Wrist-worn Device Research Articles

Actigraphy methodology in the Kids Mod PAH trial: Physical activity as a functional endpoint in pediatric clinical trials.

Pulmonary vasodilator treatment can improve hemodynamics, right ventricular function, symptoms, and survival in pediatric pulmonary hypertension (PH). However, clinical trial data are lacking due to many constraints. One major limitation is the lack of relevant trial endpoints reflective of hemodynamics or functional status in patients in whom standard exercise testing is impractical, unreliable, or not reproducible. The Kids Mod PAH trial (Mono- vs. Duo Therapy for Pediatric Pulmonary Arterial Hypertension) is an ongoing multicenter, Phase III, randomized, open-label, pragmatic trial to compare the safety and efficacy of first-line combination therapy (sildenafil and bosentan) to first-line monotherapy (sildenafil alone) in 100 pediatric patients with PH across North America. Investigators will measure participants' physical activity with a research-grade, wrist-worn actigraphy device at multiple time points as an exploratory secondary outcome. Vector magnitude counts per minute and activity intensity will be compared between the treatment arms. By directly and noninvasively measuring physical activity in the ambulatory setting, we aim to identify a novel, simple, inexpensive, and highly reproducible approach for quantitative assessment of exercise tolerance in pediatric PH. These data will increase the field's understanding of the effect of pulmonary vasodilator treatment on daily activity - a quantitative measure of functional status and wellbeing in pediatric PH and a potential primary outcome for future clinical trials in children with cardiopulmonary disorders.

Association of Physical Activity and Sleep Metrics with Depression in People with Type 1 Diabetes.

This study aimed to investigate the association of physical activity and sleep metrics, measured via wrist-worn accelerometers, with depression in people with type 1 diabetes. People with type 1 diabetes were recruited from the Dasman Diabetes Institute in Kuwait and were invited to wear a wrist-worn accelerometer device for 7 days. Mean physical activity (overall acceleration), inactivity, light activity, moderate activity, vigorous activity, the distribution of physical activity intensity (intensity gradient), sleep duration and sleep efficiency were quantified from the accelerometer data. The associations of these metrics with depression were investigated using multiple linear regression. A total of 551 people with type 1 diabetes (age 33.1 (9.5) years) were included. Overall physical activity (B = -0.09, CI = -0.14 to -0.04), moderate intensity activity (B = -0.02, CI = -0.02 to -0.01), vigorous intensity activity (B = -0.16, CI = -0.27 to -0.05), and the intensity gradient (B = -2.11, CI = -3.51 to -0.72) were negatively associated with depression score (p < 0.01) and these associations remain significant even after adjustment for age, sex, diabetes duration, and BMI. However, sleep duration and efficiency were not associated with depression. After mutual adjustment overall physical activity (B = -0.07, CI = -0.12 to -0.01), but not the intensity gradient (B = -0.90, CI = -2.47 to 0.68), remained associated with depression. Overall, moderate and vigorous physical activity, and the intensity gradient were associated with lower symptoms of depression. Overall physical activity, rather than the distribution of activity intensity, appears more important in depression. This information can help guide physical activity interventions to improve depression in people with type 1 diabetes.

Paranoid Operating System: Wearable Trackers

The use of wearable devices in conjunction with smartphone applications is at an all-time high and still growing daily. These devices communicate between themselves as well as with remote servers, and research indicates that all these communication bridges create some security and privacy-related issues. This paper will discuss and analyze the difference between a low-end and a high-end wrist wearable device in terms of their security and privacy measures. It will focus the results on what can be obtained from analyzing the Bluetooth communication and the device’s official mobile application.

Association between cardiac event-induced PTSD symptoms and daily intrusive thoughts about cardiac risk: An ecological momentary assessment study

