Smart Wearable Garment and Rapid Musculoskeletal Modelling for Accurate Neuromechanical Analysis

Current clinical diagnostic tools for post-stroke motor deficits are based on rapid but subjective evaluation. Greater accuracy could be provided in well-equipped biomechanical laboratories. However, this involves lengthy set-up, data acquisition, and offline data analysis available only days, or weeks, after the initial assessment, no longer reflecting the patient’s actual state. The ability to capture the patient’s muscle activity as well as joint kinematics is key for neuromechanical assessment, but the process of muscle localization for electrode placement and joint angle measurement is not always viable in clinical environments. Here, we propose a new wearable technology with an integrated high-density electromyography and kinematics sensors able to provide simultaneously a rapid and accurate diagnosis. The soft sensorized garment in conjunction with automatic clustering of the HD-EMG channels into muscle groups and real-time modeling of the neuromusculoskeletal system allows estimation of internal mechanical forces in a rapid, quantitative, and clinically viable way.