European Journal of Biomedical and Pharmaceutical Sciences

ASSOCIATION OF TASK PERFORMANCE WITH THE ARTIFICIAL INTELLIGENCE BASED WEARABLE SENSORS IN ELDERLY POPULATION

Yusra Iqbal*, Muhammad Athar Khan, Areesha Jamil, Tayyaba Zaman, Nazish Mushtaq and Iqra Liaqat

ABSTRACT

Advancements in artificial intelligence (AI) and wearable sensor technology have introduced new possibilities for monitoring and enhancing health outcomes in the elderly. This study aimed to find out the association of task performance with the usage of artificial intelligence and wearable sensors in the elderly population. A sample of 64 elderly people was recruited from Community Geriatric Centers. Participants were divided into two groups based on their prior experience with AI tools. Both groups performed various tasks to evaluate their mobility and heart rate. Both groups' performance was evaluated using a Smartwatch equipped with accelerometer and heart rate monitor, as well as traditional assessment methods such as the 6-Minute Walk Test (6MWT) and Manual Pulse Assessment. The data was analyzed using SPPS software version 26. The results of this study revealed no significant differences between Group A (those with prior experience using AI tools) and Group B (those without) in terms of mobility and heart rate assessments. Both groups exhibited comparable performance across the accelerometer-based mobility assessments (p = 0.900) and traditional 6-minute walk tests (p = 0.831). Heart rate measurements from wearable devices (p = 0.628) and manual pulse assessments (p = 0.657) also showed no significant variations between the two groups. The study found no significant differences in mobility or heart rate assessments between elderly participants with or without AI experience. Wearable sensors and traditional methods aligned well for mobility, but heart rate measurements varied across groups.

Keywords: Accelerometer, Artificial Intelligence, Gyroscope, Task Performance, Wearable Sensors.