ObjectivePosttraumatic stress symptoms (PSS) due to acute cardiac events are common and may lead patients to avoid secondary prevention behaviors. However, patients' daily experience of cardiac event-induced PSS has not been studied after a potentially traumatic cardiac hospitalization. MethodIn an observational cohort study, 108 mostly male patients with coronary heart disease were recruited after evaluation for suspected acute coronary syndrome (ACS). One month later, PSS were assessed via telephone-administered PTSD Checklist for DSM-5 (PCL-5). The exposure of interest was elevated (PCL-5 ≥ 20) vs. non-elevated PSS (PCL-5 ≤ 5). The occurrence and severity of cardiac-related intrusive thoughts were assessed 5 times daily for 2 weeks via electronic surveys on a wrist-worn device. ResultsModerate-to-severe intrusive thoughts were experienced by 48.1% of patients but more commonly by elevated-PSS (n = 36; 66.7%) than non-elevated-PSS (n = 72; 38.9%) patients. After adjustment for demographic and clinical characteristics, elevated- vs. non-elevated-PSS patients had a 9-fold higher odds of experiencing a moderate-to-severe intrusive thought during each 2-h assessment interval (adjusted OR = 9.14, 95% CI [2.99, 27.92], p < .01). After adjustment, intrusive thoughts on a 0-to-6 point scale were over two times as intense for elevated-PSS vs. non-elevated-PSS patients. ConclusionsIntrusive thoughts about cardiac risk were common in patients recently evaluated for ACS, but much more prevalent and intense in those with elevated vs non-elevated PSS.

Feasibility and acceptability of an ultra-long-term at-home EEG monitoring system (EEG@HOME) for people with epilepsy

BackgroundRecent technological advancements offer new ways to monitor and manage epilepsy. The adoption of these devices in routine clinical practice will strongly depend on patient acceptability and usability, with their perspectives being crucial. Previous studies provided feedback from patients, but few explored the experience of them using independently multiple devices independently at home. PurposeThe study, assessed through a mixed methods design, the direct experiences of people with epilepsy independently using a non-invasive monitoring system (EEG@HOME) for an extended duration of 6 months, at home. We aimed to investigate factors affecting engagement, gather qualitative insights, and provide recommendations for future home epilepsy monitoring systems. Materials and methodsAdults with epilepsy independently were trained to use a wearable dry EEG system, a wrist-worn device, and a smartphone app for seizure tracking and behaviour monitoring for 6 months at home. Monthly acceptability questionnaires (PSSUQ, SUS) and semi-structured interviews were conducted to explore participant experience. Adherence with the procedure, acceptability scores and systematic thematic analysis of the interviews, focusing on the experience with the procedure, motivation and benefits and opinion about the procedure were assessed. ResultsTwelve people with epilepsy took part into the study for an average of 193.8 days (range 61 to 312) with a likelihood of using the system at six months of 83 %. The e-diary and the smartwatch were highly acceptable and preferred to a wearable EEG system (PSSUQ score of 1.9, 1.9, 2.4). Participants showed an acceptable level of adherence with all solutions (Average usage of 63 %, 66 %, 92 %) reporting more difficulties using the EEG twice a day and remembering to complete the daily behavioural questionnaires. Clear information and training, continuous remote support, perceived direct and indirect benefits and the possibility to have a flexible, tailored to daily routine monitoring were defined as key factors to ensure compliance with long-term monitoring systems. ConclusionsEEG@HOME study demonstrated people with epilepsy' interest and ability in active health monitoring using new technologies. Remote training and support enable independent home use of new non-invasive technologies, but to ensure long term acceptability and usability systems will require to be integrated into patients' routines, include healthcare providers, and offer continuous support and personalized feedback.

Feasibility of a novel wearable thermal device for management of bothersome hot flashes in patients with prostate cancer

BackgroundThis single-arm prospective study evaluated the feasibility of a novel wrist-worn thermal device that applies cooling to the inside of the wrist for management of bothersome hot flashes in prostate cancer survivors.Methods57 individuals were enrolled and instructed to use the thermal device as needed for management of hot flashes for 4 weeks. The primary outcome was thermal device usage (hours and sessions per day). Additional outcomes included the change in Hot Flash Related Daily Interference Scale (HFRDIS, range 0–10) and Patient Reported Outcomes Measurement Information System Sleep Disturbance 4a (PROMIS SD T-score, range 0–100) and Sleep-Related Impairment 8a (PROMIS SRI T-score, range 0–100). Study procedures were conducted remotely from May to Dec 2021 in the US.Results44 participants completed the study and 39 had retrievable usage data. The mean ± SD age was 67 ± 6 years and 5 ± 5 years since cancer diagnosis. The baseline mean ± SD HFRDIS score of 4.3 ± 2.0 indicated moderate hot flash interference in this population. During the study, participants used the thermal device (mean ± SD) 3.2 ± 2.5 hours/day and 7.6 ± 3.6 sessions/day. Most (67%) participants reported using the device 7 days and 7 nights each week. Statistically significant improvements from baseline at Week 4 were observed for HFRDIS (mean ± SE change: −1.1 ± 0.3), PROMIS SD (−6.0 ± 1.0), and PROMIS SRI (−5.5 ± 1.2) scores (all p < 0.001). The majority (69%) of participants reported that the thermal device was effective at helping them manage hot flashes. No adverse events were reported.ConclusionsResults support the feasibility of using the thermal device for management of bothersome hot flashes in prostate cancer survivors. Future randomized controlled studies are warranted to evaluate the impact of the thermal device on frequency and severity of hot flashes, sleep quality, fatigue, and overall quality of life.

