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

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

doi:10.1145/2534088.2534097

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

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

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.

Original language	English (US)
Title of host publication	Proceedings - Wireless Health 2013, WH 2013
Publisher	Association for Computing Machinery
ISBN (Print)	9781450322904
DOIs	https://doi.org/10.1145/2534088.2534097
State	Published - 2013
Externally published	Yes
Event	4th Conference on Wireless Health, WH 2013 - Baltimore, MD, United States Duration: Nov 1 2013 → Nov 3 2013

Publication series

Name	Proceedings - Wireless Health 2013, WH 2013
Volume	2013-January

Conference

Conference	4th Conference on Wireless Health, WH 2013
Country/Territory	United States
City	Baltimore, MD
Period	11/1/13 → 11/3/13

ASJC Scopus subject areas

Artificial Intelligence
Health Informatics

Access to Document

10.1145/2534088.2534097

Cite this

Kashani, F. B., Medioni, G., Nguyen, K., Nocera, L., Shahabi, C., Wang, R., Blanco, C. E., Chen, Y. A., Chung, Y. C., Fisher, B., Mulroy, S., Requejo, P., & Winstein, C. (2013). Monitoring mobility disorders at home using 3D visual sensors and mobile sensors. In Proceedings - Wireless Health 2013, WH 2013 (Proceedings - Wireless Health 2013, WH 2013; Vol. 2013-January). Association for Computing Machinery. https://doi.org/10.1145/2534088.2534097

Monitoring mobility disorders at home using 3D visual sensors and mobile sensors. / Kashani, Farnoush B.; Medioni, Gerard; Nguyen, Khanh et al.
Proceedings - Wireless Health 2013, WH 2013. Association for Computing Machinery, 2013. (Proceedings - Wireless Health 2013, WH 2013; Vol. 2013-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kashani, FB, Medioni, G, Nguyen, K, Nocera, L, Shahabi, C, Wang, R, Blanco, CE, Chen, YA, Chung, YC, Fisher, B, Mulroy, S, Requejo, P & Winstein, C 2013, Monitoring mobility disorders at home using 3D visual sensors and mobile sensors. in Proceedings - Wireless Health 2013, WH 2013. Proceedings - Wireless Health 2013, WH 2013, vol. 2013-January, Association for Computing Machinery, 4th Conference on Wireless Health, WH 2013, Baltimore, MD, United States, 11/1/13. https://doi.org/10.1145/2534088.2534097

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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.",

author = "Kashani, {Farnoush B.} and Gerard Medioni and Khanh Nguyen and Luciano Nocera and Cyrus Shahabi and Ruizhe Wang and Blanco, {Cesar E.} and Chen, {Yi An} and Chung, {Yu Chen} and Beth Fisher and Sara Mulroy and Philip Requejo and Carolee Winstein",

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doi = "10.1145/2534088.2534097",

language = "English (US)",

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AU - Kashani, Farnoush B.

AU - Medioni, Gerard

AU - Nguyen, Khanh

AU - Nocera, Luciano

AU - Shahabi, Cyrus

AU - Wang, Ruizhe

AU - Blanco, Cesar E.

AU - Chen, Yi An

AU - Chung, Yu Chen

AU - Fisher, Beth

AU - Mulroy, Sara

AU - Requejo, Philip

AU - Winstein, Carolee

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AB - 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.

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ER -

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

Abstract

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ASJC Scopus subject areas

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