View clinical trials related to M-health.
Filter by:To explore the effect of smart app and wearable-based lifestyle intervention management on vascular health, comparing different exercise with the improvement of vascular arterial stiffness. The accuracy and consistency evaluation of smart wearable devices in screening for vascular health risks were also discussed.
To observe comprehensive physical therapy program for OSAHS patients
One of the goals in the Sustainable Development Goals (SDGs) is the availability of a healthy and prosperous life for all ages. This goal mentions health priorities i.e. non-communicable diseases. Chronic kidney failure (CRF) is one of the non-communicable diseases that is the main cause of death and disability both in the world and in Indonesia. The prevalence of CRF in Indonesia is 0.5% with 83.2% of patients being of productive age and the highest number of CRF patients in North Kalimantan, Southeast Sulawesi, DKI Jakarta and Yogyakarta. Monitoring and evaluation of patients with CRF is currently mostly carried out conventionally not using health technology that is integrated with hospital information systems. This study aims to design and provide a health information system for patients with CRF, hereinafter referred to as SIKIDI, which integrates mobile-health applications used independently by patients with existing information systems in hospitals.
It is estimated that 2.3 million Taiwanese have diabetes and there is a 44% increased rate among young adults and adolescents. Poor dietary habits and sedentary lifestyle are the major risk factors for type 2 diabetes. The growing availability of smartphones has boosted the development of new technologies that incorporate the use of digital food photography as health promotion and individualized nutrition care. Digital health technology is also used to prevent and treat diabetes with good degree of successes in the short term but the long term effect remains unknown. The broad aim of this study is to evaluate the effectiveness of digital technology eHealth care for diabetic patients. A total of 300 diabetic patients will be recruited from Diabetes Shared Care Network and community care center in Taiwan and follow up 12 months. A simple randomization by computer system will be used to randomly allocate subjects into 2 groups: control group and eHealth care. The control group (n=100) of diabetic patients will receive conventional health and nutrition education from state registered dietitian. The eHealth care group (n=200) of diabetic patients will receive a 10 mins of food portion size nutrition education using " 3D/AR MetaFood platform" and is required to record their consume meal by food image once a week using Taiwan FoodAPP. Patients in the eHealth group will receive instant feedback from the nutritionists or artificial intelligence (AI) for the information of glycemic index (GI) and glycemic load (GL), and educational video related to healthy eating or how to select GI/GL food. Anthropometry, and baseline questionnaires will be collected at baseline. Blood biochemistry (e.g. HbA1c) and body weight will be collected at baseline, 3, 6, 9, and 12 months. The collected food image data will be used for AI training to identify the relationship between the patient's diet and blood glucose changes over time.
This is a randomized, open, controlled, single-center trial to identify the weight loss effects of adding mobile health application in obesity multidisciplinary outpatient clinic.
haMSter is a smartphone app that tracks validated patient reported outcome measures (PROMs) in people multiple sclerosis (MS). In this study, 50 patients with MS will receive this app for 6 months and be asked to fill out the PRO questionnaires on their Smartphone. Endpoints include the adherence to this app and satisfaction with this Intervention.