An Integrated Software Platform for Enhanced Motion Analysis in Neurological Treatment Monitoring

Introduction: Neurological pathologies and traumas frequently result in motor system impairments, impacting patients' quality of life and presenting treatment-monitoring challenges. Conventional assessment techniques often rely on clinical rating scales and patient self-reports which may not fully capture the intricacy of motor deficits. There is a critical need for direct, quantitative, and objective methods for evaluating motor function in patients with neurological disorders or injuries. We have developed a software platform that integrates cutting-edge motion capture technology along with neural data when available into a simultaneously captured data stream for subsequent analysis.

Methods: Our system records detailed body and finger movements and adjusts to different mobility levels, offering real-time, 3D mapping of key anatomical points for in-depth motor activity analysis. When combined with neural or physiologic recordings (e.g. EEG, EMG), it has the potential to offer insights into the correlation between neural behavior and motor activity, which could be valuable for refining therapeutic strategies or further characterizing the degree of pathology. When used longitudinally, such assessment may help quantify the degree of improvement from surgical interventions.

Results: Validation tests of our software platform confirm its functionality in accurately tracking spatial positions and integrating neural or physiological data streams. The system has demonstrated precise capture and characterization of full-body movements, including the intricate motor functions of the fingers, across a range of mobility scenarios.

Conclusion : Our software platform offers an essential advancement toward integrating precise motor function quantification with neural data insights, facilitating a more nuanced approach to neurological care. This system enhances treatment personalization and improves the rigor of outcome measurement, steering the field toward more data-informed, patient-centric models.