A Novel Mobile Application for Objective Evaluation of Degenerative Cervical Myelopathy

Introduction: Degenerative cervical myelopathy (DCM) is a common and debilitating condition resulting from arthritic degeneration and compression of the cervical spinal cord. It leads to various neurological deficits, particularly impairments in dexterity, gait, and balance. However, there is a lack of high-quality, objective tools for accurately measuring DCM-related disabilities, which are critical for guiding treatment decisions and monitoring patient outcomes. Smartphones and wearable technologies are equipped with a range of sensors and capabilities, including accelerometers, gyroscopes, and cameras, that are particularly well-suited for evaluating gait and upper extremity function. Based on these theoretical benefits, we developed SynapTrack, a smartphone application designed to assess DCM severity using patient-performed tasks. This study outlines SynapTrack’s initial promising results in evaluating functional impairments in DCM patients.

Methods: SynapTrack was developed using SwiftUI for iOS devices and is currently in Beta for in-clinic data collection. The gait assessment algorithms were trained using data from the phone's sensors in patients with DCM and validated against objective measurements obtained from gait mats and video capture. Dexterity algorithms were developed using both self-reported assessments and data from objective tasks, such as the 9-hole peg test and a tapping task.

Results: Initial testing of SynapTrack with patients suggests that it can reliably measure key impairments associated with DCM. From gait analysis of patients with DCM (n=18), the app accurately quantified time between steps with an average error of 17 milliseconds and demonstrated correlations with objective gait mat measurements (r=0.92). In dexterity assessments, patients reporting greater difficulty with fine motor tasks exhibited lower performance scores on the tapping task as analyzed by backend algorithms. These preliminary results highlight the potential of SynapTrack for diagnostic and predictive purposes for patients with DCM. We anticipate having data from at least 20 DCM patients and non-myelopathy controls to present at Spine Summit.

Conclusion : The development and testing of SynapTrack show promise as an innovative, objective tool for assessing DCM-related disabilities. By leveraging smartphone sensors, SynapTrack offers a precise and accessible method for evaluating disease progression and patient status. These early results support further development and validation, with plans to expand testing to at-home settings.