Estimating Force Exerted by the Fingers Based on Forearm Ultrasound

Biosignal-based finger force estimation is an active area of research, with applications in teleoperation, human-machine interaction, and rehabilitation robotics. Traditionally, surface electromyography has been used to estimate hand grip and finger forces. In this paper, we show that forearm ultrasound can be used to estimate the force exerted by the fingers. A wireless ultrasound probe strapped to the forearm and a force sensor was used to estimate the ground truth. Accuracy percentages and root mean square error (RMSE) values were obtained for the shuffled and non-shuffled data subjected to a test-train split for all the fingers. It was found that the classification accuracy was 98.4 percent for the shuffled data, and 82 percent for the non-shuffled data averaged over all the fingers. For continuous estimation, the average RMSE was 0.02 N for the shuffled data and 0.2 N for the non-shuffled data. With a maximum force of 5 N, the average RMSE accounted for 4 percent of the maximum force for the non-shuffled data, and 0.4 percent for the shuffled data. These results show the potential of utilizing forearm ultrasound for estimating finger forces.