Monitoring mobility disorders at home using 3D visual sensors and mobile sensors

Authors:
Farnoush B. Kashani;Gerard Medioni;Khanh Nguyen;Luciano Nocera;Cyrus Shahabi;Ruizhe Wang;Cesar E. Blanco;Yi-An Chen;Yu-Chen Chung;Beth Fisher;Sara Mulroy;Philip Requejo;Carolee Winstein
Affiliations:
Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California;Univ. of Southern California, Los Angeles, California
Venue:
Proceedings of the 4th Conference on Wireless Health
Year:
2013

Citing 2
Cited 0

A vision-based analysis system for gait recognition in patients with Parkinson's disease

Expert Systems with Applications: An International Journal
Home Monitoring Musculo-skeletal Disorders with a Single 3D Sensor

CVPRW '13 Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.