Investigation of a wearable piezoelectric-IMU multi-modal sensing system for real-time muscle force estimation

Piezoelectric based ultrasonic transducer shows a promising application prospect in the wearable muscle force estimator by detecting the morphological-biochemical peculiarity of human motion. However, due to the nonlinearity of muscle contraction, muscle force estimation in a dynamic motion, such as leg lifting, is still a challenge. In this study, a wearable multi-sensory system was developed for muscle force estimation in the isometric contraction assessment and during the dynamic training. A customized wearable ultrasound system was adopted for real-time deformation measurement of muscle, and an inertial measurement unit sensor was utilized to detect the joint angle. Thus, the muscle force can be predicted by identifying the muscle deformation as well as considering the muscle thickness change caused by the joint angel variation. The robustness and efficiency of the system was investigated by evaluating the muscle force of the rectus femoris during the isometric contraction assessment and the knee's dynamic exercise. The accuracy of muscle force prediction is over 90%. During the knee's dynamic exercise, the predicted force output of the lower-limb agreed well with the measured value, demonstrating the promising application of the system in dynamic muscle force estimation. This approach can provide real-time muscle force information for the patients to improve the rehabilitative training effect when using an exoskeletal rehabilitation robot as well as evaluate their recovery situation.

Automated summary

Piezoelectric based ultrasonic transducer has great potential in wearable muscle force estimation by detecting human motion characteristics. However, muscle force estimation during dynamic motion is still challenging due to the nonlinearity of muscle contraction. In this study, a wearable multi-sensory system was developed using ultrasound and inertial measurement unit sensors to predict muscle force based on real-time muscle deformation and joint angle variation. The system was evaluated for muscle force estimation during isometric contraction assessment and dynamic knee exercise, showing high accuracy and promising application in dynamic muscle force estimation.