A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease

Shancang Li; Jue Wang; Xinheng Wang

doi:10.1109/GLOCOMW.2010.5700321

A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease

Shancang Li^*
, Jue Wang
, Xinheng Wang

^*Corresponding author for this work

Xi'an Jiaotong University
Swansea University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

9 Citations (Scopus)

Abstract

Gait analysis of human plays a significant role in maintaining the well-being of our mobility and healthcare, and it can be used for various e-healthcare systems for fast medical prognosis and diagnosis. In this paper we have developed a novel body sensor network based recognition system to identify the specific gait pattern of Parkinson's disease (PD). Firstly, a BSN with 16 nodes is used to acquire the gait information from the PD patients. Then, an algorithm is developed based on local linear embedding (LLE) to extract and recognize the gait features. Experiments demonstrate the effectiveness of proposed scheme. The results show that the proposed scheme has a recognition rate of about 95:57% for gait patterns of PD, which is higher than the conventional PCA feature extraction method. The proposed system can identify PD patients from normal people and by their gait map with high reliability and appears a promising aid in the diagnosis of the Parkinson's disease.

Original language	English
Title of host publication	2010 IEEE Globecom Workshops, GC'10
Publisher	IEEE Computer Society
Pages	256-260
Number of pages	5
ISBN (Print)	9781424488650
DOIs	https://doi.org/10.1109/GLOCOMW.2010.5700321
Publication status	Published - 2010
Externally published	Yes
Event	2010 IEEE Globecom Workshops, GC 2010 - Miami, United States Duration: 5 Dec 2010 → 10 Dec 2010

Publication series

Name	2010 IEEE Globecom Workshops, GC'10

Conference

Conference	2010 IEEE Globecom Workshops, GC 2010
Country/Territory	United States
City	Miami
Period	5/12/10 → 10/12/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1109/GLOCOMW.2010.5700321

Cite this

@inproceedings{aaf67c8b9a184921b5d93d119abfe008,

title = "A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease",

abstract = "Gait analysis of human plays a significant role in maintaining the well-being of our mobility and healthcare, and it can be used for various e-healthcare systems for fast medical prognosis and diagnosis. In this paper we have developed a novel body sensor network based recognition system to identify the specific gait pattern of Parkinson's disease (PD). Firstly, a BSN with 16 nodes is used to acquire the gait information from the PD patients. Then, an algorithm is developed based on local linear embedding (LLE) to extract and recognize the gait features. Experiments demonstrate the effectiveness of proposed scheme. The results show that the proposed scheme has a recognition rate of about 95:57\% for gait patterns of PD, which is higher than the conventional PCA feature extraction method. The proposed system can identify PD patients from normal people and by their gait map with high reliability and appears a promising aid in the diagnosis of the Parkinson's disease.",

author = "Shancang Li and Jue Wang and Xinheng Wang",

year = "2010",

doi = "10.1109/GLOCOMW.2010.5700321",

language = "English",

isbn = "9781424488650",

series = "2010 IEEE Globecom Workshops, GC'10",

publisher = "IEEE Computer Society",

pages = "256--260",

booktitle = "2010 IEEE Globecom Workshops, GC'10",

note = "2010 IEEE Globecom Workshops, GC 2010 ; Conference date: 05-12-2010 Through 10-12-2010",

}

Li, S, Wang, J & Wang, X 2010, A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease. in 2010 IEEE Globecom Workshops, GC'10., 5700321, 2010 IEEE Globecom Workshops, GC'10, IEEE Computer Society, pp. 256-260, 2010 IEEE Globecom Workshops, GC 2010, Miami, United States, 5/12/10. https://doi.org/10.1109/GLOCOMW.2010.5700321

A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease. / Li, Shancang; Wang, Jue; Wang, Xinheng.
2010 IEEE Globecom Workshops, GC'10. IEEE Computer Society, 2010. p. 256-260 5700321 (2010 IEEE Globecom Workshops, GC'10).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease

AU - Li, Shancang

AU - Wang, Jue

AU - Wang, Xinheng

PY - 2010

Y1 - 2010

N2 - Gait analysis of human plays a significant role in maintaining the well-being of our mobility and healthcare, and it can be used for various e-healthcare systems for fast medical prognosis and diagnosis. In this paper we have developed a novel body sensor network based recognition system to identify the specific gait pattern of Parkinson's disease (PD). Firstly, a BSN with 16 nodes is used to acquire the gait information from the PD patients. Then, an algorithm is developed based on local linear embedding (LLE) to extract and recognize the gait features. Experiments demonstrate the effectiveness of proposed scheme. The results show that the proposed scheme has a recognition rate of about 95:57% for gait patterns of PD, which is higher than the conventional PCA feature extraction method. The proposed system can identify PD patients from normal people and by their gait map with high reliability and appears a promising aid in the diagnosis of the Parkinson's disease.

AB - Gait analysis of human plays a significant role in maintaining the well-being of our mobility and healthcare, and it can be used for various e-healthcare systems for fast medical prognosis and diagnosis. In this paper we have developed a novel body sensor network based recognition system to identify the specific gait pattern of Parkinson's disease (PD). Firstly, a BSN with 16 nodes is used to acquire the gait information from the PD patients. Then, an algorithm is developed based on local linear embedding (LLE) to extract and recognize the gait features. Experiments demonstrate the effectiveness of proposed scheme. The results show that the proposed scheme has a recognition rate of about 95:57% for gait patterns of PD, which is higher than the conventional PCA feature extraction method. The proposed system can identify PD patients from normal people and by their gait map with high reliability and appears a promising aid in the diagnosis of the Parkinson's disease.

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U2 - 10.1109/GLOCOMW.2010.5700321

DO - 10.1109/GLOCOMW.2010.5700321

M3 - Conference Proceeding

AN - SCOPUS:79951893568

SN - 9781424488650

T3 - 2010 IEEE Globecom Workshops, GC'10

SP - 256

EP - 260

BT - 2010 IEEE Globecom Workshops, GC'10

PB - IEEE Computer Society

T2 - 2010 IEEE Globecom Workshops, GC 2010

Y2 - 5 December 2010 through 10 December 2010

ER -

A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease

Abstract

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UN SDGs

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