Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson's Disease patients.
Robbin Romijnders, Elke Warmerdam, Clint Hansen and 3 others
PMID 33549105WHAT IT FOUND
Shank-mounted sensors accurately detect foot contacts during straight and curved walking in older adults and people with Parkinson's or stroke.
Detection fails during turns, missing many steps and creating false ones. Do not trust sensor data from turning without manual checks.
Key findings
01The sensors detected foot contacts with high accuracy during straight-line walking, even when participants were performing a dual-task.
02During turns, the algorithm missed many events and falsely detected others, showing lower accuracy than during straight or slalom walking.
03For stroke patients, the error in detecting foot contacts was significantly higher during dual-task walking compared to single-task walking.
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 used a short 5-meter walking distance, which may not reflect longer daily walks. The tests were conducted in a controlled laboratory setting, not in real-world daily life. The poor performance during turns may be due to the specific signal processing method used, which relied on forward leg swing.
Declared interests
Funded by H2020 Marie Skłodowska-Curie Actions and Projekt DEAL. No commercial conflicts of interest were reported.
The easy way to misread this
Do not assume that gait sensors work equally well for all walking tasks. The study shows that while detection is accurate for straight and slalom walking, it fails during turns, missing many steps and creating false events. Using this data for turn analysis will lead to incorrect conclusions about a patient's gait.