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Background: In orthopaedics today, sensing technology is routinely used. It is most frequently established in perioperative care and fundamental studies of human mobility. Given that modern wearable technology is capable of monitoring and diagnosing capabilities, this technology could assist in addressing some of the issues the healthcare industry encounters. Numerous patients experience knee joint issues during the course of their lifetime. Fitknees® is a wireless motion sensor-based system that assesses the clinical, functional and subjective measurements of chronic knee injury patients. Aim of Study: The objective of this clinical study was to determine the validity and reliability of Fitknees® against the currently used clinical methods like goniometry, timed tests and distance calculations during various assessment tests in healthy population. To test the validity and reliability of fitknees for range of motion, extension lag, proprioception and static and dynamic balance and stair climbing. Methods: The study included 10 healthy adults without knee pain. The individuals aged between 18 years and above. Tests for validity were performed concurrently on the same testing sessions. Reliability tests were performed by subjects within 48 hours between sessions. Results: The knee outcomes measured by Fitknees® were range of motion (ROM), extension lag, proprioception, static balance, dynamic balance and staircase climbing. Fitknees® was found to provide greater accuracy and better ability to detect minimum changes in patients for most measures, in comparison to conventional assessment methods. Reliability was also high for all outcome measures, except mobility with shows significance with p value < 0. 005.Conclusion: The results of the study indicate that the Fitknees® is a reliable and conditionally valid wearable sensor system for quantifying clinical outcomes of the knee.
Motion sensor, knee outcome, progress tracking, treatment documentation, biomechanical data, remote healthcare, experienced clinician assessment
Motion sensor, knee outcome, progress tracking, treatment documentation, biomechanical data, remote healthcare, experienced clinician assessment
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