Clinical Research Directory

Evaluating Health Outcomes of AI-Based Fitness Wearables & App Programs in Elderly With Cognitive Decline

The overarching goal of our research is to develop personalized and accessible healthy aging lifestyle interventions aimed at promoting physical activity (PA) and improving health among community-dwelling older adults living alone with cognitive decline (LACD). To achieve this goal, the purpose of this project is to determine whether wearable and app-based mHealth intervention component(s) will contribute to increased PA and improved health outcomes in older adults LACD. Our specific aims are to: identify and evaluate mHealth intervention components that practically and significantly contribute to enhanced mechanistic outcomes (e.g., self-efficacy, outcome expectations) and increased PA (primary outcome) in older adults LACD over a 6-month period; determine the optimal combinations of intervention components for future efficacy testing; elucidate the mechanism of behavioral change (MoBC) and potential outcomes of these intervention components, namely, the mediating effects of MoBC variables (e.g., self-efficacy, outcome expectations) on the relationship between intervention components and change in PA. The first two aims are primary and fully-powered. The third aim is exploratory. The aims will support a refined, data-driven intervention design for a subsequent larger trial.

SmartWatch-driven AF Detection in Stroke Patients

Unrecognized atrial fibrillation (AF) is a common cause of ischemic stroke. Implantable event monitors (ICM) are the gold standard for continuous heart rhythm monitoring but they have been implemented in very few patients after stroke due to high invasiveness and high costs. In this trial, patients with implanted ICMs (Medtronic Reveal LINQ Insertable Cardiac Monitor) will be randomized to use one of two wearables (1:1 Apple Watch or PulseOn) for continuous monitoring. The aim is to compare the probability of detecting an episode of AF with a wearable versus the gold standard ICM. Both groups will use the wearable for 12 weeks. If the wearables detect an arrhythmic pulse curve, this is communicated by vibration. By laying the other hand on the device, a 1-channel ECG is performed. ECG data will be transferred regularly to the CoreLab (Universityhospital Leipzig) for analysis. After 12 weeks, the patients will visit the site and answer questions regarding the usability, compliance and satisfaction with the wearables.

Identifying Wearable Biomarkers to Monitor Dietary Intake

Background: Measuring what people eat is a challenge in nutrition research. Traditional methods, like food diaries, rely on self-reporting of individuals, and suffer from poor accuracy and recall bias. Aims: This project aims to identify physiological biomarkers related to food and energy intake, which may be used to develop an objective tool to estimate individuals' food intake in future. Eating behaviours are accompanied by significant physiological changes such as skin temperature, blood oxygen saturation, pulse rate etc. The investigators intend to investigate whether monitoring these physiological changes can help us estimate eating behaviour, such as meal size, eating speed, and duration of meals. Study design: Ten healthy adults will be invited for two study visits at NIHR Imperial Clinical Research Facility. Each visit will last for approximately 2 hr. They will consume a high- and low-calorie meal designed by nutritional researchers in a randomised order. During eating events, the investigators will track their physiological changes via a bedside monitor and wearable sensors. Blood samples will be taken from participants to measure their glycaemic response. Associations between energy load, glycaemic response, and physiological changes will be investigated. Our findings may promote an accelerated development of a wearable tool for dietary assessment in future.