Introduction

Portable devices capable of electrocardiogram (ECG) acquisition have the potential to enhance structural heart disease (SHD) management by enabling early detection through artificial intelligence-ECG (AI-ECG) algorithms. However, the performance of these AI algorithms for identifying SHD in a real-world screening setting is unknown. To address this gap, we aim to evaluate the validity of our wearable-adapted AI algorithm, which has been previously developed and validated for detecting SHD from single-lead portable ECGs in patients undergoing routine echocardiograms in the Yale New Haven Hospital (YNHH).

Research Methods and Analysis

This is the protocol for a cross-sectional study in the echocardiographic laboratories of YNHH. The study will enroll 585 patients referred for outpatient transthoracic echocardiogram (TTE) as part of their routine clinical care. Patients expressing interest in participating in the study will undergo a screening interview, followed by enrollment upon meeting eligibility criteria and providing informed consent. During their routine visit, patients will undergo a 1-lead ECG with two devices - one with an Apple Watch and the second with another portable 1-lead ECG device. With participant consent, these 1-lead ECG data will be linked to participant demographic and clinical data recorded in the YNHH electronic health records (EHR). The study will assess the performance of the AI-ECG algorithm in identifying SHD, including left ventricular systolic dysfunction (LVSD), valvular disease and severe left ventricular hypertrophy (LVH), by comparing the algorithm's results with data obtained from TTE, which is the established gold standard for diagnosing SHD.

Ethics and Dissemination

All patient EHR data required for assessing eligibility and conducting the AI-ECG will be accessed through secure servers approved for protected health information. Data will be maintained on secure, encrypted servers for a minimum of five years after the publication of our findings in a peer-reviewed journal, and any unanticipated adverse events or risks will be reported by the principal investigator to the Yale Institutional Review Board, which has reviewed and approved this protocol (Protocol Number: 2000035532).

Wearable monitoring device based on an internet management platform improves metabolic parameters in type 2 diabetes patients: a prospective pilot study

OBJECTIVES

This pilot study aimed to prospectively investigate the effects of a wearable monitoring device, based on an Internet management platform, on the comprehensive management of type 2 diabetes mellitus (T2DM) patients.

METHODS

A total of 120 hospitalized patients with T2DM were enrolled and randomly divided into the control group and the intervention group. Patients in the control group only received conventional diabetes treatments, while patients in the intervention group were provided with a wearable monitoring device in addition to conventional diabetes treatments. Moreover, the wearable device could connect to an Internet platform for diabetes management and upload self-monitoring data. All patients were followed for 3 months. The changes in parameters representing glucose metabolism, blood lipids, renal function, and patient satisfaction were compared between the two groups. All results were analyzed on an intention-to-treat basis.

RESULTS

One hundred twenty subjects met all criteria and agreed to participate in this study. During the follow-up period, 5 and 4 subjects were lost to follow-up in the intervention and control groups, respectively. Compared with the control group, the blood glucose of the intervention group decreased significantly after 3 months (p < 0.05). Subgroup analysis found that females, those younger than 60 years, with baseline glycated hemoglobin A1c (HbA1c) levels of 8% or greater, and patients with good adherence showed significant improvements in HbA1c (p < 0.05). However, there was no significant difference in blood lipid and renal function. The intervention group showed a better adherence rate to blood glucose, comprehensive adherence rate, and diabetes treatment satisfaction (p < 0.05). One subject in the intervention group and two subjects in the control group reported mild hypoglycemia. No other adverse events such as infections and skin allergies occurred in the two groups.

CONCLUSION

The intervention of a wearable monitoring device based on an Internet management platform significantly improved blood glucose control in T2DM patients, as well as the overall adherence rate and patient satisfaction with treatment.

CLINICAL TRIAL REGISTRATION

NCT04973644.

Post-Intensive Care Syndrome in Neurocritical Care Patients

Post-intensive care syndrome (PICS) refers to unintended consequences of critical care that manifest as new or worsening impairments in physical functioning, cognitive ability, or mental health. As intensive care unit (ICU) survival continues to improve, PICS is becoming increasingly recognized as a public health problem. Studies that focus on PICS have typically excluded patients with acute brain injuries and chronic neurodegenerative problems. However, patients who require neurocritical care undoubtedly suffer from impairments that overlap substantially with those encompassed by PICS. A major challenge is to distinguish between impairments related to brain injury and those that occur as a consequence of critical care. The general principles for the prevention and management of PICS and multidomain impairments in patients with moderate and severe neurological injuries are similar including the ICU liberation bundle, multidisciplinary team-based care throughout the continuum of care, and increasing awareness regarding the challenges of critical care survivorship among patients, families, and multidisciplinary team members. An extension of this concept, PICS-Family (PICS-F) refers to the mental health consequences of the intensive care experience for families and loved ones of ICU survivors. A dyadic approach to ICU survivorship with an emphasis on recognizing families and caregivers that may be at risk of developing PICS-F after neurocritical care illness can help improve outcomes for ICU survivors. In this review, we will summarize our current understanding of PICS and PICS-F, emerging literature on PICS in severe acute brain injury, strategies for preventing and treating PICS, and share our recommendations for future directions.

Mobile Health Interventions: A Frontier for Mitigating the Global Burden of Cardiovascular Disease

Mobile health (mHealth) interventions have emerged as a promising approach for cardiovascular disease (CVD) prevention and management. The proliferation of smartphones and wearable devices enables convenient access to health monitoring tools, educational resources, and communication with healthcare providers. mHealth interventions encompass mobile apps, wearables, and telehealth services that empower users to monitor vital signs, adhere to medication, and adopt healthier lifestyles. Their effectiveness hinges on user engagement, leveraging behavioral science principles and gamification strategies. While mHealth offers advantages such as personalized support and increased reach, it faces challenges pertaining to data privacy, security concerns, and resistance from healthcare providers. Robust encryption and adherence to regulations like the Health Insurance Portability and Accountability Act (HIPAA) are crucial for safeguarding sensitive health data. Integrating mHealth into clinical workflows can enhance healthcare delivery, but organizational adjustments are necessary. The future of mHealth is closely intertwined with artificial intelligence (AI), enabling remote monitoring, predictive algorithms, and data-driven insights. Tech giants are incorporating advanced health-tracking capabilities into their devices, paving the way for personalized wellness approaches. However, mHealth grapples with ethical dilemmas surrounding data ownership, privacy breaches, and inadvertent data capture. Despite its potential, mHealth necessitates a concerted effort to overcome obstacles and ensure ethical, secure, and practical implementation. Addressing technical challenges, fostering standardization, and promoting equitable access are pivotal for unlocking the transformative impact of mHealth on cardiovascular health and reducing the global burden of CVD.

