Wearable Electronic Devices

The goal of this clinical trial is to examine how daily behavioral patterns in early pregnancy, including sleep, physical activity, and meal timing, influence continuous glucose dynamics and subsequent risk of gestational diabetes mellitus (GDM) in pregnant women without pre-existing diabetes. The main questions it aims to answer are: 1. Do early-pregnancy chronobehavioral patterns (e.g., irregular sleep, night eating, and unstable rest-activity rhythms) relate to continuous glucose patterns measured using continuous glucose monitoring (CGM)? 2. Can early behavioral and CGM-derived measures predict glucose regulation and metabolic outcomes later in pregnancy (24-28 weeks)? 3. Does real-time self-monitoring using wearable devices and food logging improve glycemic outcomes compared to usual care? This study is a prospective, nested randomized pilot trial embedded within the ongoing Towards Optimal Fertility, Fathering and Fatherhood studY (TOFFFY) cohort (NCT06293235) at KK Women's and Children's Hospital, Singapore. A total of 140 pregnant women without pre-existing diabetes, recruited at ≤13 weeks gestation, will be randomized in a 1:1 ratio to either a pilot arm (wearable-based self-monitoring) or a control arm (usual care). Participants in the pilot arm (n=70) will undergo intensive behavioral and metabolic monitoring over a 14-day period in early pregnancy, including continuous glucose monitoring using a CGM device, wrist actigraphy to assess sleep-wake and rest-activity patterns, and an AI-supported mobile application to record meal timing and dietary intake. Participants will have real-time access to their glucose data and behavioral feedback, enabling self-monitoring and potential behavioral adjustments.

DEL-DIP is a prospective observational study employing a Delphi methodology (at least two online rounds) to elicit and consolidate the views of an expert panel within the INNOPREV project. The study aims to develop operational recommendations to support the coordinated implementation of Polygenic Risk Scores (PRS) and wearable devices in cardiovascular prevention. Specifically, it addresses the following research question: which recommendations and requirements-genomic, digital, and clinical/organizational-are necessary to integrate PRS and wearable technologies into routine practice and healthcare services, and for which of these elements do experts achieve consensus (defined as a Content Validity Index, CVI, \> 79%)

This prospective observational cohort study aims to assess the risk of radiation-induced cardiotoxicity in patients undergoing thoracic radiotherapy by integrating real-time arrhythmia monitoring using wearable cardiac rehabilitation (wearable CR) devices and AI-based cardiac substructure segmentation. The study will analyze radiation dose exposure to key cardiac structures, including the sinoatrial node (SAN) and pulmonary veins (PV), to identify risk factors for atrial fibrillation (AF) and other arrhythmias. Patients will receive wearable CR monitoring at 3, 12, and 24 months post-radiotherapy, with cardiology follow-up and intervention based on standard clinical guidelines. The study will recruit 111 patients over three years, with a two-year follow-up after radiotherapy. The primary endpoint is the incidence of grade 3+ AF within 2 years, with secondary outcomes including any-grade arrhythmia rates, arrhythmia burden, and survival analysis. By establishing a prospective thoracic radiotherapy patient cohort, this study aims to identify dose-related risk factors, improve early detection and management of radiation-induced arrhythmias, and provide evidence-based strategies to enhance treatment safety and efficacy.

Backgroud: With the widespread application of artificial intelligence, sensor technology, and wearable technology in clinical and daily life, wearable devices have shown a promising application prospect and tremendous potential. Currently, both domestic and international clinical applications of wearable ECG devices for the diagnosis and treatment of coronary heart disease are mostly single-lead ECG wearable devices or simulated multi-lead wearable ECG monitoring devices, which are widely used in the diagnosis of arrhythmias such as atrial fibrillation. There is a lack of clinical diagnostic efficacy research on myocardial ischemia in coronary heart disease. Aim: To investigate the diagnostic efficacy of wearable multi-channel ECG acquisition devices for myocardial ischemia in suspected CHD patients Methods：Assessing the sensitivity, specificity, and accuracy of wearable multi-channel ECG devices in diagnosing myocardial ischemia in coronary heart disease by comparing with the "gold standard" SPECT-MPI.The target recruitment is 107 suspected coronary heart disease myocardial ischemia patients.If patients do not meet the exclusion criteria, they will wear the wearable multi-channel ECG device for 7 days after enrollment, followed by a myocardial SPECT examination; there is no specific order for these examinations. After enrollment, baseline information of the patients (such as age, gender, height, weight, etc.), comorbidities (such as hypertension, diabetes, hyperlipidemia, chronic kidney disease, etc.), and auxiliary examination data (such as complete blood count, biochemistry, cardiac injury markers, BNP, echocardiography, wearable multi-channel ECG device data, SPECT-related examination data, such as ST-segment, total load score, total rest score, etc.) will be collected. The endpoint of this study is to evaluate the sensitivity, specificity, and accuracy of the wearable multi-channel ECG device in assessing myocardial ischemia in CHD.