Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system

Yuchao Ma; Sharon Henry; Alex Kierlanczyk; Majid Sarrafzadeh; Joseph Caprioli; Kouros Nouri-Mahdavi; Hassan Ghasemzadeh; Navid Amini

doi:10.1109/PERCOMW.2015.7134077

Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system

Yuchao Ma, Sharon Henry, Alex Kierlanczyk, Majid Sarrafzadeh, Joseph Caprioli, Kouros Nouri-Mahdavi, Hassan Ghasemzadeh, Navid Amini

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

7 Scopus citations

Abstract

Many studies have reported that older adults with glaucoma experience mobility issues due to gait difficulties. These include walking slowly and bumping into obstacles, which increase the risk of falls in glaucoma patients. In this paper, we design and develop a shoe-integrated sensing system as well as signal processing and machine learning algorithms to objectively quantify gait patterns in glaucoma patients. The sensor platform was utilized in a randomized clinical trial involving 9 glaucoma patients and 10 age-matched healthy participants performing a series of gait tests. Sensor signals are collected wirelessly and processed on a local computer. With the captured data, we develop data analysis techniques to make a comparison between gait characteristics in older adults with or without glaucoma. Our results demonstrate that the proposed system achieved an accuracy of more than 90% in distinguishing gait patterns of those with glaucoma from healthy individuals for various gait analysis tests.

Original language	English (US)
Title of host publication	2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	433-438
Number of pages	6
ISBN (Electronic)	9781479984251
DOIs	https://doi.org/10.1109/PERCOMW.2015.7134077
State	Published - Jun 24 2015
Externally published	Yes
Event	13th IEEE International Conference on Pervasive Computing and Communication, PerCom Workshops 2015 - St. Louis, United States Duration: Mar 23 2015 → Mar 27 2015

Publication series

Name	2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015

Conference

Conference	13th IEEE International Conference on Pervasive Computing and Communication, PerCom Workshops 2015
Country/Territory	United States
City	St. Louis
Period	3/23/15 → 3/27/15

Keywords

Accelerometer
Classification
Feature Selection
Gait Analysis
Glaucoma

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Human-Computer Interaction
Health(social science)

Access to Document

10.1109/PERCOMW.2015.7134077

Cite this

Ma, Y., Henry, S., Kierlanczyk, A., Sarrafzadeh, M., Caprioli, J., Nouri-Mahdavi, K., Ghasemzadeh, H., & Amini, N. (2015). Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system. In 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015 (pp. 433-438). Article 7134077 (2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PERCOMW.2015.7134077

Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system. / Ma, Yuchao; Henry, Sharon; Kierlanczyk, Alex et al.
2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 433-438 7134077 (2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015).

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

Ma, Y, Henry, S, Kierlanczyk, A, Sarrafzadeh, M, Caprioli, J, Nouri-Mahdavi, K, Ghasemzadeh, H & Amini, N 2015, Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system. in 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015., 7134077, 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015, Institute of Electrical and Electronics Engineers Inc., pp. 433-438, 13th IEEE International Conference on Pervasive Computing and Communication, PerCom Workshops 2015, St. Louis, United States, 3/23/15. https://doi.org/10.1109/PERCOMW.2015.7134077

Ma Y, Henry S, Kierlanczyk A, Sarrafzadeh M, Caprioli J, Nouri-Mahdavi K et al. Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system. In 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 433-438. 7134077. (2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015). doi: 10.1109/PERCOMW.2015.7134077

Ma, Yuchao ; Henry, Sharon ; Kierlanczyk, Alex et al. / Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system. 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 433-438 (2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015).

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abstract = "Many studies have reported that older adults with glaucoma experience mobility issues due to gait difficulties. These include walking slowly and bumping into obstacles, which increase the risk of falls in glaucoma patients. In this paper, we design and develop a shoe-integrated sensing system as well as signal processing and machine learning algorithms to objectively quantify gait patterns in glaucoma patients. The sensor platform was utilized in a randomized clinical trial involving 9 glaucoma patients and 10 age-matched healthy participants performing a series of gait tests. Sensor signals are collected wirelessly and processed on a local computer. With the captured data, we develop data analysis techniques to make a comparison between gait characteristics in older adults with or without glaucoma. Our results demonstrate that the proposed system achieved an accuracy of more than 90% in distinguishing gait patterns of those with glaucoma from healthy individuals for various gait analysis tests.",

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AB - Many studies have reported that older adults with glaucoma experience mobility issues due to gait difficulties. These include walking slowly and bumping into obstacles, which increase the risk of falls in glaucoma patients. In this paper, we design and develop a shoe-integrated sensing system as well as signal processing and machine learning algorithms to objectively quantify gait patterns in glaucoma patients. The sensor platform was utilized in a randomized clinical trial involving 9 glaucoma patients and 10 age-matched healthy participants performing a series of gait tests. Sensor signals are collected wirelessly and processed on a local computer. With the captured data, we develop data analysis techniques to make a comparison between gait characteristics in older adults with or without glaucoma. Our results demonstrate that the proposed system achieved an accuracy of more than 90% in distinguishing gait patterns of those with glaucoma from healthy individuals for various gait analysis tests.

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Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system

Abstract

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Keywords

ASJC Scopus subject areas

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