A novel approach for predicting usability of upper limb prostheses

Abstract

Limb amputation can lead to significant functional challenges in daily activities, prompting amputees to use prosthetic devices (PDs). However, the cognitive demands of PDs and usability issues have resulted in user rejections. This study aimed to create a Human Performance Model for Upper-Limb Prosthetic Devices (HPM-UP). The model used formulations of learnability, error rate, memory load, efficiency, and satisfaction to assess usability. The model was validated in an experiment with 30 healthy participants using a bypass prosthetic device. Findings indicated that the HPM-UP successfully predicted the usability of prosthetic devices, aligning with human subject data. This research proposes a quantitative approach to predict upper limb prosthetic device usability by quantifying each dimension and computationally connecting them. The model, available on Github and executable with Rstudio, could enable clinicians to assess and analyze the human performance of various commercial prostheses, aiding in recommending optimal devices for patients.