Estimation of minimum ground clearance (MGC) using body-worn inertial sensors

Denise McGrath; Barry Greene; Cathal Walsh; Brian Caulfield

doi:10.1016/j.jbiomech.2011.01.034

Estimation of minimum ground clearance (MGC) using body-worn inertial sensors

Denise McGrath, Barry Greene, Cathal Walsh, Brian Caulfield

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

25 Citations (Scopus)

Abstract

Objective assessment of balance and mobility in elderly populations using body-worn sensors has recently become a prevalent theme in falls-related research. Recent research by the authors identified mean absolute-valued vertical angular velocity measured using shank mounted inertial sensors during a timed-up-and-go test as having a strong association with falls history in a group of elderly adults. This study aimed to investigate the clinical relevance of this parameter by exploring the relationship between it and minimum ground clearance (MGC) measured with an optical motion capture system. MGC is an important variable when considering trip-related falls risk. This paper also presents a method of estimating properties of MGC during walking, across a range of speeds and gait patterns, using body-worn inertial sensors. We found that mean MGC and coefficient of variation (CV) MGC are correlated with mean absolute-valued vertical angular velocity and acceleration as measured by shank or foot mounted inertial sensors. Regression models generated using inertial sensor derived variables were used to robustly estimate the mean MGC and CV MGC measured by an optical marker-tracking system. Foot-mounted sensors were found to yield slightly better results than sensors on the shank. Different walking speeds and gait patterns were not found to influence the accuracy of the models. We conclude that these findings have the potential to evaluate a walking trial using body-worn inertial sensors, which could then be used to identify individuals with increased risk of unprovoked collisions with the ground during locomotion.

Original language	English
Pages (from-to)	1083-1088
Journal	Journal of Biomechanics
Volume	44
DOIs	https://doi.org/10.1016/j.jbiomech.2011.01.034
Publication status	Published (in print/issue) - 2011

Bibliographical note

Reference text: Begg, R., Best, R., Dell’oro, L., et al., 2007. Minimum foot clearance during walking: strategies for the minimisation of trip-related falls. Gait Posture 25 (2), 191–198.
Burns, A., Greene, B.R., Mcgrath, M.J., et al., 2010. SHIMMER(TM) — a wireless sensor platform for non-invasive biomedical research. IEEE Sensors Journal, IEEE Sensors, 101527–101534.
Dingwell, J.B., Ulbrecht, J.S., Boch, J., et al., 1999. Neuropathic gait shows only trends towards increased variability of sagittal plane kinematics during treadmill locomotion. Gait & Posture 10 (1), 21–29.
Ferraris, F., Grimaldi, U., Parvis, M., 1995. Procedure for effortless in-field calibration of three-axis rate gyros and accelerometers. Sensor and Materials 7 (5), 311–330.
Goble, D.J., Coxon, J.P., Wenderoth, N., et al., 2009. Proprioceptive sensibility in the elderly: degeneration, functional consequences and plastic-adaptive processes. Neuroscience & Biobehavioral Reviews 33 (3), 271–278.
Greene, B.R., O’donovan, A., Romero-Ortuno, R., et al., 2010. Quantitative falls risk assessment using the timed up and go test. IEEE Transactions Biomedical Engineering, 572918–572926.
Karst, G.M., Hageman, P.A., Jones, T.F., et al., 1999. Reliability of foot trajectory measures within and between testing sessions. Journal of Gerontology A: Biological Sciences and Medical Sciences 54 (7), M343–M347.
Khandoker, A.H., Taylor, S.B., Karmakar, C.K., etal., 2008. Investigating scale invariant dynamics in minimum toe clearance variability of the young and elderly during treadmill walking. IEEE Transactions on Neural Systems and Rehabilitation Engineering 16 (4), 380–389.
Lai, D.T., Charry, E., Begg, R., et al., 2008. A prototype wireless inertial-sensing device for measuring toe clearance. Conference Proceedings IEEE Engineering in Medicine and Biology Society 20084899-902.
Mariani, B., Hoskovec, C., Rochat, S., et al., 2010. 3D gait assessment in young and elderly subjects using foot-worn inertial sensors. Journal of Biomechanics 43 (15), 2999–3006.
Mills, P.M., Barrett, R.S., Morrison,S., 2008. Toe clearance variability during walking in young and elderly men. Gait Posture 28 (1),101–107.
Nakasa, T., Fukuhara, K., Adachi, N., et al., 2008. The deficit of joint position sense in the chronic unstable ankle as measured by inversion angle replication error. Archives of Orthopaedic and Trauma Surgery 128 (5), 445–449.
Osaki, Y., Kunin, M., Cohen, B., et al., 2007. Three-dimensional kinematics and dynamics of the foot during walking: a model of central control mechanisms. Experimental Brain Research 176 (3), 476–496.
Winter, D.A., 1992. Foot trajectory in human gait: a precise and multifactorial motor control task. Physical Therapy 72 (1), 45–53 discussion 54-6.

