BACKGROUND: Opioid overdose is a global health crisis, affecting over 27 million individuals worldwide, with more than 100,000 drug overdose deaths in the United States in 2022-2023. This protocol outlines the development of the PneumoWave chest biosensor, a wearable device being designed to detect respiratory depression in real time through chest motion measurement, intending to enhance early intervention and thereby reduce fatalities.
OBJECTIVE: The study aims to (1) differentiate opioid-induced respiratory depression (OIRD) from nonfatal opioid use patterns to develop and refine an overdose detection algorithm and (2) examine participants\' acceptability of the chest biosensor.
METHODS: The study adopts an observational design over a 6-month period. The biosensor, a small device, will be worn by consenting participants during injecting events to capture chest motion data. Safe injecting facilities (SIF) in Melbourne, Victoria (site 1), and Sydney, New South Wales (site 2), which are legally sanctioned spaces where individuals can use preobtained illicit drugs under medical supervision. Each site is anticipated to recruit up to 100 participants who inject opioids and attend the SIF. Participants will wear the biosensor during supervised injecting events at both sites. The biosensor will attempt to capture data on an anticipated 40 adverse drug events. The biosensor\'s ability to detect OIRD will be compared to the staff-identified events that use standard protocols for managing overdoses. Measurements will include (1) chest wall movement measured by the biosensor, securely streamed to a cloud, and analyzed to refine an overdose detection algorithm and (2) acute events or potential overdose identified by site staff. Acceptability will be measured by a feedback questionnaire as many times as the participant is willing to throughout the study.
RESULTS: As of April 2024, a total of 47 participants have been enrolled and data from 1145 injecting events have already been collected, including 10 overdose events. This consists of 17 females and 30 males with an average age of 45 years. Data analysis is ongoing.
CONCLUSIONS: This protocol establishes a foundation for advancing wearable technology in opioid overdose prevention within SIFs. The study will provide chest wall movement data and associated overdose data that will be used to train an algorithm that allows the biosensor to detect an overdose. The study will contribute crucial insights into OIRD, emphasizing the biosensor\'s potential step forward in real-time intervention strategies.
UNASSIGNED: DERR1-10.2196/57367.

UNASSIGNED: Electrical stimulation (ES) has been shown to substantially enhance the quality of life by alleviating pain in patients with chronic wounds. This study aimed to observe the effects of low-frequency pulsed wearable ES at the common peroneal nerve on chronic refractory wounds of the lower limb.
UNASSIGNED: Forty-eight participants were randomly divided into control group (n = 24) and treatment group (n = 24) in this study. The control group received standard wound care (SWC) exclusively, whereas the treatment group was administered both SWC and the wearable low-frequency ES targeting the common peroneal nerve. Measurements of wound area, pain intensity, wound status, and quality of life scores were systematically recorded both before and after 4 weeks treatment.
UNASSIGNED: After 4 weeks of intervention, the percentage area reduction was significantly higher in the treatment group compared to the control group (Z = -3.9, p < 0.001), and the healing rate of the treatment group was significantly higher than that of the control group (33% vs. 4%). Moreover, the visual Analog Scale for Pain score (β = -0.65, p = 0.019), the Bates-Jensen Wound Assessment Tool score (p < 0.05), and the questionnaire on quality of life with chronic wounds (Wound-Qol) score (β = -4.23, p = 0.003) were significantly decreased in the patients in the treatment group compared to the control group.
UNASSIGNED: The wearable low-frequency pulsed ES at the common peroneal nerve for the treatment of chronic refractory wounds showed significant improvement and were far superior compared to SWC. Future research should broaden its scope to include a diverse range of wound types and benefit from collaboration across multiple research centers.

