Validation of an innovative algorithm for detecting self-propulsion in manual wheelchair users

Area of Science:

• Rehabilitation Engineering
• Biomechanics
• Wearable Technology

Background:

• Actimetry is crucial for assessing physical activity in manual wheelchair (MWC) users.
• Current methods struggle with precise data interpretation and differentiating propulsion from non-propulsion activities.

Purpose of the Study:

• To evaluate the accuracy of a novel algorithm in measuring total distance covered by MWC users.
• To validate the algorithm's capability in distinguishing between MWC self-propulsion and non-propulsion.

Main Methods:

• An experimental study collected actimetry data (Actigraph GT3X+) from MWC users in controlled (indoor) and uncontrolled (outdoor) settings.
• Participants completed multiple propulsion trials over various distances, including self-propulsion and pushing the MWC.
• Data analysis involved descriptive statistics and accuracy measures (percentage of true value).

Main Results:

• The algorithm demonstrated excellent accuracy (98.9%–99.8%) in measuring total distance covered indoors.
• It accurately differentiated self-propulsion from non-propulsion, with accuracies ranging from 96.2%–99.2% (controlled) and 91.3%–100.0% (uncontrolled).

Conclusions:

• The validated algorithm provides precise total distance measurements for MWC users.
• It offers excellent discrimination between self-propulsion and non-propulsion, enhancing physical activity monitoring.