Using AI-Based Technologies to Help Nurses Detect Behavioral Disorders: Narrative Literature Review

BACKGROUND

The behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia and have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to help nurses in the early prodromal detection of BPSD. Despite significant recent interest in the topic and the increasing number of available appropriate devices, little information is available on using AITs to help nurses striving to detect BPSD early.

OBJECTIVE

The aim of this study is to identify the number and characteristics of existing publications on introducing AITs to support nursing interventions to detect and manage BPSD early.

METHODS

A literature review of publications in the PubMed database referring to AITs and dementia was conducted in September 2023. A detailed analysis sought to identify the characteristics of these publications. The results were reported using a narrative approach.

RESULTS

A total of 25 publications from 14 countries were identified, with most describing prospective observational studies. We identified three categories of publications on using AITs and they are (1) predicting behaviors and the stages and progression of dementia, (2) screening and assessing clinical symptoms, and (3) managing dementia and BPSD. Most of the publications referred to managing dementia and BPSD.

CONCLUSIONS

Despite growing interest, most AITs currently in use are designed to support psychosocial approaches to treating and caring for existing clinical signs of BPSD. AITs thus remain undertested and underused for the early and real-time detection of BPSD. They could, nevertheless, provide nurses with accurate, reliable systems for assessing, monitoring, planning, and supporting safe therapeutic interventions.

Precision epidemiology at the nexus of mathematics and nanotechnology: Unraveling the dance of viral dynamics

The intersection of mathematical modeling, nanotechnology, and epidemiology marks a paradigm shift in our battle against infectious diseases, aligning with the focus of the journal on the regulation, expression, function, and evolution of genes in diverse biological contexts. This exploration navigates the intricate dance of viral transmission dynamics, highlighting mathematical models as dual tools of insight and precision instruments, a theme relevant to the diverse sections of Gene. In the context of virology, ethical considerations loom large, necessitating robust frameworks to protect individual rights, an aspect essential in infectious disease research. Global collaboration emerges as a critical pillar in our response to emerging infectious diseases, fortified by the predictive prowess of mathematical models enriched by nanotechnology. The synergy of interdisciplinary collaboration, training the next generation to bridge mathematical rigor, biology, and epidemiology, promises accelerated discoveries and robust models that account for real-world complexities, fostering innovation and exploration in the field. In this intricate review, mathematical modeling in viral transmission dynamics and epidemiology serves as a guiding beacon, illuminating the path toward precision interventions, global preparedness, and the collective endeavor to safeguard human health, resonating with the aim of advancing knowledge in gene regulation and expression.

Comprehensive and personalized approach is a critical area for developing remote cardiac rehabilitation programs

In the evolving landscape of cardiac rehabilitation (CR), adopting digital technologies, including synchronous/real-time digital interventions and smart applications, has emerged as a transformative approach. These technologies offer real-time health data access, continuous vital sign monitoring, and personalized educational enhanced patient self-management and engagement. Despite their potential benefits, challenges and limitations exist, necessitating careful consideration. Synchronous/real-time digital CR involves remote, two-way audiovisual communication, addressing issues of accessibility and promoting home-based interventions. Smart applications extend beyond traditional healthcare, providing real-time health data and fostering patient empowerment. Wearable devices and mobile apps enable continuous monitoring, tracking of rehabilitation outcomes, and facilitate lifestyle modifications crucial for cardiac health maintenance. As digital CR progresses, ensuring patient access, equitable implementation, and addressing the digital divide becomes paramount. Artificial intelligence holds promise in the early detection of cardiac events and tailoring patient-specific CR programs. However, challenges such as digital literacy, data privacy, and security must be addressed to ensure inclusive implementation. Moreover, the shift toward digital CR raises concerns about cost, safety, and potential depersonalization of therapeutic relationships. A transformative shift towards technologically enabled CR necessitates further research, focusing not only on technological advancements but also on customization to meet diverse patient needs. Overcoming challenges related to cost, safety, data security, and potential depersonalization is crucial for the widespread adoption of digital CR. Future studies should explore integrating moral values into digital therapeutic relationships and ensure that digital CR is accessible, equitable, and seamlessly integrated into routine cardiac care. Theoretical frameworks that accommodate the dynamic quality of real-time monitoring and feedback feature of digital CR interventions should be considered to guide intervention development.

Palliative and End-of-Life Family Caregiving in Rural Areas: A Scoping Review of Social Determinants of Health and Emotional Well-Being

Introduction: Due to their remote location, rural-dwelling family caregivers (FCGs) experience geographic and psychosocial challenges when providing home-based palliative and end-of-life (PEOL) care for their care recipient. Limited research has evaluated the social and environmental factors that may compound FCG burden and contribute to adverse emotional health outcomes among rural-dwelling PEOL FCGs. Objective: To characterize the social determinants of health (SDOH) that affect the provision of PEOL care among rural-dwelling FCGs, along with symptoms of anxiety and depression. Methods: A scoping review was conducted using Arksey and O'Malley's Framework. Searches were conducted in PubMed, CINAHL, PsycINFO, and Cochrane, and 511 articles published between 2010 and 2023 were screened. Keywords included "rural," "PEOL care," and "FCG." Inclusion criteria included FCGs, ages ≥18 years; findings reported on SDOH, anxiety, and/or depressive symptoms; within a rural context; and U.S. based. Findings: In this review, 18 studies met eligibility and were included. Apart from six studies that specifically investigated Black and Latinx FCGs, most FCGs were middle-aged White female spouses. SDOH impacting PEOL care provision included: limited access to PEOL services due to remote distance and travel needs for services; low health literacy in medical terminology and patient symptom management; limited English-language proficiency; perceived clinician racial and ethnic discrimination; financial vulnerabilities affecting health care coverage; and underdeveloped infrastructure. These barriers negatively impacted decision making, communication with clinicians, and patient symptom management. FCGs reported emotional distress related to patients' symptom management and limited opportunities for respite. There was a limited investigation of emotional well-being and minimal interventions aimed toward improving rural-dwelling FCG emotional health. The presence of community support promoted hospice use and facilitated the provision of care. Conclusions: FCGs are vulnerable to adverse emotional health when providing home-based PEOL care. Research is needed to develop supportive interventions (e.g., digital health) for rural-dwelling FCGs.

Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review

BACKGROUND

Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users' acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential.

OBJECTIVE

This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations.

METHODS

We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords "wearable devices," "mobile apps," "mHealth apps," "physiological data," "usability," "user experience," and "user evaluation" were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist.

RESULTS

A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation.

CONCLUSIONS

Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.

Association Between Wearable Device Use and Quality of Life in Patients With Idiopathic Inflammatory Myopathies and Primary Systemic Vasculitis

Background Despite the increasing use of wearable devices worldwide, concise data on these instruments in patients with systemic autoimmune rheumatic diseases, including idiopathic inflammatory myopathies (IIM) and primary systemic vasculitis (PSV), are lacking. Objectives The aim of this study is to investigate the knowledge and use of wearable devices and to assess their impact on the general quality of life of patients with IIM and PSV. Moreover, we compared these characteristics between patients with IIM and PSV users and non-users of wearable devices. Methods This single-center, cross-sectional study was conducted between January 2023 and June 2023. We included adult patients with IIM and PSV and a control group (CTR) and evaluated their use of cell phones and wearables, level of physical activity, and quality of life. Results A total of 132 patients with IIM, 82 with PSV, and 178 in the CTR were evaluated. Overall, 169 patients and 144 in the CTR were aware of wearable devices, of whom 50 (29.6%) and 47 (32.6%), respectively, had already used this technology. In addition, the IPAQ-Mets and EQ-5D scores were lower in the IIM and PSV groups than in the CTR, and the fatigue severity scale (FSS) scores were higher in the IIM and PSV groups than in the CTR. Patients who used the devices showed FSS scores of 29 (18-40) points, with higher levels of IPAQ-Mets among device users, indicating greater physical activity than among nonusers. Conclusion Based on the results, the use of wearable devices is associated with better fatigue and IPAQ scores. Possibly, the use of such devices can have an impact on better lifestyle habits among these patients.

Use of wearables among Multiple Sclerosis patients and healthcare Professionals: A scoping review

INTRODUCTION

Multiple sclerosis (MS) is an increasingly prevalent chronic, autoimmune, and inflammatory central nervous system illness, whose common symptoms undermine the quality of life of patients and their families. Recent technical breakthroughs potentially offer continuous, reliable, sensitive, and objective remote monitoring solutions for healthcare. Wearables can be useful for evaluating falls, fatigue, sedentary behavior, exercise, and sleep quality in people with MS (PwMS).

OBJECTIVE

This scoping review of relevant literature explores studies investigating the perceptions of patients and healthcare professionals (HCPs) about the use of wearable technologies in the management of MS.

METHODS

The Joanna Briggs Institute methodology for scoping reviews was used. The search strategy was applied to the databases, MEDLINE via Ovid, Embase, APA PsycInfo, and CINAHL. Further searches were performed in IEEE, Scopus, and Web of Science. The review considered studies reporting quantitative or qualitative data on perceptions and experiences of PwMS and HCPs concerning wearables' usability, satisfaction, barriers, and facilitators.

RESULTS

10 studies were included in this review. Wearables' usefulness and accessibility, ease of use, awareness, and motivational tool potential were patient-perceived facilitators of use. Barriers related to anxiety and frustration, complexity, and the design of wearables. Perceived usefulness and system requirements are identified as facilitators of using wearables by HCPs, while data security concerns and fears of increased workload and limited effectiveness in the care plan are identified as barriers to use wearables.

CONCLUSIONS

This review contributes to our understanding of the benefits of wearable technologies in MS by exploring perceptions of both PwMS and HCPs. The scoping review provided a broad overview of facilitators and barriers to wearable use in MS. There is a need for further studies underlined with sound theoretical frameworks to provide a robust evidence-base for the optimal use of wearables to empower healthcare users and providers.

Wearable device adherence among insufficiently-active young adults is independent of identity and motivation for physical activity

Wearable devices are increasingly being integrated to improve prevention, chronic disease management and rehabilitation. Inferences about individual differences in device-measured physical activity depends on devices being worn long enough to obtain representative samples of behavior. Little is known about how psychological factors are associated with device wear time adherence. This study evaluated associations between identity, behavioral regulations, and device wear adherence during an ambulatory monitoring period. Young adults who reported insufficient physical activity (N = 271) were recruited for two studies before and after the SARS-COVID-19 pandemic declaration. Participants completed a baseline assessment and wore an Actigraph GT3X + accelerometer on their waist for seven consecutive days. Multiple linear regression indicated that wear time was positively associated with age, negatively associated with integrated regulation for physical activity, and greater after (versus before) the pandemic declaration. Overall, the model accounted for limited variance in device wear time. Exercise identity and exercise motivation were not associated with young adults' adherence to wearing the physical activity monitors. Researchers and clinicians can use wearable devices with young adults with minimal concern about systematic motivational biases impacting adherence to device wear.

Heart Rate Measurement Using the Built-In Triaxial Accelerometer from a Commercial Digital Writing Device

Currently, wearable technology is an emerging trend that offers remarkable access to our data through smart devices like smartphones, watches, fitness trackers and textiles. As such, wearable devices can enable health monitoring without disrupting our daily routines. In clinical settings, electrocardiograms (ECGs) and photoplethysmographies (PPGs) are used to monitor heart and respiratory behaviors. In more practical settings, accelerometers can be used to estimate the heart rate when they are attached to the chest. They can also help filter out some noise in ECG signals from movement. In this work, we compare the heart rate data extracted from the built-in accelerometer of a commercial smart pen equipped with sensors (STABILO's DigiPen) to standard ECG monitor readouts. We demonstrate that it is possible to accurately predict the heart rate from the smart pencil. The data collection is carried out with eight volunteers writing the alphabet continuously for five minutes. The signal is processed with a Butterworth filter to cut off noise. We achieve a mean-squared error (MSE) better than 6.685 × 10-3 comparing the DigiPen's computed Δt (time between pulses) with the reference ECG data. The peaks' timestamps for both signals all maintain a correlation higher than 0.99. All computed heart rates (HR =60Δt) from the pen accurately correlate with the reference ECG signals.

