Monitoring at-home prosthesis control improvements through real-time data logging

Area of Science:

• Biomedical Engineering
• Rehabilitation Science
• Prosthetics and Orthotics

Background:

• Validating advanced prostheses for daily use is crucial for long-term user benefits.
• Osseointegration offers a stable interface for prosthetic limb attachment.
• Expert prosthesis users can provide valuable insights into real-world device performance.

Purpose of the Study:

• To assess the daily functional integration of an advanced prosthetic limb in an upper limb amputee.
• To evaluate the performance and user experience of a Modular Prosthetic Limb (MPL) controlled by electromyography (EMG) pattern recognition.
• To investigate the impact of prolonged, real-world use on prosthesis control and user workload.

Main Methods:

• A nine-week take-home case study with a single participant using an osseointegrated MPL.
• Wireless EMG pattern recognition for movement decoding and control.
• Onboard data logging for continuous monitoring of prosthesis usage, sensor data, and EMG.
• Clinical assessments (Box and Blocks, Assessment of the Capacity for Myoelectric Control, NASA Task Load Index) before and after the study.

Main Results:

• Continuous prosthesis usage increased steadily, reaching up to 5.5 hours daily.
• Pattern recognition control accuracy improved weekly (1.2%), with efficient transitions between degrees of freedom.
• Clinical scores improved significantly (Box and Blocks +43%, Myoelectric Control +6.2%), while cognitive workload decreased (NASA TLX -25%).

Conclusions:

• An onboard monitoring system effectively captures real-world prosthetic limb usage patterns.
• Advanced prostheses, like the MPL, can significantly enhance daily function and reduce cognitive load for users.
• This approach supports the goal of restoring independence and quality of life for individuals with upper limb amputation.