Effect of remote lifestyle intervention by using IoT, ICT, and further AI in diabetic medical cooperatio
Not Applicable
Completed
- Conditions
- Type 2 diabetes
- Registration Number
- JPRN-UMIN000038753
- Lead Sponsor
- Hiroshima University Graduate School of Biomedical and Health Sciences Preventive Medicine for Diabetes and Lifestyle-related Diseases
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Complete: follow-up complete
- Sex
- All
- Target Recruitment
- 39
Inclusion Criteria
Not provided
Exclusion Criteria
Diabetes other than type2. Under dialysis treatment. Any other reason by decision of Research representative or researchers.
Study & Design
- Study Type
- Interventional
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Change of HbA1c after 6 months
- Secondary Outcome Measures
Name Time Method Change of HbA1c after 3 months. Change of Blood pressure and body composition after 3 and 6 months. Change of eating habit and physical function after 6 months.
Related Research Topics
Explore scientific publications, clinical data analysis, treatment approaches, and expert-compiled information related to the mechanisms and outcomes of this trial. Click any topic for comprehensive research insights.
What molecular mechanisms underlie IoT and AI-driven lifestyle interventions in type 2 diabetes management?
How does remote monitoring via IoT and AI compare to standard in-person diabetes care in terms of glycemic control and patient outcomes?
Are there specific biomarkers that predict response to AI-based lifestyle interventions in type 2 diabetes patients?
What adverse events are associated with long-term use of IoT-enabled remote diabetes management systems and how are they managed?
What combination therapies or digital health platforms are being developed alongside IoT and AI for type 2 diabetes management?