Detection of important features and comparison of datasets for fall detection based on wrist-wearable devices

Detection of important features and comparison of datasets for fall detection based on wrist-wearable devices

Abstract PR005: Preferences of older cancer survivors for integration of remote activity monitoring using wearable devices

Abstract Purpose: To describe the preferences for integration of wearable devices into their healthcare to remotely monitor physical activity among older adult cancer survivors. Methods: 89 cancer survivors, aged 65 and older, completed our preferences for wearable devices in healthcare questionnaire. Participants were asked to self-report demographic information, current physical activity participation, and preferences for inclusion of wearable devices as part of their care plan through a current provider (i.e. physician, physical therapist, etc.). Data are summarized and reported as mean ± standard deviation or percent. Results: Participants were on average 71±5 years old, 59% female, and mostly White, non-Hispanic (93%). 76.2% of participants reporting engaging in 0 days of vigorous intensity physical activity, with 31% reporting no moderate intensity physical activity. 59% of older cancer survivors report they already own a wearable device, with the most common device being a wrist-worn device (93%). For those that do not currently own a device, 94% report they would be interested in owning a wearable device. 94% of older cancer survivors state they would be interested in using a wearable device as part of their usual care plan for their provider to remotely monitor their health. 88% report having no privacy concerns with sharing their wearable data with their healthcare provider. Participants report they would be willing to purchase their own monitor if it meant future out of pocket healthcare costs (81%) or reduced time investment to travel to the clinic (63%). Conclusions: Results indicate older cancer survivors are interested in their care team remotely monitoring their activity levels. Further, the majority of older cancer survivors report they are willing to purchase their own device. Future research is warranted to determine an implementation plan to integrate these devices into current clinic workflows and determine optimal interaction among patients and providers. Citation Format: Whitney A. Morelli, Kelly Clohesey, Jessica Liu. Preferences of older cancer survivors for integration of remote activity monitoring using wearable devices [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR005.

Systematic Review of Accelerometer Responsiveness to Change for Measuring Physical Activity, Sedentary Behavior, or Sleep

Measurement of 24-hr movement behaviors is important for assessing adherence to guidelines, participation trends over time, group differences, and whether health-promoting interventions are successful. For a measurement tool to be useful, it must be valid, reliable, and able to detect change, the latter being a measurement property called responsiveness, sensitivity to change, or longitudinal validity. We systematically reviewed literature on the responsiveness of accelerometers to detect change in 24-hr movement behaviors. Databases (PubMed, Scopus, and EBSCOHost) were searched for peer-reviewed papers published in English between 1998 and 2023. Quality/risk of bias was assessed using a customized tool. This study is registered at https://osf.io/qrn8a. Twenty-six papers met the inclusion/exclusion criteria with an overall sample of 1,939 participants. Narrative synthesis was used. Most studies focused on adults (n = 21), and almost half (n = 12) included individuals with specific medical conditions. Studies primarily took place in free-living settings (n = 21) and used research-grade accelerometers (n = 24) worn on the hip (n = 18), thigh (n = 7), or wrist (n = 9). Outcomes included physical activity (n = 19), sedentary time/behavior (n = 12), or sleep (n = 2) and were calculated using proprietary formulas (e.g., Fitbit algorithm), cut points, and/or count-based methods. Most studies calculated responsiveness by comparing before versus after an intervention (n = 16). Six studies included a criterion measure to confirm that changes occurred. Limited research is available on the responsiveness of accelerometers for detecting change in 24-hr movement behaviors, particularly in youth populations, for sleep outcomes, and for commercial and thigh- or wrist-worn devices. Lack of a criterion measure precludes conclusions about the responsiveness even in more frequently studied outcomes/populations.

