Monitoring at-home prosthesis control improvements through real-time data logging
Abstract
Objective. Validating the ability for advanced prostheses to improve function beyond the laboratory remains a critical step in enabling long-term benefits for prosthetic limb users. Approach. A nine week take-home case study was completed with a single participant with upper limb amputation and osseointegration to better understand how an advanced prosthesis is used during daily activities. The participant was already an expert prosthesis user and used the Modular Prosthetic Limb (MPL) at home during the study. The MPL was controlled using wireless electromyography (EMG) pattern recognition-based movement decoding. Clinical assessments were performed before and after the take-home portion of the study. Data was recorded using an onboard data log in order to measure daily prosthesis usage, sensor data, and EMG data. Main results. The participant’s continuous prosthesis usage steadily increased (p= 0.04, max = 5.5 h) over time and over 30% of the total time was spent actively controlling the prosthesis. The duration of prosthesis usage after each pattern recognition training session also increased over time (p = 0.04), resulting in up to 5.4 h of usage before retraining the movement decoding algorithm. Pattern recognition control accuracy improved (1.2% per week, p p Significance. In this case study, we demonstrate that an onboard system to monitor prosthesis usage enables better understanding of how prostheses are incorporated into daily life. That knowledge can support the long-term goal of completely restoring independence and quality of life to individuals living with upper limb amputation.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 30, 2022
- Source ID
- 10.1088/1741-2552/ac6d7b
Entities
People
- Connor O. Pyles
- Courtney W. Moran
- Erin E Sutton
- Jared M. Wormley
- Jonathan A. Forsberg
- Josef A Butkus
- Kelles D Gordge
- Lauren D Dodd
- Luke E Osborn
- Matthew S. Fifer
- Michelle J. Nordstrom
- Nicolas Norena Acosta
- Paul F Pasquina
- Robert S. Armiger
Organizations
- Johns Hopkins University Applied Physics Laboratory
- Uniformed Services University of the Health Sciences