BACKGROUND: The number of individuals using digital health devices has grown in recent years. A higher rate of use in patients suggests that primary care providers (PCPs) may be able to leverage these tools to effectively guide and monitor physical activity (PA) for their patients. Despite evidence that remote patient monitoring (RPM) may enhance obesity interventions, few primary care practices have implemented programs that use commercial digital health tools to promote health or reduce complications of the disease.
OBJECTIVE: This formative study aimed to assess the perceptions, needs, and challenges of implementation of an electronic health record (EHR)-integrated RPM program using wearable devices to promote patient PA at a large urban primary care practice to prepare for future intervention.
METHODS: Our team identified existing workflows to upload wearable data to the EHR (Epic Systems), which included direct Fitbit (Google) integration that allowed for patient PA data to be uploaded to the EHR. We identified pictorial job aids describing the clinical workflow to PCPs. We then performed semistructured interviews with PCPs (n=10) and patients with obesity (n=8) at a large urban primary care clinic regarding their preferences and barriers to the program. We presented previously developed pictorial aids with instructions for (1) providers to complete an order set, set step-count goals, and receive feedback and (2) patients to set up their wearable devices and connect them to their patient portal account. We used rapid qualitative analysis during and after the interviews to code and develop key themes for both patients and providers that addressed our research objective.
RESULTS: In total, 3 themes were identified from provider interviews: (1) providers\' knowledge of PA prescription is focused on general guidelines with limited knowledge on how to tailor guidance to patients, (2) providers were open to receiving PA data but were worried about being overburdened by additional patient data, and (3) providers were concerned about patients being able to equitably access and participate in digital health interventions. In addition, 3 themes were also identified from patient interviews: (1) patients received limited or nonspecific guidance regarding PA from providers and other resources, (2) patients want to share exercise metrics with the health care team and receive tailored PA guidance at regular intervals, and (3) patients need written resources to support setting up an RPM program with access to live assistance on an as-needed basis.
CONCLUSIONS: Implementation of an EHR-based RPM program and associated workflow is acceptable to PCPs and patients but will require attention to provider concerns of added burdensome patient data and patient concerns of receiving tailored PA guidance. Our ongoing work will pilot the RPM program and evaluate feasibility and acceptability within a primary care setting.

UNASSIGNED: Lung function constraints and comorbidities such as coronary heart disease, sarcopenia, and mood disorders make chronic obstructive pulmonary disease (COPD) patients avoid physical activity (PA). However, PA represents an important pillar of COPD management and is explicitly recommended by professional associations to enhance physical functioning and positively modulate disease progression.
UNASSIGNED: In this monocentric, prospective, observational feasibility study, it was our primary objective to investigate the association between PA and the evolution of the COPD assessment test (CAT) and the occurrence of acute exacerbations of COPD (AECOPD), respectively. To this end, we equipped 42 COPD patients with an activity tracking wearable and telemonitored their daily PA levels over one year using a dedicated web-based interface. Patients additionally provided weekly CAT scores using the same telehealth platform and came in for 3 study visits to assess functional parameters and biochemical markers related to nutrition and inflammation.
UNASSIGNED: A principal study finding was that PA was inversely associated with CAT score (drop of 0.21 points associated with an increase of 1000 daily steps, p = 0.004), and that the 50% of patients with higher PA levels showed less CAT score progression over time (0.42 points per year) than the 50% of patients with lower PA levels (3.26 points per year) (p < 0.001). In addition, higher PA levels were significantly associated with a lower likelihood of experiencing a moderate-to-severe AECOPD (31% risk reduction associated with an increase of 1000 daily steps, p = 0.0097).
UNASSIGNED: Our study demonstrates the relevance of PA for key COPD outcome metrics in a real-world setting and underpins the importance of PA for COPD self-management in everyday life. Our study paves the way for future intervention trials to prospectively identify medically relevant PA thresholds and establish training recommendations for different patient subgroups.

BACKGROUND: Women with overweight (OW) and those with obesity (OB) tend to gain excessive weight during pregnancy, often resulting in adverse outcomes. The long-term effects of mobile health (mHealth) interventions on maternal and infant outcomes remain unclear.
OBJECTIVE: To examine the effects of an mHealth intervention on OW and OB from the course of their pregnancy to six months postpartum.
METHODS: A randomized controlled trial was conducted in northern Taiwan. Ninety-two pregnant women with a body mass index (BMI)of ≥25 kg/m2 were recruited from prenatal clinics at <17 weeks of gestation. Prepregnancy weight was baseline maternal weight, with data collected subsequently at the last assessment before childbirth and six months postpartum. The intervention group (IG) received the mHealth intervention, while the control group (CG) received standard antenatal care. The trial was registered on ClinicalTrials.gov (identifier: NCT04553731) with the initial registration date of September 16, 2020.
RESULTS: The IG tended to have a lower mean body weight than the CG at the last assessment before childbirth (82.23 kg vs 84.35 kg) and at six months postpartum (72.55 Kg vs 72.58 Kg). IG\'s newborn birth weight was significantly lower than CG\'s (3074.8 vs. 3313.6 g; p = 0.009). Regression analysis revealed that OB in IG had a significant reduction in weight before childbirth (β = -7.51, p = 0.005) compared to OB in CG. Compared to OW in CG, both OW in IG (β = -243.59, p = 0.027) and OB in IG (β = -324.59, p = 0.049) were associated with decreased newborn birth weight.
CONCLUSIONS: mHealth helped women with obesity to successfully manage their GWG and body weight before childbirth and newborns\' birth weight, despite this effect not persisting to reduce weight retention at six months postpartum.