Keywords

Inertial sensor
Minimum ground clearance
Falls risk.

Access to Document

10.1016/j.jbiomech.2011.01.034

http://uir.ulster.ac.uk/24145/1/Estimation_of_minimum_ground_clearance_using_body_worn_sensors.pdf

Cite this

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title = "Estimation of minimum ground clearance (MGC) using body-worn inertial sensors",

abstract = "Objective assessment of balance and mobility in elderly populations using body-worn sensors has recently become a prevalent theme in falls-related research. Recent research by the authors identified mean absolute-valued vertical angular velocity measured using shank mounted inertial sensors during a timed-up-and-go test as having a strong association with falls history in a group of elderly adults. This study aimed to investigate the clinical relevance of this parameter by exploring the relationship between it and minimum ground clearance (MGC) measured with an optical motion capture system. MGC is an important variable when considering trip-related falls risk. This paper also presents a method of estimating properties of MGC during walking, across a range of speeds and gait patterns, using body-worn inertial sensors. We found that mean MGC and coefficient of variation (CV) MGC are correlated with mean absolute-valued vertical angular velocity and acceleration as measured by shank or foot mounted inertial sensors. Regression models generated using inertial sensor derived variables were used to robustly estimate the mean MGC and CV MGC measured by an optical marker-tracking system. Foot-mounted sensors were found to yield slightly better results than sensors on the shank. Different walking speeds and gait patterns were not found to influence the accuracy of the models. We conclude that these findings have the potential to evaluate a walking trial using body-worn inertial sensors, which could then be used to identify individuals with increased risk of unprovoked collisions with the ground during locomotion.",

keywords = "Inertial sensor, Minimum ground clearance, Falls risk.",

author = "Denise McGrath and Barry Greene and Cathal Walsh and Brian Caulfield",

note = "Reference text: Begg, R., Best, R., Dell{\textquoteright}oro, L., et al., 2007. Minimum foot clearance during walking: strategies for the minimisation of trip-related falls. Gait Posture 25 (2), 191–198. Burns, A., Greene, B.R., Mcgrath, M.J., et al., 2010. SHIMMER(TM) — a wireless sensor platform for non-invasive biomedical research. IEEE Sensors Journal, IEEE Sensors, 101527–101534. Dingwell, J.B., Ulbrecht, J.S., Boch, J., et al., 1999. Neuropathic gait shows only trends towards increased variability of sagittal plane kinematics during treadmill locomotion. Gait & Posture 10 (1), 21–29. Ferraris, F., Grimaldi, U., Parvis, M., 1995. Procedure for effortless in-field calibration of three-axis rate gyros and accelerometers. Sensor and Materials 7 (5), 311–330. Goble, D.J., Coxon, J.P., Wenderoth, N., et al., 2009. Proprioceptive sensibility in the elderly: degeneration, functional consequences and plastic-adaptive processes. Neuroscience & Biobehavioral Reviews 33 (3), 271–278. Greene, B.R., O{\textquoteright}donovan, A., Romero-Ortuno, R., et al., 2010. Quantitative falls risk assessment using the timed up and go test. IEEE Transactions Biomedical Engineering, 572918–572926. Karst, G.M., Hageman, P.A., Jones, T.F., et al., 1999. Reliability of foot trajectory measures within and between testing sessions. Journal of Gerontology A: Biological Sciences and Medical Sciences 54 (7), M343–M347. Khandoker, A.H., Taylor, S.B., Karmakar, C.K., etal., 2008. Investigating scale invariant dynamics in minimum toe clearance variability of the young and elderly during treadmill walking. IEEE Transactions on Neural Systems and Rehabilitation Engineering 16 (4), 380–389. Lai, D.T., Charry, E., Begg, R., et al., 2008. A prototype wireless inertial-sensing device for measuring toe clearance. Conference Proceedings IEEE Engineering in Medicine and Biology Society 20084899-902. Mariani, B., Hoskovec, C., Rochat, S., et al., 2010. 3D gait assessment in young and elderly subjects using foot-worn inertial sensors. Journal of Biomechanics 43 (15), 2999–3006. Mills, P.M., Barrett, R.S., Morrison,S., 2008. Toe clearance variability during walking in young and elderly men. Gait Posture 28 (1),101–107. Nakasa, T., Fukuhara, K., Adachi, N., et al., 2008. The deficit of joint position sense in the chronic unstable ankle as measured by inversion angle replication error. Archives of Orthopaedic and Trauma Surgery 128 (5), 445–449. Osaki, Y., Kunin, M., Cohen, B., et al., 2007. Three-dimensional kinematics and dynamics of the foot during walking: a model of central control mechanisms. Experimental Brain Research 176 (3), 476–496. Winter, D.A., 1992. Foot trajectory in human gait: a precise and multifactorial motor control task. Physical Therapy 72 (1), 45–53 discussion 54-6.",

