Investigation of thumb-tip force prediction based on Hill's Muscle model using noninvasive electromyography and ultrasound signals - Sidek, Shahrul Na'im (2017)
Restoring human body that is lost during accident with prosthetic unit is one challenging issue in engineering field. The loss of human body, involving upper and lower limbs leaves great impact on human that it can limit daily activities in many ways. There are many studies that have been done previously in making and improving prosthetic unit for amputees. Most of them are made to replicate the basic functionalities of the missing limbs but adopt more conventional, passive type of controllers. As a result the prosthetic unit range of motion is limited and the motion is unnatural. Hence, there is a need to develop model based controller for the system to address the problem. The goal of the research is to develop a semi analytical model of a thumb that could be used to develop model based controller. In this work the information from the muscle characteristics need to be analyzed. The electromyography signals from the four muscles responsible on thumb flexion are recorded and analyzed. On top, information such as the length of the muscles and tendons is gathered from ultrasound image and MRI to increase the data accuracy. These data is fed into Hill’s muscle model and optimized by the PSO to map the relationship between thumb posture, thumb tip force and all the signal measured. The resulting thumb model developed using the method proposed has shown better accuracy as compared to previous method.