BACKGROUND: Step counting is comparable among many research-grade and consumer-grade accelerometers in laboratory settings.
OBJECTIVE: The purpose of this study was to compare the agreement between Actical and Apple Watch step-counting in a community setting.
METHODS: Among Third Generation Framingham Heart Study participants (N=3486), we examined the agreement of step-counting between those who wore a consumer-grade accelerometer (Apple Watch Series 0) and a research-grade accelerometer (Actical) on the same days. Secondarily, we examined the agreement during each hour when both devices were worn to account for differences in wear time between devices.
RESULTS: We studied 523 participants (n=3223 person-days, mean age 51.7, SD 8.9 years; women: n=298, 57.0%). Between devices, we observed modest correlation (intraclass correlation [ICC] 0.56, 95% CI 0.54-0.59), poor continuous agreement (29.7%, n=957 of days having steps counts with ≤15% difference), a mean difference of 499 steps per day higher count by Actical, and wide limits of agreement, roughly ±9000 steps per day. However, devices showed stronger agreement in identifying who meets various steps per day thresholds (eg, at 8000 steps per day, kappa coefficient=0.49), for which devices were concordant for 74.8% (n=391) of participants. In secondary analyses, in the hours during which both devices were worn (n=456 participants, n=18,760 person-hours), the correlation was much stronger (ICC 0.86, 95% CI 0.85-0.86), but continuous agreement remained poor (27.3%, n=5115 of hours having step counts with ≤15% difference) between devices and was slightly worse for those with mobility limitations or obesity.
CONCLUSIONS: Our investigation suggests poor overall agreement between steps counted by the Actical device and those counted by the Apple Watch device, with stronger agreement in discriminating who meets certain step thresholds. The impact of these challenges may be minimized if accelerometers are used by individuals to determine whether they are meeting physical activity guidelines or tracking step counts. It is also possible that some of the limitations of these older accelerometers may be improved in newer devices.

UNASSIGNED: To assess the utility of wearable cameras in medical examinations, we created a physician-view video-based examination question and explanation, and the survey results indicated that these cameras can enhance the evaluation and educational capabilities of medical examinations.

BACKGROUND: The early detection of respiratory infections could improve responses against outbreaks. Wearable devices can provide insights into health and well-being using longitudinal physiological signals.
OBJECTIVE: The purpose of this study was to prospectively evaluate the performance of a consumer wearable physiology-based respiratory infection detection algorithm in health care workers.
METHODS: In this study, we evaluated the performance of a previously developed system to predict the presence of COVID-19 or other upper respiratory infections. The system generates real-time alerts using physiological signals recorded from a smartwatch. Resting heart rate, respiratory rate, and heart rate variability measured during the sleeping period were used for prediction. After baseline recordings, when participants received a notification from the system, they were required to undergo testing at a Northwell Health System site. Participants were asked to self-report any positive tests during the study. The accuracy of model prediction was evaluated using respiratory infection results (laboratory results or self-reports), and postnotification surveys were used to evaluate potential confounding factors.
RESULTS: A total of 577 participants from Northwell Health in New York were enrolled in the study between January 6, 2022, and July 20, 2022. Of these, 470 successfully completed the study, 89 did not provide sufficient physiological data to receive any prediction from the model, and 18 dropped out. Out of the 470 participants who completed the study and wore the smartwatch as required for the 16-week study duration, the algorithm generated 665 positive alerts, of which 153 (23.0%) were not acted upon to undergo testing for respiratory viruses. Across the 512 instances of positive alerts that involved a respiratory viral panel test, 63 had confirmed respiratory infection results (ie, COVID-19 or other respiratory infections detected using a polymerase chain reaction or home test) and the remaining 449 had negative upper respiratory infection test results. Across all cases, the estimated false-positive rate based on predictions per day was 2%, and the positive-predictive value ranged from 4% to 10% in this specific population, with an observed incidence rate of 198 cases per week per 100,000. Detailed examination of questionnaires filled out after receiving a positive alert revealed that physical or emotional stress events, such as intense exercise, poor sleep, stress, and excessive alcohol consumption, could cause a false-positive result.
CONCLUSIONS: The real-time alerting system provides advance warning on respiratory viral infections as well as other physical or emotional stress events that could lead to physiological signal changes. This study showed the potential of wearables with embedded alerting systems to provide information on wellness measures.