Performance analysis of solution-processed nanosheet strain sensors-a systematic review of graphene and MXene wearable devices

Nanotechnology has led to the realisation of many potentialInternet of Thingsdevices that can be transformative with regards to future healthcare development. However, there is an over saturation of wearable sensor review articles that essentially quote paper abstracts without critically assessing the works. Reported metrics in many cases cannot be taken at face value, with researchers overly fixated on large gauge factors. These facts hurt the usefulness of such articles and the very nature of the research area, unintentionally misleading those hoping to progress the field. Graphene and MXenes are arguably the most exciting organic and inorganic nanomaterials for polymer nanocomposite strain sensing applications respectively. Due to their combination of cost-efficient, scalable production and device performances, their potential commercial usage is very promising. Here, we explain the methods for colloidal nanosheets suspension creation and the mechanisms, metrics and models which govern the electromechanical properties of the polymer-based nanocomposites they form. Furthermore, the many fabrication procedures applied to make these nanosheet-based sensing devices are discussed. With the performances of 70 different nanocomposite systems from recent (post 2020) publications critically assessed. From the evaluation of these works using universal modelling, the prospects of the field are considered. Finally, we argue that the realisation of commercial nanocomposite devices may in fact have a negative effect on the global climate crisis if current research trends do not change.

Advancements in Wearable Digital Health Technology: A Review of Epilepsy Management

This review explores recent advancements in wearable digital health technology specifically designed to manage epilepsy. Epilepsy presents unique challenges in monitoring and management due to the unpredictable nature of seizures. Wearable devices offer continuous monitoring and real-time data collection, providing insights into seizure patterns and trends. Wearable technology is important in epilepsy management because it enables early detection, prediction, and personalized intervention, empowering patients and healthcare providers. Key findings highlight the potential of wearable devices to improve seizure detection accuracy, enhance patient empowerment through real-time monitoring, and facilitate data-driven decision-making in clinical practice. However, further research is needed to validate the accuracy and reliability of these devices across diverse patient populations and clinical settings. Collaborative efforts between researchers, clinicians, technology developers, and patients are essential to drive innovation and advancements in wearable digital health technology for epilepsy management, ultimately improving outcomes and quality of life for individuals with this neurological condition.

Seizure Detection, Prediction, and Forecasting

SUMMARY

Among the many fears associated with seizures, patients with epilepsy are greatly frustrated and distressed over seizure's apparent unpredictable occurrence. However, increasing evidence have emerged over the years to support that seizure occurrence is not a random phenomenon as previously presumed; it has a cyclic rhythm that oscillates over multiple timescales. The pattern in rises and falls of seizure rate that varies over 24 hours, weeks, months, and years has become a target for the development of innovative devices that intend to detect, predict, and forecast seizures. This article will review the different tools and devices available or that have been previously studied for seizure detection, prediction, and forecasting, as well as the associated challenges and limitations with the utilization of these devices. Although there is strong evidence for rhythmicity in seizure occurrence, very little is known about the mechanism behind this oscillation. This article concludes with early insights into the regulations that may potentially drive this cyclical variability and future directions.

Strategies in surface engineering for the regulation of microclimates in skin-medical product interactions

There is a growing number of personal healthcare devices that are in prolonged contact with the skin. The functionality of these products is linked to the interface formed by the contact between the medical apparatus and the skin. The interface can be characterised by its topology, compliance, and moisture and thermal regulating capabilities. Many devices are, however, described to have suboptimal and occlusive contacts, resulting in physiological unfavourable microclimates at the interface. The resulting poor management of moisture and temperature can impact the functionality and utility of the device and, in severe cases, lead to physical harm to the user. Being able to control the microclimate is therefore expected to limit medical-device related injuries and prevent associated skin complications. Surface engineering can modify and potentially enhance the regulation of the microclimate factors surrounding the interface between a product's surface and the skin. This review provides an overview of potential engineering solutions considering the needs for, and influences on, regulation of temperature and moisture by considering the skin-medical device interface as a system. These findings serve as a platform for the anticipated progress in the role of surface engineering for skin-device microclimate regulation.

The hospital at home in the USA: current status and future prospects

The annual cost of hospital care services in the US has risen to over $1 trillion despite relatively worse health outcomes compared to similar nations. These trends accentuate a growing need for innovative care delivery models that reduce costs and improve outcomes. HaH-a program that provides patients acute-level hospital care at home-has made significant progress over the past two decades. Technological advancements in remote patient monitoring, wearable sensors, health information technology infrastructure, and multimodal health data processing have contributed to its rise across hospitals. More recently, the COVID-19 pandemic brought HaH into the mainstream, especially in the US, with reimbursement waivers that made the model financially acceptable for hospitals and payors. However, HaH continues to face serious challenges to gain widespread adoption. In this review, we evaluate the peer-reviewed evidence and discuss the promises, challenges, and what it would take to tap into the future potential of HaH.

Effects of isometric training and R.I.C.E. treatment on the arm muscle performance of swimmers with elbow pain

The effects of IT and R.I.C.E. treatment on arm muscle performance in overhead athletes with elbow pain (EP) have been partially validated. However, there is a lack of research evidence regarding the efficacy of these two methods on arm muscle performance among swimmers with EP. The aim of this study was to investigate the trends and differences in the effects of IT and R.I.C.E. treatment on arm muscle performance among swimmers with EP. The main outcomes were the time effects and group effects of interventions on muscle voluntary contraction (MVC). Sixty elite freestyle swimmers from Tianjin, China, voluntarily participated in the study and completed a 10-week intervention program. Swimmers with EP in the IT group showed a positive trend in MVC, with an approximately 2% increase, whereas the MVC of subjects in the R.I.C.E. treatment group and control group decreased by approximately 4% and 5%, respectively. In comparison, the effects of the IT intervention on the MVC of the triceps and brachioradialis muscles in swimmers with EP were significant (p = 0.042 < 0.05, p = 0.027 < 0.05). The mean MVC value of the IT group (0.60) was greater than that of the other two groups (0.51, 0.50). IT has a beneficial impact on the MVC performance of the triceps and brachioradialis muscles in swimmers with EP. It is recommended that professionals consider incorporating IT into regular training routines to mitigate the risk of EP issues. Future research should examine the effectiveness of both interventions on hand-grip strength and completion time in 50-m freestyle swim drills in order for swimmers with EP to return to this sport.

Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation

In healthcare, machine learning (ML) shows significant potential to augment patient care, improve population health, and streamline healthcare workflows. Realizing its full potential is, however, often hampered by concerns about data privacy, diversity in data sources, and suboptimal utilization of different data modalities. This review studies the utility of cross-cohort cross-category (C4) integration in such contexts: the process of combining information from diverse datasets distributed across distinct, secure sites. We argue that C4 approaches could pave the way for ML models that are both holistic and widely applicable. This paper provides a comprehensive overview of C4 in health care, including its present stage, potential opportunities, and associated challenges.

Advances in Printed Electronic Textiles

Electronic textiles (e-textiles) have emerged as a revolutionary solution for personalized healthcare, enabling the continuous collection and communication of diverse physiological parameters when seamlessly integrated with the human body. Among various methods employed to create wearable e-textiles, printing offers unparalleled flexibility and comfort, seamlessly integrating wearables into garments. This has spurred growing research interest in printed e-textiles, due to their vast design versatility, material options, fabrication techniques, and wide-ranging applications. Here, a comprehensive overview of the crucial considerations in fabricating printed e-textiles is provided, encompassing the selection of conductive materials and substrates, as well as the essential pre- and post-treatments involved. Furthermore, the diverse printing techniques and the specific requirements are discussed, highlighting the advantages and limitations of each method. Additionally, the multitude of wearable applications made possible by printed e-textiles is explored, such as their integration as various sensors, supercapacitors, and heated garments. Finally, a forward-looking perspective is provided, discussing future prospects and emerging trends in the realm of printed wearable e-textiles. As advancements in materials science, printing technologies, and design innovation continue to unfold, the transformative potential of printed e-textiles in healthcare and beyond is poised to revolutionize the way wearable technology interacts and benefits.

Factors Associated with Veteran Self-Reported Use of Digital Health Devices

BACKGROUND

Digital health devices (DHDs), technologies designed to gather, monitor, and sometimes share data about health-related behaviors or symptoms, can support the prevention or management of chronic conditions. DHDs range in complexity and utility, from tracking lifestyle behaviors (e.g., pedometer) to more sophisticated biometric data collection for disease self-management (e.g., glucometers). Despite these positive health benefits, supporting adoption and sustained use of DHDs remains a challenge.

OBJECTIVE

This analysis examined the prevalence of, and factors associated with, DHD use within the Veterans Health Administration (VHA).

DESIGN

National survey.

PARTICIPANTS

Veterans who receive VHA care and are active secure messaging users.

MAIN MEASURES

Demographics, access to technology, perceptions of using health technologies, and use of lifestyle monitoring and self-management DHDs.

RESULTS

Among respondents, 87% were current or past users of at least one DHD, and 58% were provided a DHD by VHA. Respondents 65 + years were less likely to use a lifestyle monitoring device (AOR 0.57, 95% CI [0.39, 0.81], P = .002), but more likely to use a self-management device (AOR 1.69, 95% [1.10, 2.59], P = .016). Smartphone owners were more likely to use a lifestyle monitoring device (AOR 2.60, 95% CI [1.42, 4.75], P = .002) and a self-management device (AOR 1.83, 95% CI [1.04, 3.23], P = .037).

CONCLUSIONS

The current analysis describes the types of DHDs that are being adopted by Veterans and factors associated with their adoption. Results suggest that various factors influence adoption, including age, access to technology, and health status, and that these relationships may differ based on the functionalities of the device. VHA provision of devices was frequent among device users. Providing Veterans with DHDs and the training needed to use them may be important factors in facilitating device adoption. Taken together, this knowledge can inform future implementation efforts, and next steps to support patient-team decision making about DHD use.

Patterns of digital health access and use among US adults: A latent class analysis

Background Digital technologies allow users to engage in health-related behaviors associated with positive outcomes. We aimed to identify classes of US adults with distinct digital technologies access and health use patterns and characterize class composition. Data came from Health Information National Trends Survey Wave 5 Cycles 1-4, a nationally representative cross-sectional survey of US adults ( N  = 13,993). We used latent class analysis to identify digital technologies access and health use patterns based on 32 behaviors and access to requisite technologies and platforms that include the internet, internet-enabled devices, health monitors, and electronic health records (EHRs). We ran a multinomial logistic regression to identify sociodemographic and health correlates of class membership ( n  = 10,734). Results Ten classes captured patterns of digital technology access and health use among US adults. This included a digitally isolated, a mobile-dependent, and a super user class, which made up 8.9%, 7.8%, and 13.6% of US adults, respectively, and captured access patterns from only basic cellphones and health monitors to near complete access to web-, mobile-, and EHR-based platforms. Half of US adults belonged to classes that lacked access to EHRs and relied on alternative web-based tools typical of patient portals. The proportion of class members who used digital technologies for health purposes varied from small to large. Older and less educated adults had lower odds of belonging to classes characterized by access or engagement in health behaviors. Hispanic and Asian adults had higher odds of belonging to the mobile-dependent class. Individuals without a regular healthcare provider and those who had not visited a provider in the past year were more likely to belong to classes with limited digital technologies access or health use. Discussion Only one third of US adults belonged to classes that had near complete access to digital technologies and whose members engaged in almost all health behaviors examined. Sex, age, and education were associated with membership in classes that lacked access to 1 + digital technologies or exhibited none to limited health uses of such technologies. Results can guide efforts to improve access and health use of digital technologies to maximize associated health benefits and minimize disparities.

Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities

Physical rehabilitation and exercise training have emerged as promising solutions for improving health, restoring function, and preserving quality of life in populations that face disparate health challenges related to disability. Despite the immense potential for rehabilitation and exercise to help people with disabilities live longer, healthier, and more independent lives, people with disabilities can experience physical, psychosocial, environmental, and economic barriers that limit their ability to participate in rehabilitation, exercise, and other physical activities. Together, these barriers contribute to health inequities in people with disabilities, by disproportionately limiting their ability to participate in health-promoting physical activities, relative to people without disabilities. Therefore, there is great need for research and innovation focusing on the development of strategies to expand accessibility and promote participation in rehabilitation and exercise programs for people with disabilities. Here, we discuss how cutting-edge technologies related to telecommunications, wearables, virtual and augmented reality, artificial intelligence, and cloud computing are providing new opportunities to improve accessibility in rehabilitation and exercise for people with disabilities. In addition, we highlight new frontiers in digital health technology and emerging lines of scientific research that will shape the future of precision care strategies for people with disabilities.

Inter-Specimen Analysis of Diverse Finite Element Models of the Lumbar Spine

Over the past few decades, there has been a growing popularity in utilizing finite element analysis to study the spine. However, most current studies tend to use one specimen for their models. This research aimed to validate multiple finite element models by comparing them with data from in vivo experiments and other existing finite element studies. Additionally, this study sought to analyze the data based on the gender and age of the specimens. For this study, eight lumbar spine (L2-L5) finite element models were developed. These models were then subjected to finite element analysis to simulate the six fundamental motions. CT scans were obtained from a total of eight individuals, four males and four females, ranging in age from forty-four (44) to seventy-three (73) years old. The CT scans were preprocessed and used to construct finite element models that accurately emulated the motions of flexion, extension, lateral bending, and axial rotation. Preloads and moments were applied to the models to replicate physiological loading conditions. This study focused on analyzing various parameters such as vertebral rotation, facet forces, and intradiscal pressure in all loading directions. The obtained data were then compared with the results of other finite element analyses and in vivo experimental measurements found in the existing literature to ensure their validity. This study successfully validated the intervertebral rotation, intradiscal pressure, and facet force results by comparing them with previous research findings. Notably, this study concluded that gender did not have a significant impact on the results. However, the results did highlight the importance of age as a critical variable when modeling the lumbar spine.

A prospective natural history study of post acute sequalae of COVID-19 using digital wearables: Study protocol

Background

Post-acute sequelae of COVID-19 (PASC) is characterized by having 1 + persistent, recurrent, or emergent symptoms post the infection's acute phase. The duration and symptom manifestation of PASC remain understudied in nonhospitalized patients. Literature on PASC is primarily based on data from hospitalized patients where clinical indicators such as respiratory rate, heart rate, and oxygen saturation have been predictive of disease trajectories. Digital wearables allow for a continuous collection of such physiological parameters. This protocol outlines the design, aim, and procedures of a natural history study of PASC using digital wearables.

Methods

This is a single-arm, prospective, natural history study of a cohort of 550 patients, ages 18 to 65 years old, males or females who own a smartphone and/or a tablet that meets pre-determined Bluetooth version and operating system requirements, speak English, and provide documentation of a positive COVID-19 test issued by a healthcare professional or organization within 5 days before enrollment. The study aims to identify wearables collected physiological parameters that are associated with PASC in patients with a positive diagnosis. The primary endpoint is long COVID-19, defined as ≥ 1 symptom at 3 weeks beyond first symptom onset or positive diagnosis, whichever comes first. The secondary endpoint is chronic COVID-19, defined as ≥ 1 symptom at 12 weeks beyond first symptom onset or positive diagnosis. We hypothesize that physiological parameters collected via wearables are associated with self-reported PASC. Participants must be willing and able to consent to participate in the study and adhere to study procedures for six months.

Discussion

This is a fully decentralized study investigating PASC using wearable devices to collect physiological parameters and patient-reported outcomes. Given evidence on key demographics and risk profiles associated with PASC, the study will shed light on the duration and symptom manifestation of PASC in nonhospitalized patient subgroups and is an exemplar of use of wearables as population-level monitoring health tools for communicable diseases.

Trial registration

ClinicalTrials.gov NCT04927442.

Promoting physical activity in clinical practice through wearable technology

ABSTRACT

The negative health consequences of physical inactivity continue to be a global problem that must be addressed from the highest levels of government down to local primary care providers. Physical activity has been identified as a useful patient vital sign in health care. Advanced practice nurses should aggressively prescribe physical activity as an evidence-based intervention to help mitigate the increased mortality and morbidity associated with a sedentary lifestyle. A focused literature review was conducted using PubMed, CINAHL, and the Cochrane online databases. Fitness wearables and mobile health trackers are a catalyst for lifestyle behavior change and cultivate a health care partnership between the patient and their provider. The evolution of fitness wearables into mainstream health care hinges on the ability of devices to integrate into electronic health records, uniformity of manufacturer standards, intuitiveness, and the assurance of user privacy and security. It is incumbent on nurse practitioners to educate themselves about the reliability and practicality of fitness trackers for their patient population. Future research should focus on adopting quality standards for all consumer devices, the seamless integration of device data into electronic health records and ensuring personal privacy and security.

Wolf Creek XVII part 3: Automated cardiac arrest diagnosis

Introduction

Automated cardiac arrest diagnosis offers the possibility to significantly shorten the interval between onset of out-of-hospital cardiac arrest (OHCA) and notification of EMS, providing the opportunity for earlier resuscitation and possibly increased survival.

Methods

Automated cardiac arrest diagnosis was one of six focus topics for the Wolf Creek XVII Conference held on June 14-17 2023 in Ann Arbor, Michigan, USA. Conference invitees included international thought leaders and scientists in the field of cardiac arrest resuscitation from academia and industry. Participants submitted via online survey knowledge gaps, barriers to translation and research priorities for each focus topic. Expert panels used the survey results and their own perspectives and insights to create and present a preliminary unranked list for each category that was debated, revised and ranked by all attendees to identify the top 5 for each category.

Results

Top knowledge gaps include the accuracy of automated OHCA detection technologies and the feasibility and reliability of automated EMS activation. The main barriers to translation are the risk of false positives potentially overburdening EMS, development and application costs of technology and the challenge of integrating new technology in EMS IT systems. The top research priorities are large-scale evaluation studies to measure real world performance and user research regarding the willingness to adopt these technologies.