Investigation of physiological responses on drone noise in a laboratory condition

This study analyzed the impact of drone noise on human physiology in a laboratory environment using recorded data. It focused on the noise generated by drones during hovering flight. Two drone noises with various spectral characteristics were collected through the field measurements. To assess the effect of immersion, subjects were exposed to both auditory and visual stimuli, including images and videos of the drones. Physiological responses were recorded using a 14-channel EEG device and a wrist-worn device that monitored HR, IBI, EDA, and skin temperature. A preliminary experiment was conducted with four subjects to evaluate the differences in drone types and individual physiological responses. The study also analyzed the relationship between physiological responses and physical noise characteristics and explored methods to reduce noise during physiological response collection.

Feasibility, Acceptability, and Usability of Physiology and Emotion Monitoring in Adults and Children Using the Novel Time2Feel Smartphone Application

The present study tests the feasibility, acceptability, and utility of the novel smartphone application—Time2Feel—to monitor family members’ emotional experiences, at the experiential and physiological level, and their context. To our knowledge, Time2Feel is the first of its kind, having the capability to monitor multiple members’ emotional experiences simultaneously and survey users’ emotional experiences when experiencing an increase in physiological arousal. In this study, a total of 44 parents and children used Time2Feel along with the Empatica E4 wrist-wearable device for 10 days. Engagement rates were within the acceptable range and consistent with previous work using experience sampling methods. Perceived ease of use and satisfaction fell mostly in the moderate range, with users reporting challenges with connectivity. We further discuss how addressing connectivity would increase acceptability. Finally, Time2Feel was successful at identifying physiological deviations in electrodermal activity for parents and children alike, and even though responses to those deviation-generated surveys were largely consistent with random survey responses, some differences were noted for mothers and fathers. We discuss the implications of using Time2Feel for understanding families’ emotional and stressful experiences day-to-day.

Interactive effects of physical activity and sarcopenia on incident ischemic heart disease: Results from a nation-wide cohort study

Background and aimsLack of physical activity (PA) and sarcopenia is a known risk factors for ischemic heart disease (IHD). However, considering their coexistence in the middle-aged and elderly population, the interaction of these two factors remains uncertain. Here, we investigated the interactive effects of PA and sarcopenia on IHD. MethodsWe extracted 344,688 participants free of IHD at baseline from the UK Biobank. PA was classified into low, moderate, and high according to the International Physical Activity Questionnaire. Sarcopenia was identified in accordance with the European Working Group on Sarcopenia in Older People 2. Cox proportional hazard models were applied to estimate the effect of PA and sarcopenia on incident IHD and its subtypes. We also used objective PA data measured by wrist-worn devices to repeat these analyses. ResultsOver a median follow-up of 11.7 years, 24,809 (7.2%) participants developed incident IHD. Lack of PA was associated with a higher risk of IHD after adjusting for potential confounders. The hazard ratio (HR) was 1.09 (95% CI: 1.05–1.13) for individuals without sarcopenia and 1.29 (95% CI: 1.17–1.42) for those with sarcopenia. Regarding the joint effect, the combination of low PA and sarcopenia was associated with the highest risk of IHD, with an HR of 1.54 (95% CI: 1.44–1.66), and both additive and multiplicative interactions were significant (RERI 0.27, 95% CI: 0.14–0.39, p-interaction <0.01). For subtypes of IHD, the interaction was pronounced in acute myocardial infarction and chronic ischemic heart disease. ConclusionsThese results suggest a synergistic interaction between lack of PA and sarcopenia on the risk of IHD. Findings from this study may help facilitate more effective primary prevention of IHD.

Monitoring SpO2, Heart Rate, and Body Temperature on Smartband with Data Sending Use IoT Displayed on Android (SpO2)

The patient's health must not deteriorate if treatment is not started right away if they show indications of a disease. Monitoring is the most important thing that needs to be done to ascertain the patient's state, especially for those with lung illness who have asthma and pneumonia with moderate symptoms. SpO2, BPM, and body temperature are vital signs that can be used as indicators of a person's degree of health. The main goal of this project was to create wearable devices index finger then a wrist-worn devices that can measure SpO2, Heart rate, and body temperature in real time, regardless of distance, and alert users' smartphones when a patient's condition is abnormal. The body temperature is measured using the MLX90614 sensor, positioned on the wrist, whereas the Oxygen saturation and Heart rate are measured with MAX30100 sensor, placed on the index finger. The ESP32 Microcontroller processes the sensor data after which the results are displayed on the TFT Display GC9A01 and to Ubidots application on a smartphone or computer. When the SpO2, BPM, and Temperature values drop below the predetermined range, Ubidots sends an alert message to the associated email address on the smartphone or computer. In comparison to BPM, which had the lowest error is 0.06% and highest at 5.65%, and temperature, which had the least error value of 0.1% and the most 0.88%, SpO2 had the lowest error is 0.2% and biggest error at 1.6%. MAX30100 sensor, which serves as a processor for SpO2 and Heart rate values on the index finger, delivers a good response when utilized by respondents, according to the smart band's manufacturer. The results of data measurement can also be shown on LCD TFT GC9A01 and Ubidots applications. This device will be kept in a hospital, clinic, or utilized on its own at home. Additionally, regardless of the distance, this application is anticipated to assist families or medical personnel in keeping track of the health of senior patients.

