F. Kashani, G. Medioni, Khanh Nguyen, Luciano Nocera, C. Shahabi, Ruizhe Wang, Cesar Blanco, Yi-An Chen, Yu-Chen Chung, Beth Fisher, Sara Mulroy, Phil Requejo, C. Winstein
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Monitoring mobility disorders at home using 3D visual sensors and mobile sensors
In this paper, we present PoCM2 (Point-of-Care Mobility Monitoring), a generic and extensible at-home mobility evaluation and monitoring system. PoCM2 uses both 3D visual sensors (such as Microsoft Kinect) and mobile sensors (i.e., internal and external sensors embedded with/connected to a mobile device such as a smartphone) for complementary data acquisition, as well as a series of analytics that allow evaluation of both archived and real-time mobility data. We demonstrate the performance of PoCM2 with a specific application developed for freeze detection and quantification from Parkinson's Disease mobility data, as an approach to estimate the medication level of the PD patients and potentially recommend adjustments.