A Data Fusion System to Study Synchronization in Social Activities

TL;DR

This paper presents a data fusion system that synchronizes multi-subject sensor data to analyze social activities, aiding health monitoring especially for aging populations.

Contribution

It introduces a novel system for synchronizing and fusing multi-subject sensor data during social activities, enabling detailed analysis of collaborative behaviors.

Findings

Successful synchronization of multi-subject sensor data demonstrated

Effective differentiation of social activities based on fused data

Potential for improved health monitoring in social contexts

Abstract

As the world population gets older, the healthcare system must be adapted, among others by providing continuous health monitoring at home and in the city. The social activities have a significant role in everyone health status. Hence, this paper proposes a system to perform a data fusion of signals sampled on several subjects during social activities. This study implies the time synchronization of data coming from several sensors whether these are embedded on people or integrated in the environment. The data fusion is applied to several experiments including physical, cognitive and rest activities, with social aspects. The simultaneous and continuous analysis of four subjects cardiac activity and GPS coordinates provides a new way to distinguish different collaborative activities comparing the measurements between the subjects and along time.