Conclusion

Automated cardiac arrest diagnosis has the potential to significantly impact time to resuscitation and survival of OHCA because it could convert unwitnessed events into witnessed events. Validation and feasibility studies are needed. The specificity of the technology must be high not to overburden limited EMS resources. If adequate event classification is achieved, future research could shift toward event prediction, focusing on identifying potential digital biomarkers and signatures of imminent cardiac arrest. Implementation could be challenging due to high costs of development, regulatory considerations and instantiation logistics.

Older Adults' Perceptions About Using Intelligent Toilet Seats Beyond Traditional Care: Web-Based Interview Survey

BACKGROUND

In contemporary society, age tech (age technology) represents a significant advancement in health care aimed at enhancing patient engagement, ensuring sustained independence, and promoting quality of life for older people. One innovative form of age tech is the intelligent toilet seat, which is designed to collect, analyze, and provide insights based on toileting logs and excreta data. Understanding how older people perceive and interact with such technology can offer invaluable insights to researchers, technology developers, and vendors.

OBJECTIVE

This study examined older adults' perspectives regarding the use of intelligent toilet seats. Through a qualitative methodology, this research aims to unearth the nuances of older people's opinions, shedding light on their preferences, concerns, and potential barriers to adoption.

METHODS

Data were collected using a web-based interview survey distributed on Amazon Mechanical Turk. The analyzed data set comprised 174 US-based individuals aged ≥65 years who voluntarily participated in this study. The qualitative data were carefully analyzed using NVivo (Lumivero) based on detailed content analysis, ensuring that emerging themes were coded and classified based on the conceptual similarities in the respondents' narratives.

RESULTS

The analysis revealed 5 dominant themes encompassing the opinions of aging adults. The perceived benefits and advantages of using the intelligent toilet seat were grouped into 3 primary themes: health-related benefits including the potential for early disease detection, continuous health monitoring, and seamless connection to health care insights. Technology-related advantages include the noninvasive nature of smart toilet seats and leveraging unique and innovative data collection and analysis technology. Use-related benefits include ease of use, potential for multiple users, and cost reduction owing to the reduced need for frequent clinical visits. Conversely, the concerns and perceived risks were classified into 2 significant themes: psychological concerns, which included concerns about embarrassment and aging-related stereotypes, and the potential emotional impact of constant health monitoring. Technical performance risks include concerns centered on privacy and security, device reliability, data accuracy, potential malfunctions, and the implications of false positives or negatives.

CONCLUSIONS

The decision of older adults to incorporate intelligent toilet seats into their daily lives depends on myriad factors. Although the potential health and technological benefits are evident, valid concerns that need to be addressed remain. To foster widespread adoption, it is imperative to enhance the advantages while simultaneously addressing and mitigating the identified risks. This balanced approach will pave the way for a more holistic integration of smart health care devices into the routines of the older population, ensuring that they reap the full benefits of age tech advancements.

Early monitoring of intravenous thrombolysis in acute ischaemic stroke using wearable intelligent vital sign devices: protocol for a prospective, multicentre, observational registry cohort study

INTRODUCTION

Continuous monitoring of vital signs during and after ischaemic stroke was recommended by the 'Guidelines for the Early Management of Patients with Acute Ischaemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischaemic Stroke'. Vital sign data can be associated with disease conditions and prognosis, while there is limited evidence regarding continuous monitoring of vital signs during and after acute ischaemic stroke. The wearable intelligent vital sign monitoring device is small and lightweight and constantly monitors the health status during daily activities. However, wearable intelligent vital sign monitoring devices have not been widely used in clinical practice so far. Therefore, we will investigate the effectiveness and safety of wearable intelligent vital sign monitoring devices in early in-hospital management and monitoring programmes for patients with acute ischaemic stroke. This paper presents the study protocol.

METHODS AND DESIGN

This study is a prospective, multicentre, observational registry study starting from 20 March 2023 to 20 March 2025. A total of 5740 patients with acute ischaemic stroke from 10 Chinese hospitals are planned to be enrolled. Continuous vital sign data, demographics, medical history, medication history, treatments, laboratory tests, imaging scans and follow-up data will be collected. Follow-up time points were 30 days after discharge, 30 days after intravenous thrombolysis, 3 months after intravenous thrombolysis and 12 months after intravenous thrombolysis (until March 2026). The primary outcome included the evaluation of the modified Rankin Scale at 3 months, as well as the assessment of the rate of symptomatic and asymptomatic intracranial haemorrhage throughout the hospitalisation period.

ETHICS AND DISSEMINATION

This study has been approved by the Medical Ethics Committee of Xuanwu Hospital, Capital Medical University ([2022] 203). We plan to disseminate the research findings through publication in peer-reviewed scientific journals and presentations at international conferences.

TRIAL REGISTRATION NUMBER

ChiCTR2300069512.

Evaluating a Remote Monitoring Program for Respiratory Diseases: Prospective Observational Study

BACKGROUND

Patients with chronic respiratory diseases and those in the postdischarge period following hospitalization because of COVID-19 are particularly vulnerable, and little is known about the changes in their symptoms and physiological parameters. Continuous remote monitoring of physiological parameters and symptom changes offers the potential for timely intervention, improved patient outcomes, and reduced health care costs.

OBJECTIVE

This study investigated whether a real-time multimodal program using commercially available wearable technology, home-based Bluetooth-enabled spirometers, finger pulse oximeters, and smartphone apps is feasible and acceptable for patients with chronic respiratory diseases, as well as the value of low-burden, long-term passive data collection.

METHODS

In a 3-arm prospective observational cohort feasibility study, we recruited 60 patients from the Royal Free Hospital and University College Hospital. These patients had been diagnosed with interstitial lung disease, chronic obstructive pulmonary disease, or post-COVID-19 condition (n=20 per group) and were followed for 180 days. This study used a comprehensive remote monitoring system designed to provide real-time and relevant data for both patients and clinicians. Data were collected using REDCap (Research Electronic Data Capture; Vanderbilt University) periodic surveys, Remote Assessment of Disease and Relapses-base active app questionnaires, wearables, finger pulse oximeters, smartphone apps, and Bluetooth home-based spirometry. The feasibility of remote monitoring was measured through adherence to the protocol, engagement during the follow-up period, retention rate, acceptability, and data integrity.

