Bioimpedance Measurement to Enhance Physical Activity Recognition

This research aims to develop an innovative wearable system that integrates bioimpedance sensing with an inertial measurement unit (IMU) to enable real-time recognition and classification of human physical activities. The study involves participants wearing an elastic wrap embedded with biopotential textile electrodes and an IMU sensor while performing a series of predefined low-intensity activities in a controlled environment. During each activity, physiological and motion signals will be captured using a bioimpedance device and recorded directly onto a computer system. The collected data will then be systematically processed and analysed using machine learning techniques to support accurate identification and classification of human activity patterns.