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      Estimation of Spatial-Temporal Gait Parameters Using a Low-Cost Ultrasonic Motion Analysis System

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          Abstract

          In this paper, a low-cost motion analysis system using a wireless ultrasonic sensor network is proposed and investigated. A methodology has been developed to extract spatial-temporal gait parameters including stride length, stride duration, stride velocity, stride cadence, and stride symmetry from 3D foot displacements estimated by the combination of spherical positioning technique and unscented Kalman filter. The performance of this system is validated against a camera-based system in the laboratory with 10 healthy volunteers. Numerical results show the feasibility of the proposed system with average error of 2.7% for all the estimated gait parameters. The influence of walking speed on the measurement accuracy of proposed system is also evaluated. Statistical analysis demonstrates its capability of being used as a gait assessment tool for some medical applications.

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          Gait assessment in Parkinson's disease: toward an ambulatory system for long-term monitoring.

          Françios J G Vingerhoets, Arash Salarian, Catherine Dehollain … (2004)
          An ambulatory gait analysis method using body-attached gyroscopes to estimate spatio-temporal parameters of gait has been proposed and validated against a reference system for normal and pathologic gait. Later, ten Parkinson's disease (PD) patients with subthalamic nucleus deep brain stimulation (STN-DBS) implantation participated in gait measurements using our device. They walked one to three times on a 20-m walkway. Patients did the test twice: once STN-DBS was ON and once 180 min after turning it OFF. A group of ten age-matched normal subjects were also measured as controls. For each gait cycle, spatio-temporal parameters such as stride length (SL), stride velocity (SV), stance (ST), double support (DS), and gait cycle time (GC) were calculated. We found that PD patients had significantly different gait parameters comparing to controls. They had 52% less SV, 60% less SL, and 40% longer GC. Also they had significantly longer ST and DS (11% and 59% more, respectively) than controls. STN-DBS significantly improved gait parameters. During the stim ON period, PD patients had 31% faster SV, 26% longer SL, 6% shorter ST, and 26% shorter DS. GC, however, was not significantly different. Some of the gait parameters had high correlation with Unified Parkinson's Disease Rating Scale (UPDRS) subscores including SL with a significant correlation (r = -0.90) with UPDRS gait subscore. We concluded that our method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.
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            Position-Location Solutions by Taylor-Series Estimation

            WADE FOY (1976)
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              Minimum foot clearance during walking: strategies for the minimisation of trip-related falls.

              Rezaul Begg, Lisa Dell'Oro, Simon Taylor … (2007)
              This paper models minimum foot clearance (MFC) data during steady-state gait to investigate how the various descriptive statistics of the MFC distribution differ in healthy young and elderly females. A minimum of 20min of treadmill walking was analysed for 17 young and 16 elderly females using a Peak Motus motion analysis system. The results indicated that none of the 33 participants' MFC data sets were Normally distributed. The deviation from a Normal distribution was systematic (always skewness>0 and kurtosis>0). Skewness and kurtosis in MFC data was highly correlated (young: r=0.60, p=0.01; elderly: r=0.95, p<0.01). MFC descriptive statistics provide useful information about basic strategies used by individuals to minimize the likelihood of tripping. Possible strategies to minimize tripping include: (a) increasing MFC height central tendency, (b) reducing MFC variability, and/or (c) increasing right skewness. A low median MFC was often associated with a low IQR or high skewness to compensate. Further research is required to establish how, or if at all, these strategies are modified in populations that are more at risk of falling.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sensors (Basel)
                Journal ID (iso-abbrev): Sensors (Basel)
                Title: Sensors (Basel, Switzerland)
                Publisher: MDPI
                ISSN (Electronic): 1424-8220
                Publication date Collection: August 2014
                Publication date (Electronic): 20 August 2014
                Volume: 14
                Issue: 8
                Pages: 15434-15457
                Affiliations
                School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore; E-Mails: qiyo0001@ 123456e.ntu.edu.sg (Y.Q.); egunawan@ 123456ntu.edu.sg (E.G.); ekslow@ 123456ntu.edu.sg (K.-S.L.); rijil001@ 123456e.ntu.edu.sg (R.T.)
                Author notes
                [* ] Author to whom correspondence should be addressed; E-Mail: ecbsoh@ 123456ntu.edu.sg ; Tel.: +65-6790-5373.
                Article
                Publisher ID: sensors-14-15434
                DOI: 10.3390/s140815434
                PMC ID: 4178990
                PubMed ID: 25140636
                SO-VID: 27ae7964-5f65-4b01-885e-76a3b260c384
                Copyright © © 2014 by the authors; licensee MDPI, Basel, Switzerland.
                License:

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                Date received : 28 May 2014
                Date revision received : 14 August 2014
                Date accepted : 15 August 2014
                Categories
                Subject: Article

                ScienceOpen disciplines: Biomedical engineering
                Keywords: ultrasonic sensor,gait analysis,walking assessment,gait kinematics,wireless sensor network
                Data availability:
                ScienceOpen disciplines: Biomedical engineering
                Keywords: ultrasonic sensor, gait analysis, walking assessment, gait kinematics, wireless sensor network

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