RESULTS

Lowest-burden passive data collection methods, via wearables, demonstrated superior adherence, engagement, and retention compared with active data collection methods, with an average wearable use of 18.66 (SD 4.69) hours daily (77.8% of the day), 123.91 (SD 33.73) hours weekly (72.6% of the week), and 463.82 (SD 156.70) hours monthly (64.4% of the month). Highest-burden spirometry tasks and high-burden active app tasks had the lowest adherence, engagement, and retention, followed by low-burden questionnaires. Spirometry and active questionnaires had the lowest retention at 0.5 survival probability, indicating that they were the most burdensome. Adherence to and quality of home spirometry were analyzed; of the 7200 sessions requested, 4248 (59%) were performed. Of these, 90.3% (3836/4248) were of acceptable quality according to American Thoracic Society grading. Inclusion of protocol holidays improved retention measures. The technologies used were generally well received.

CONCLUSIONS

Our findings provide evidence supporting the feasibility and acceptability of remote monitoring for capturing both subjective and objective data from various sources for respiratory diseases. The high engagement level observed with passively collected data suggests the potential of wearables for long-term, user-friendly remote monitoring in respiratory disease management. The unique piloting of certain features such as protocol holidays, alert notifications for missing data, and flexible support from the study team provides a reference for future studies in this field.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/28873.

Applications of wearable sensors in upper extremity MSK conditions: a scoping review

PURPOSE

This scoping review uniquely aims to map the current state of the literature on the applications of wearable sensors in people with or at risk of developing upper extremity musculoskeletal (UE-MSK) conditions, considering that MSK conditions or disorders have the highest rate of prevalence among other types of conditions or disorders that contribute to the need for rehabilitation services.

MATERIALS AND METHODS

The preferred reporting items for systematic reviews and meta-analysis (PRISMA) extension for scoping reviews guideline was followed in this scoping review. Two independent authors conducted a systematic search of four databases, including PubMed, Embase, Scopus, and IEEEXplore. We included studies that have applied wearable sensors on people with or at risk of developing UE-MSK condition published after 2010. We extracted study designs, aims, number of participants, sensor placement locations, sensor types, and number, and outcome(s) of interest from the included studies. The overall findings of our scoping review are presented in tables and diagrams to map an overview of the existing applications.

RESULTS

The final review encompassed 80 studies categorized into clinical population (31 studies), workers' population (31 studies), and general wearable design/performance studies (18 studies). Most were observational, with 2 RCTs in workers' studies. Clinical studies focused on UE-MSK conditions like rotator cuff tear and arthritis. Workers' studies involved industrial workers, surgeons, farmers, and at-risk healthy individuals. Wearable sensors were utilized for objective motion assessment, home-based rehabilitation monitoring, daily activity recording, physical risk characterization, and ergonomic assessments. IMU sensors were prevalent in designs (84%), with a minority including sEMG sensors (16%). Assessment applications dominated (80%), while treatment-focused studies constituted 20%. Home-based applicability was noted in 21% of the studies.

CONCLUSION

Wearable sensor technologies have been increasingly applied to the health care field. These applications include clinical assessments, home-based treatments of MSK disorders, and monitoring of workers' population in non-standardized areas such as work environments. Assessment-focused studies predominate over treatment studies. Additionally, wearable sensor designs predominantly use IMU sensors, with a subset of studies incorporating sEMG and other sensor types in wearable platforms to capture muscle activity and inertial data for the assessment or rehabilitation of MSK conditions.

The use of commercial wrist-worn technology to track physiological outcomes in behavioral interventions

PURPOSE OF REVIEW

The aim of this review is to provide an overview of the use of commercial wrist-worn mobile health devices to track and monitor physiological outcomes in behavioral interventions as well as discuss considerations for selecting the optimal device.

RECENT FINDINGS

Wearable technology can enhance intervention design and implementation. The use of wrist-worn wearables provides the opportunity for tracking physiological outcomes, thus providing a unique approach for assessment and delivery of remote interventions. Recent findings support the utility, acceptability, and benefits of commercial wrist-worn wearables in interventions, and they can be used to continuously monitor outcomes, remotely administer assessments, track adherence, and personalize interventions. Wrist-worn devices show acceptable accuracy when measuring heart rate, blood pressure, step counts, and physical activity; however, accuracy is dependent on activity type, intensity, and device brand. These factors should be considered when designing behavioral interventions that utilize wearable technology.

SUMMARY

With the continuous advancement in technology and frequent product upgrades, the capabilities of commercial wrist-worn devices will continue to expand, thus increasing their potential use in intervention research. Continued research is needed to examine and validate the most recent devices on the market to better inform intervention design and implementation.

Early myopericarditis diagnosed in a 31-year-old patient using smartwatch technology: A case report

INTRODUCTION

Smartwatches, wrist-mounted devices with computing capacity able to connect with other devices via short-range wireless networking, are today commonly used by the general population to monitor their health status using specific applications. Currently, these devices offer new possibilities in remote health care monitoring and integration with other applications, through alert notifications, collection of personal data by a variety of sensors and the storage of these data. Several companies are introducing smartwatches with "health status" monitoring software with multiple functions, i.e. electrocardiogram (ECG) sensors. Recently, detection of atrial fibrillation based on heart rate monitoring by optical sensors resulted to be feasible and reliable when using the Apple Watch® and its corresponding application. Indeed, previous case reports highlighted its sensitivity in detecting morphological changes typical of the Acute Coronary Syndrome.

CASE REPORT

We report the case of a healthcare worker, who experienced chest pain and diffuse myalgia, detected ECG alterations in the ST segment, and reached the Emergency Department Myopericarditis was diagnosed and treated promptly to prevent complications.

DISCUSSION

Acute viral myocarditis and pericarditis are clinical conditions, usually characterized by 21 a benign course that does not require medical evaluation. However, ventricular arrhythmias are also common in viral myocarditis, and the latter is associated with a large proportion of sudden cardiac deaths in the young population without previous structural heart disease. In this case report, smartwatch technology allowed the preventive implementation of interventions against potentially life-threatening complications. Further developments in smartwatch technology could lead to more sensitive and specific diagnostic algorithms for conditions that require immediate medical intervention.