Sudden cardiac arrest during exercise can occur without prior warning signs at rest, highlighting the importance of monitoring for its prevention. To detect the signs of ischemic heart disease, including coronary artery anomalies, ST changes must be detected using three‑lead electrocardiograms (ECGs) corresponding to each region of the three coronary artery branches. We conducted ECG monitoring of five runners during a marathon using a wearable three‑lead ECG device (e-skin ECG; Xenoma Inc., Tokyo, Japan). Data without noise or artifacts were successfully collected for one of five runners during the entire marathon. Within the initial hour of the marathon, poor electrode adhesion to the skin hindered the data collection for the remaining four runners, which resulted in significantly decreased acquisition rate compared with the first hour (86.7 ± 13.4 % to 37.3 ± 36.9 %, p = 0.028). Couplets of premature ventricular contractions with clear ECG waveforms in the three leads were detected in one runner during the marathon. Further device improvements are necessary to enable marathon runners to obtain ECGs efficiently without affecting their performance. This study also demonstrated the potential applications of three‑lead wearable ECG monitoring for other short-duration sports and remote home-based cardiac rehabilitation.
UNASSIGNED: This is an initial trial of a three‑lead wearable electrocardiogram (ECG) monitoring device during a full marathon. ECG data were obtained with low noise and artifacts during the first hour of the marathon; however, the data acquisition rate decreased in the middle and late stages owing to poor electrode adhesion. This study demonstrated the possibility of applying wearable ECG monitoring during short-term exercise and cardiac rehabilitation to detect warning signs and prevent sudden cardiac arrest.

BACKGROUND: Obesity prevalence in youth with spina bifida is higher than in their typically developing peers. Obesity is associated with lifelong medical, psychological, and economic burdens. Successful prevention or treatment of obesity in individuals with spina bifida is compromised by (1) the lack of valid and reliable methods to identify body fat in a clinical setting and (2) limited data on energy expenditure that are necessary to provide daily caloric recommendations.
OBJECTIVE: The objectives of this study will be to develop 2 algorithms for use in youth with spina bifida in a clinical setting, one to model body fat and one to predict total daily energy expenditure. In addition, physical activity and dietary intake will be described for the sample.
METHODS: This multisite, prospective, national clinical study will enroll 232 youth with myelomeningocele aged 5 to 18 years (stratified by age and mobility). Participants will be enrolled for 1 week. Data obtained include 4 measures of body composition, up to 5 height measures, a ramped activity protocol, and a nutrition and physical activity screener. Participants will wear an accelerometer for the week. On the final study day, 2 samples of urine or saliva, which complete the doubly labeled water protocol, will be obtained. The analysis will include descriptive statistics, Bland-Altman plots, concordance correlation, and regression analysis.
RESULTS: The study received extramural federal funding in July 2019. Data collection was initiated in March 2020. As of April 2024, a total of 143 (female participants: n=76, 53.1%; male participants: n=67, 46.9%) out of 232 participants have been enrolled. Data collection is expected to continue throughout 2024. A no-cost extension until November 2025 will be requested for data analysis and dissemination of findings.
CONCLUSIONS: This study furthers previous pilot work that confirmed the acceptability and feasibility of obtaining alternate height, body composition, and energy expenditure measures. The findings from this study will enhance screening, prevention, and treatment of abnormal weight status by facilitating the accurate identification of youths\' weight status category and recommendations of daily caloric needs for this population that is at higher risk of obesity. Furthermore, the findings have the potential to impact outcomes for youth diagnosed with disabilities other than spina bifida who experience similar challenges related to alterations in body composition or fat distribution or measurement challenges secondary to mobility issues or musculoskeletal problems.
UNASSIGNED: DERR1-10.2196/52779.