Assessing walking ability using a robotic gait trainer: opportunities and limitations of assist-as-needed control in spinal cord injury.
Serena Maggioni, Lars Lünenburger, Robert Riener and 3 others
PMID 37735690WHAT IT FOUND
A robotic gait trainer's knee support level during swing predicted walking speed in ambulatory SCI patients.
However, the model failed for non-ambulatory and able-bodied users, and reliability was poor due to learning effects. It is not yet ready for clinical assessment.
Key findings
01Knee stiffness required by the robot at terminal swing was a significant predictor of overground walking speed in ambulatory patients with SCI.
02Adding isometric hip flexion force to the model improved the prediction of walking speed, but the model could not accurately predict ability in non-ambulatory patients.
03The measurement showed poor absolute reliability, with a significant learning effect observed between the first and second testing sessions.
STILL TO COME
How it was doneWhat they foundWhat it means for PTsWhat it means for OTs
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What it does not show
The study was very small (27 participants), with only 11 ambulatory SCI patients used to build the prediction models. The predictive model did not work for non-ambulatory patients, overestimating their walking ability. There was a significant learning effect between sessions, meaning participants performed better the second time, which compromises the reliability of the measure for tracking progress. The reference trajectory used in the robot was manually adjusted by the therapist, introducing subjectivity. The 'assist-as-needed' algorithm only adapted support for one leg at a time, which may not reflect natural bilateral walking patterns.
Declared interests
The study was funded by FP7 Health (Non-U.S. Gov't). The authors state that the Lokomat device was provided by Hocoma AG, but do not explicitly declare Hocoma's role in the study design or analysis in the provided text, though the device is central to the work.
The easy way to misread this
Do not assume this robotic assessment is ready for clinical use. The study found that the model overestimated walking ability in non-ambulatory patients and showed poor reliability due to learning effects between sessions. It is a proof-of-concept for research, not a validated clinical tool.