A novel approach for predicting usability of upper limb prostheses

Area of Science:

• Rehabilitation Engineering
• Human-Computer Interaction
• Prosthetics and Orthotics

Background:

• Limb amputation presents significant functional challenges, often necessitating prosthetic devices (PDs).
• High cognitive demands and usability issues with PDs frequently lead to user rejection.
• Existing methods lack a quantitative approach to predict PD usability and human performance.

Purpose of the Study:

• To develop a Human Performance Model for Upper-Limb Prosthetic Devices (HPM-UP).
• To quantitatively assess PD usability through learnability, error rate, memory load, efficiency, and satisfaction.
• To provide a computational tool for predicting PD performance and aiding clinical recommendations.

Main Methods:

• Formulated key usability dimensions: learnability, error rate, memory load, efficiency, and satisfaction.
• Developed the Human Performance Model for Upper-Limb Prosthetic Devices (HPM-UP).
• Validated the HPM-UP with 30 healthy participants using a bypass prosthetic device.

Main Results:

• The HPM-UP successfully predicted the usability of prosthetic devices.
• Model predictions aligned with human subject data.
• The model offers a quantitative approach to assess PD usability.

Conclusions:

• The HPM-UP provides a validated, quantitative method for assessing upper limb prosthetic device usability.
• The model can assist clinicians in analyzing and recommending optimal prosthetic devices for patients.
• The HPM-UP is publicly available on Github for broader application and research.