Predicting Obsessive-Compulsive Disorder Events in Children and Adolescents in the Wild using a Wearable Biosensor (Wrist Angel): Protocol for the Analysis Plan of a Nonrandomized Pilot Study.

Physiological signals such as heart rate and electrodermal activity can provide insight into an individual's mental state, which are invaluable information for mental health care. Using recordings of physiological signals from wearable devices in the wild can facilitate objective monitoring of symptom severity and evaluation of treatment progress. We designed a study to evaluate the feasibility of predicting obsessive-compulsive disorder (OCD) events from physiological signals recorded using wrist-worn devices in the wild. Here, we present an analysis plan for the study to document our a priori hypotheses and increase the robustness of the findings of our planned study. In total, 18 children and adolescents aged between 8 and 16 years were included in this study. Nine outpatients with an OCD diagnosis were recruited from a child and adolescent mental health center. Nine youths without a psychiatric diagnosis were recruited from the catchment area. Patients completed a clinical interview to assess OCD severity, types of OCD, and number of OCD symptoms in the clinic. Participants wore a biosensor on their wrist for up to 8 weeks in their everyday lives. Patients were asked to press an event tag button on the biosensor when they were stressed by OCD symptoms. Participants without a psychiatric diagnosis were asked to press this button whenever they felt really scared. Before and after the 8-week observation period, participants wore the biosensor under controlled conditions of rest and stress in the clinic. Features are extracted from 4 different physiological signals within sliding windows to predict the distress event logged by participants during data collection. We will test the prediction models within participants across time and multiple participants. Model selection and estimation using 2-layer cross-validation are outlined for both scenarios. Participants were included between December 2021 and December 2022. Participants included 10 female and 8 male participants with an even sex distribution between groups. Patients were aged between 10 and 16 years, and adolescents without a psychiatric diagnosis were between the ages of 8 and 16 years. Most patients had moderate to moderate to severe OCD, except for 1 patient with mild OCD. The strength of the planned study is the investigation of predictions of OCD events in the wild. Major challenges of the study are the inherent noise of in-the-wild data and the lack of contextual knowledge associated with the recorded signals. This preregistered analysis plan discusses in detail how we plan to address these challenges and may help reduce interpretation bias of the upcoming results. If the obtained results from this study are promising, we will be closer to automated detection of OCD events outside of clinical experiments. This is an important tool for the assessment and treatment of OCD in youth. ClinicalTrials.gov NCT05064527; https://clinicaltrials.gov/study/NCT05064527. DERR1-10.2196/48571.

NCOG-20. WEARABLE DEVICE DATA QUANTIFY DISEASE PROGRESSION IN HIGH GRADE GLIOMA AND MAY PROVIDE NOVEL OUTCOME MEASURES

Abstract BACKGROUND Functional status is a prognostic measure of survival in high grade glioma (HGG). Real-time monitoring between clinical encounters can extend the reach of care and provide actionable insights to drive more personalized and proactive care. We present data from the completed BrainWear Study, a highly novel study evaluating if data captured via a wrist-worn wearable device in patients with HGG can be used to explain, influence and/or predict cancer-related outcomes. Materials and METHODS All participants agreed to wear a wrist-worn Axivity AX3 triaxial accelerometer changed at 14-day intervals. Raw accelerometer data was processed using the UKBiobank Accelerometer analysis package v6.2.3 for Python and inclusion of high-quality wear time selected as ≥72 hours of data over 7-days. We analysed variation in activity by patient demographics and MRI result utilising the Response Assessment in Neuro-Oncology (RANO) criteria. Patient reported outcomes (PROs) were completed at planned study timepoints. Wilcoxin-signed rank test was used to compare participant activity at timepoints of stable or progressive disease (PD). Mixed-effects models were used to evaluate changes in activity. RESULTS 12512 days of accelerometer data were recorded from 56 patients (36 male; 20 female) with a median age of 60 years. 80% of the data were characterised as high-quality. Mean acceleration(mg) and time spent walking daily(h/day) correlated positively with the global health QOL and physical functioning scores and inversely with the fatigue score from PROs. In the 6-weeks surrounding an MRI scan, patients with PD walked on average 1856 steps less per day than those with stable disease, and spent 22 minutes less walking (p=0.0403). Several wearable data daily physical activity measures demonstrated statistically significant change at the time of PD. CONCLUSION Remote monitoring data can complement snapshots of health gathered during clinical visits. Collection of digital data hold promise for novel HGG trial outcome measure development.

