Effective Validation Model and Use of Mobile-Health Applications for the Elderly

Area of Science:

• Gerontology
• Biomedical Engineering
• Health Informatics

Background:

• Mobile health (mHealth) applications are increasing rapidly.
• Elderly individuals often lack trust in mHealth app measurements due to insufficient scientific validation.
• There is a need for effective validation models for mHealth apps targeting the elderly population.

Purpose of the Study:

• To evaluate the accuracy of mobile health applications for biophysical measurements in the elderly.
• To compare mobile app data with standard instruments through controlled experiments.
• To propose a validation model for mHealth applications used by older adults.

Main Methods:

• Fifty elderly participants were enrolled to assess weight and cardiac status.
• Two mobile applications (Activ for energy expenditure, SMCa for heart rate) were tested during controlled walking.
• Minute-by-minute data were collected and statistically analyzed for average error and accuracy using 95% confidence intervals.

Main Results:

• The Activ/SMCa applications demonstrated statistically similar results to specialized equipment, with 95% confidence intervals.
• Training and initial data registration significantly improved the perceived ease of use among elderly participants.
• The study identified anthropometric and body movement differences between subjects with similar Body Mass Index (BMI) but different ages.

Conclusions:

• This research presents a novel model for validating mHealth apps with elderly users.
• The findings support the reliability of mobile health applications for biophysical measurements in older adults.
• Future research should incorporate age and usability perception alongside BMI for comprehensive app validation.