year = "2011",

doi = "10.1016/j.jbiomech.2011.01.034",

language = "English",

volume = "44",

pages = "1083--1088",

journal = "Journal of Biomechanics",

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AU - McGrath, Denise

AU - Greene, Barry

AU - Walsh, Cathal

AU - Caulfield, Brian

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N2 - Objective assessment of balance and mobility in elderly populations using body-worn sensors has recently become a prevalent theme in falls-related research. Recent research by the authors identified mean absolute-valued vertical angular velocity measured using shank mounted inertial sensors during a timed-up-and-go test as having a strong association with falls history in a group of elderly adults. This study aimed to investigate the clinical relevance of this parameter by exploring the relationship between it and minimum ground clearance (MGC) measured with an optical motion capture system. MGC is an important variable when considering trip-related falls risk. This paper also presents a method of estimating properties of MGC during walking, across a range of speeds and gait patterns, using body-worn inertial sensors. We found that mean MGC and coefficient of variation (CV) MGC are correlated with mean absolute-valued vertical angular velocity and acceleration as measured by shank or foot mounted inertial sensors. Regression models generated using inertial sensor derived variables were used to robustly estimate the mean MGC and CV MGC measured by an optical marker-tracking system. Foot-mounted sensors were found to yield slightly better results than sensors on the shank. Different walking speeds and gait patterns were not found to influence the accuracy of the models. We conclude that these findings have the potential to evaluate a walking trial using body-worn inertial sensors, which could then be used to identify individuals with increased risk of unprovoked collisions with the ground during locomotion.

AB - Objective assessment of balance and mobility in elderly populations using body-worn sensors has recently become a prevalent theme in falls-related research. Recent research by the authors identified mean absolute-valued vertical angular velocity measured using shank mounted inertial sensors during a timed-up-and-go test as having a strong association with falls history in a group of elderly adults. This study aimed to investigate the clinical relevance of this parameter by exploring the relationship between it and minimum ground clearance (MGC) measured with an optical motion capture system. MGC is an important variable when considering trip-related falls risk. This paper also presents a method of estimating properties of MGC during walking, across a range of speeds and gait patterns, using body-worn inertial sensors. We found that mean MGC and coefficient of variation (CV) MGC are correlated with mean absolute-valued vertical angular velocity and acceleration as measured by shank or foot mounted inertial sensors. Regression models generated using inertial sensor derived variables were used to robustly estimate the mean MGC and CV MGC measured by an optical marker-tracking system. Foot-mounted sensors were found to yield slightly better results than sensors on the shank. Different walking speeds and gait patterns were not found to influence the accuracy of the models. We conclude that these findings have the potential to evaluate a walking trial using body-worn inertial sensors, which could then be used to identify individuals with increased risk of unprovoked collisions with the ground during locomotion.

KW - Inertial sensor

KW - Minimum ground clearance

KW - Falls risk.

U2 - 10.1016/j.jbiomech.2011.01.034

DO - 10.1016/j.jbiomech.2011.01.034

M3 - Article

SN - 1873-2380

VL - 44

SP - 1083

EP - 1088

JO - Journal of Biomechanics

JF - Journal of Biomechanics

ER -

Estimation of minimum ground clearance (MGC) using body-worn inertial sensors

Abstract

Bibliographical note

Keywords

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