A Wavelet Transform-Based Approach for Detecting Postural Transitions in Patients Following Anterior Cruciate Ligament Reconstruction¹

Wearable sensing and monitoring technologies hold promise for multiple motor and behavioral domains, including individuals who have had anterior cruciate ligament reconstruction (ACLr) [1]. Long-term gait deficits in this population may result from compensatory gait behaviors in the early postsurgery phase of recovery. These compensatory behaviors often develop in the home. This suggests the need for tools capable of monitoring peoples' behaviors in ambient settings. Of particular import is the number of postural transitions (e.g., sit-to-stand gestures) that people perform in the home. These gestures are important because a person's functional independence and quality of life depend on his or her ability to perform such activities. The detection of these postural transitions in patients after surgery may help clinicians understand the trajectory of recovery during rehabilitation of the torn anterior cruciate ligament [2]. Therefore, a system capable of detecting the postural transitions and potentially calling the...