Demonstrating the wearable sensors’ ability to identify walking abnormalities is a key step in bringing gait analysis to patients' homes in telemedicine and digital health.
In our recent study published in Sensors journal, we could demonstrate that small inertial sensors with low sampling rates can detect the presence and severity of knee OA.
The suggested method for extraction of valuable parameters from sensors' data will pave the way for enabling clinicians to use gait analysis in regular consultation, to identify patients with knee OA and to evaluate their response to treatments.
This will provide an opportunity to monitor the recovery process after surgery and individualize the rehabilitation programs.
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