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      Balance and knee extensibility evaluation of hemiplegic gait using an inertial body sensor network

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          Abstract

          Background

          Most hemiplegic patients have difficulties in their balance and posture control while walking because of the asymmetrical posture and the abnormal body balance. The assessment of rehabilitation of hemiplegic gait is usually made by doctors using clinical scale, but it is difficult and could not be used frequently. It is therefore needed to quantitatively analyze the characteristics of hemiplegic gait. Thus the assessment would be simple, and real-time evaluation of rehabilitation could be carried out.

          Methods

          Twenty subjects (ten hemiplegic patients, ten normal subjects) were recruited. The subjects walked straight for five meters at their self-selected comfortable speed towards a target line on the floor.

          Xsens MTx motion trackers were used for acquiring gestures of body segments to estimate knee joint angles and identify gait cycles. A practical method for data acquisition that does not need to obtain accurate distances between a knee joint and its corresponding sensors is presented.

          Results

          The results showed that there were significant differences between the two groups in the three nominated angle amplitudes. The mean values of balance level of each parameter in hemiplegic gait and normal gait were: 0.21 versus 0.01, 0.18 versus 0.03, and 0.92 versus 0.03, respectively. The mean values of added angles of each parameter in hemiplegic gait and normal gait were: 74.64 versus 91.31, -76.48 versus −132.4, and 6.77 versus 35.74.

          Conclusions

          It was concluded that the wearable bio-motion acquisition platform provided a practical approach that was effective in discriminating gait symptoms between hemiplegic and asymptomatic subjects. The extensibility of hemiplegic patients’ lower limbs was significantly lower than that of normal subjects, and the hemiplegic gait had worse balance level compared with normal gait. The effect of rehabilitation training of hemiplegic gait could be quantitatively analyzed.

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          Most cited references23

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          Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes.

          K. Aminian, B Najafi, C Büla … (2002)
          In this study we describe an ambulatory system for estimation of spatio-temporal parameters during long periods of walking. This original method based on wavelet analysis is proposed to compute the values of temporal gait parameters from the angular velocity of lower limbs. Based on a mechanical model, the medio-lateral rotation of the lower limbs during stance and swing, the stride length and velocity are estimated by integration of the angular velocity. Measurement's accuracy was assessed using as a criterion standard the information provided by foot pressure sensors. To assess the accuracy of the method on a broad range of performance for each gait parameter, we gathered data from young and elderly subjects. No significant error was observed for toe-off detection, while a slight systematic delay (10 ms on average) existed between heelstrike obtained from gyroscopes and footswitch. There was no significant difference between actual spatial parameters (stride length and velocity) and their estimated values. Errors for velocity and stride length estimations were 0.06 m/s and 0.07 m, respectively. This system is light, portable, inexpensive and does not provoke any discomfort to subjects. It can be carried for long periods of time, thus providing new longitudinal information such as stride-to-stride variability of gait. Several clinical applications can be proposed such as outcome evaluation after total knee or hip replacement, external prosthesis adjustment for amputees, monitoring of rehabilitation progress, gait analysis in neurological diseases, and fall risk estimation in elderly.
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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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              Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems.

              Ruth E. Mayagoitia, Anand V Nene, Peter Veltink (2002)
              A general-purpose system to obtain the kinematics of gait in the sagittal plane based on body-mounted sensors was developed. It consisted of four uniaxial seismic accelerometers and one rate gyroscope per body segment. Tests were done with 10 young healthy volunteers, walking at five different speeds on a treadmill. In order to study the system's accuracy, measurements were made with an optic, passive-marker system and the body-mounted system, simultaneously. In all the comparison cases, the curves obtained from the two systems were very close, showing root mean square errors representing <7% full range in 75% of the cases (overall mean 6.64%, standard deviation 4.13%) and high coefficients of multiple correlation in 100% of cases (overall mean 0.9812, standard deviation 0.02). Calibration of the body-mounted system is done against gravity. The body-mounted sensors do not hinder natural movement. The calculation algorithms are computationally demanding and only are applicable off-line. The body-mounted sensors are accurate, inexpensive and portable and allow long-term recordings in clinical, sport and ergonomics settings.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Biomed Eng Online
                Journal ID (iso-abbrev): Biomed Eng Online
                Title: BioMedical Engineering OnLine
                Publisher: BioMed Central
                ISSN (Electronic): 1475-925X
                Publication date Collection: 2013
                Publication date (Electronic): 29 August 2013
                Volume: 12
                Page: 83
                Affiliations
                [1 ]Shenzhen Institutes of Advanced Technology, The Shenzhen Key Laboratory for Low-cost Healthcare, Shenzhen University Town, 1068 Xueyuan Avenue, Shenzhen 518055, PR China
                [2 ]Graduate University of Chinese Academy of Sciences, Beijing 10049, PR China
                [3 ]School of Physical Education & Sports Science, South China Normal University, Guangzhou, China
                Article
                Publisher ID: 1475-925X-12-83
                DOI: 10.1186/1475-925X-12-83
                PMC ID: 3766026
                PubMed ID: 23988116
                SO-VID: 60596a56-b4b8-4bfa-ab24-888cdc112f08
                Copyright © Copyright ©2013 Guo et al.; licensee BioMed Central Ltd.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 6 May 2013
                Date accepted : 24 August 2013
                Categories
                Subject: Research

                ScienceOpen disciplines: Biomedical engineering
                Keywords: gait analysis,body sensor network,hemiplegic gait,biomechanics
                Data availability:
                ScienceOpen disciplines: Biomedical engineering
                Keywords: gait analysis, body sensor network, hemiplegic gait, biomechanics

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