Fully automatic screening for atrial fibrillation using a photoplethysmography based wristband and a novel smart infrastructure

Abstract Background Atrial Fibrillation (AF) is the leading cause of stroke, and its prevalence is expected to rise. While early detection is crucial in preventing thromboembolic events, its often asymptomatic and paroxysmal nature makes it challenging to capture using conventional electrocardiography (ECG). Photoplethysmography (PPG) enabled devices, such as smartwatches, allow continuous monitoring of the heart rhythm and accurate screening for AF. Purpose In this study, we aimed to build an IT-infrastructure for fully automated screening of AF in hospitalised patients at risk using a PPG-based wrist worn wearable device. Methods We conducted an investigator-initiated, prospective, clinical trial to evaluate the performance of a PPG-based wristband coupled to an automatic data process device hub in hospitalised patients. Participants with a CHA2DS2-VASc score of two or higher and no prior history of AF were eligible for the study. Consenting participants received a wristband with a built-in PPG sensor to be worn during the entire hospital stay. Data from the wristband was automatically transmitted, stored, analysed and visualised. When absolute arrhythmia (AA) was detected in the PPG signal, a subsequent seven-day Holter ECG was performed to confirm the diagnosis. Results A total of 346 patients were included in the analysis (age 72 ± 10 years; 175 females (50.6%); mean CHA2DS2-VASc score of 3.5 ± 1.3). No data was lost in the process. The mean monitoring time was 4.3 ± 4.4 days, 45.9% was evaluable. In twelve patients (3.5%, CI: 1.5% - 5.4%) absolute arrhythmia (AA) was detected in the PPG-signal. The mean screening time until first detection of AA was 14.7 ± 16.8 hours. The highest detection rate was observed within the first 24 hours of screening (p = 0.004) (Figure 1). The AA burden per hour was 1.9 times greater during the night (22:00 - 06:00) compared to the day (p = 0.003) (Figure 2). Of the 346 patients, 304 (87.9%) were compliant in wearing the wristband for the entire hospitalisation. In nine patients a Holter ECG was recorded, no AF was identified. Conclusions We successfully established an infrastructure for automated AF screening in hospitalised patients using wrist-worn PPG devices, enabling real-time visualisation of incoming data and facilitating therapeutic interventions with minimal delay. To our knowledge this is the first hospital to implement a fully automated AF screening infrastructure based on PPG devices. In a population at risk, AA was identified in 3.5% of all patients. The high compliance rate of the wearable device further supports its feasibility and utility in clinical practice.Figure 1:Time to first detection of AAFigure 2:Total AA burden per hour

Multimorbidity is associated with lower total 24-hour movement activity among US adults

ObjectiveHaving chronic conditions may result in reduced physical and cognitive function but less is known about multimorbidity with daily movement. We examined the association of multimorbidity and device-measured total daily movement in a nationally representative sample of US adults aged ≥ 30 years from the 2011–2014 National Health and Nutrition Examination Surveys. MethodsAny multimorbidity (≥2 conditions) and complex multimorbidity (≥3 conditions across ≥ 3 body systems) were quantified using 16 chronic conditions via self-report and/or clinical thresholds. Total movement over 24-hours (Monitor-Independent Movement Summary units [MIMS-units]) was measured using a wrist-worn device (ActiGraph GT3X). Multivariable linear regression examined the association of 1) each chronic condition, 2) number of conditions, 3) any multimorbidity, and 4) complex multimorbidity with total movement. Covariates included age, gender, race/ethnicity, educational attainment, and smoking status. ResultsAmong US adults (N = 7304, mean age: 53.2 ± 0.34 years, 53.2% female, 69.4% Non-Hispanic White), 62.2% had any multimorbidity with 34.2% having complex multimorbidity. After adjustment, a higher number of chronic conditions was associated with incrementally lower total movement (β MIMS-units [95% CI] compared to those with no chronic conditions; one: −419 [−772, −66], two: −605 [−933, −278], three: −1201 [−1506, −895], four: −1908 [−2351, −1465], 5+: −2972 [−3384, −2560]). Complex multimorbidity presence was associated with −1709 (95% CI: −2062, −1357) and −1269 (−1620, −918) lower total movement compared to those without multimorbidity and multimorbidity but not complex, respectively. ConclusionsMultimorbidity was associated with lower 24-h movement among US adults and may be helpful for identifying adults at risk for low movement.

Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?

Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant's naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients' comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities.

Adaptive Signal-to-Noise Ratio Indicator for Wearable Bioimpedance Monitoring.

Bioimpedance monitoring is an increasingly important non-invasive technique for assessing physiological parameters such as body composition, hydration levels, heart rate, and breathing. However, sensor signals obtained from real-world experimental conditions invariably contain noise, which can significantly degrade the reliability of the derived quantities. Therefore, it is crucial to evaluate the quality of measured signals to ensure accurate physiological parameter values. In this study, we present a novel wrist-worn wearable device for bioimpedance monitoring, and propose a method for estimating signal quality for sensor signals obtained on the device. The method is based on the continuous wavelet transform of the measured signal, identification of wavelet ridges, and assessment of their energy weighted by the ridge duration. We validate the algorithm using a small-scale experimental study with the wearable device, and explore the effects of variables such as window size and different skin/electrode coupling agents on signal quality and repeatability. In comparison with traditional wavelet-based signal denoising, the proposed method is more adaptive and achieves a comparable signal-to-noise ratio.

Testing the Effects of App-Based Motivational Messages on Physical Activity and Resting Heart Rate Through Smartphone App Compliance in Patients With Vulnerable Coronary Artery Plaques: Protocol for a Microrandomized Trial.

Achieving the weekly physical activity recommendations of at least 150-300 minutes of moderate-intensity or 75-150 minutes of vigorous-intensity aerobic exercise is important for reducing cardiometabolic risk, but evidence shows that most people struggle to meet these goals, particularly in the mid to long term. The Messages Improving Resting Heart Health (MIRTH) study aims to determine if (1) sending daily motivational messages through a research app is effective in improving motivation and in promoting adherence to physical activity recommendations in men and women with coronary heart disease randomized to a 12-month intensive lifestyle intervention, and (2) the time of the day when the message is delivered impacts compliance with exercise training. We will conduct a single-center, microrandomized trial. Participants will be randomized daily to either receive or not receive motivational messages over two 90-day periods at the beginning (phase 1: months 4-6) and at the end (phase 2: months 10-12) of the Lifestyle Vulnerable Plaque Study. Wrist-worn devices (Fitbit Inspire 2) and Bluetooth pairing with smartphones will be used to passively collect data for proximal (ie, physical activity duration, steps walked, and heart rate within 180 minutes of receiving messages) and distal (ie, change values for resting heart rate and total steps walked within and across both phases 1 and 2 of the trial) outcomes. Participants will be recruited from a large academic cardiology office practice (Central Sydney Cardiology) and the Royal Prince Alfred Hospital Departments of Cardiology and Radiology. All clinical investigations will be undertaken at the Charles Perkins Centre Royal Prince Alfred clinic. Individuals aged 18-80 years (n=58) with stable coronary heart disease who have low attenuation plaques based on a coronary computed tomography angiography within the past 3 months and have been randomized to an intensive lifestyle intervention program will be included in MIRTH. The Lifestyle Vulnerable Plaque Study was funded in 2020 and started enrolling participants in February 2022. Recruitment for MIRTH commenced in November 2022. As of September 2023, 2 participants were enrolled in the MIRTH study and provided baseline data. This MIRTH microrandomized trial will represent the single most detailed and integrated analysis of the effects of a comprehensive lifestyle intervention delivered through a customized mobile health app on smart devices on time-based motivational messaging for patients with coronary heart disease. This study will also help inform future studies optimizing for just-in-time adaptive interventions. Australian New Zealand Clinical Trials Registry ACTRN12622000731796; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382861. DERR1-10.2196/46082.