PaWLA: PPG-based Weight Lifting Assessment

Physical activity (PA) plays a crucial role in leading a healthy life without chronic diseases. Among various PAs, weight lifting, one of the essential stationary exercises, is an integral part of routine workout sessions. Being aware of the intensity of the performed exercise is also an essential factor in keeping track of the workout. Inspired by this, we propose a low-cost quantitative weight lifting assessment system, PaWLA, leveraging only a single Photoplethysmography (PPG) sensor. Particularly, we design PaWLA as a mobile weight recognition system that can classify the user’s lifted weight into its corresponding label based on PPG sensor readings from the wrist region. The changes in blood volume in the radial artery due to the strain of lifting the weight are exploited via PPG sensor readings in this work. We build our custom hardware prototype using COTS components to prove the system’s feasibility. Evaluation of the system with nine volunteers shows that PaWLA can achieve an average F1 score of up to 97.4%, proving the feasibility and efficiency of the proposed method.