Monitoring mobility disorders at home using 3D visual sensors and mobile sensors
Farnoush Banaei Kashani, Gérard G. Medioni, Khanh Nguyen, Luciano P. Nocera, Cyrus Shahabi, Ruizhe Wang, Cesar E. Blanco, Yi‐An Chen, Yu‐Chen Chung, Beth E. Fisher, Sara J. Mulroy, Philip Santos Requejo, Carolee Joyce Winstein · 2013
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.