Unobtrusive and ubiquitous in-home monitoring: A methodology for continuous assessment of gait velocity in elders

Stuart Hagler; Daniel Austin; Tamara L. Hayes; Jeffrey Kaye; Misha Pavel

doi:10.1109/TBME.2009.2036732

Unobtrusive and ubiquitous in-home monitoring: A methodology for continuous assessment of gait velocity in elders

Stuart Hagler
, Daniel Austin
, Tamara L. Hayes
, Jeffrey Kaye
, Misha Pavel

Neurology

Research output: Contribution to journal › Article › peer-review

140 Scopus citations

Abstract

Gait velocity has been shown to quantitatively estimate risk of future hospitalization, a predictor of disability, and has been shown to slow prior to cognitive decline. In this paper, we describe a system for continuous and unobtrusive in-home assessment of gait velocity, a critical metric of function. This system is based on estimating walking speed from noisy time and location data collected by a "sensor line" of restricted view passive infrared motion detectors. We demonstrate the validity of our system by comparing with measurements from the commercially available GAITRite walkway system gait mat. We present the data from 882 walks from 27 subjects walking at three different subject-paced speeds (encouraged to walk slowly, normal speed, or fast) in two directions through a sensor line. The experimental results show that the uncalibrated system accuracy (average error) of estimated velocity was 7.1 cm/s (SD $=$ 11.3 cm/s), which improved to 1.1 cm/s (SD $=$ 9.1 cm/s) after a simple calibration procedure. Based on the average measured walking speed of 102 cm/s, our system had an average error of less than 7% without calibration and 1.1% with calibration.

Original language	English (US)
Article number	5339193
Pages (from-to)	813-820
Number of pages	8
Journal	IEEE Transactions on Biomedical Engineering
Volume	57
Issue number	4
DOIs	https://doi.org/10.1109/TBME.2009.2036732
State	Published - Apr 2010

Funding

Manuscript received July 20, 2009; revised September 24, 2009. First published November 20, 2009; current version published March 24, 2010. This work was supported in part by the National Institutes of Health, in part by the National Institute on Aging under Grant R01AG024059, Grant P30AG024978, and Grant P30AG008017, and in part by Intel Corporation. Asterisk indicates corresponding author.

Funders	Funder number
Author National Institutes of Health National Institutes of Health National Institutes of Health National Institutes of Health The Bev Hartig Huntington's Disease Foundation National Institutes of Health
National Institute of Aging	R01AG024059, P30AG008017, P30AG024978
Intel Corporation

Keywords

Eldercare
Gait
Passive infrared (PIR) motion detectors
Ubiquitous computing
Unobtrusive monitoring
Walking speed

ASJC Scopus subject areas

Biomedical Engineering

Access to Document

10.1109/TBME.2009.2036732

Cite this

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title = "Unobtrusive and ubiquitous in-home monitoring: A methodology for continuous assessment of gait velocity in elders",

abstract = "Gait velocity has been shown to quantitatively estimate risk of future hospitalization, a predictor of disability, and has been shown to slow prior to cognitive decline. In this paper, we describe a system for continuous and unobtrusive in-home assessment of gait velocity, a critical metric of function. This system is based on estimating walking speed from noisy time and location data collected by a {"}sensor line{"} of restricted view passive infrared motion detectors. We demonstrate the validity of our system by comparing with measurements from the commercially available GAITRite walkway system gait mat. We present the data from 882 walks from 27 subjects walking at three different subject-paced speeds (encouraged to walk slowly, normal speed, or fast) in two directions through a sensor line. The experimental results show that the uncalibrated system accuracy (average error) of estimated velocity was 7.1 cm/s (SD \$=\$ 11.3 cm/s), which improved to 1.1 cm/s (SD \$=\$ 9.1 cm/s) after a simple calibration procedure. Based on the average measured walking speed of 102 cm/s, our system had an average error of less than 7\% without calibration and 1.1\% with calibration.",

keywords = "Eldercare, Gait, Passive infrared (PIR) motion detectors, Ubiquitous computing, Unobtrusive monitoring, Walking speed",

author = "Stuart Hagler and Daniel Austin and Hayes, \{Tamara L.\} and Jeffrey Kaye and Misha Pavel",

note = "Funding Information: Manuscript received July 20, 2009; revised September 24, 2009. First published November 20, 2009; current version published March 24, 2010. This work was supported in part by the National Institutes of Health, in part by the National Institute on Aging under Grant R01AG024059, Grant P30AG024978, and Grant P30AG008017, and in part by Intel Corporation. Asterisk indicates corresponding author.",

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AU - Pavel, Misha

N1 - Funding Information: Manuscript received July 20, 2009; revised September 24, 2009. First published November 20, 2009; current version published March 24, 2010. This work was supported in part by the National Institutes of Health, in part by the National Institute on Aging under Grant R01AG024059, Grant P30AG024978, and Grant P30AG008017, and in part by Intel Corporation. Asterisk indicates corresponding author.

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N2 - Gait velocity has been shown to quantitatively estimate risk of future hospitalization, a predictor of disability, and has been shown to slow prior to cognitive decline. In this paper, we describe a system for continuous and unobtrusive in-home assessment of gait velocity, a critical metric of function. This system is based on estimating walking speed from noisy time and location data collected by a "sensor line" of restricted view passive infrared motion detectors. We demonstrate the validity of our system by comparing with measurements from the commercially available GAITRite walkway system gait mat. We present the data from 882 walks from 27 subjects walking at three different subject-paced speeds (encouraged to walk slowly, normal speed, or fast) in two directions through a sensor line. The experimental results show that the uncalibrated system accuracy (average error) of estimated velocity was 7.1 cm/s (SD $=$ 11.3 cm/s), which improved to 1.1 cm/s (SD $=$ 9.1 cm/s) after a simple calibration procedure. Based on the average measured walking speed of 102 cm/s, our system had an average error of less than 7% without calibration and 1.1% with calibration.

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Unobtrusive and ubiquitous in-home monitoring: A methodology for continuous assessment of gait velocity in elders

Abstract

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Keywords

ASJC Scopus subject areas

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