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

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 in, 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. (C) 2002 Published by Elsevier Science Ltd.

Evaluation of an ambulatory system for gait analysis in hip osteoarthritis and after total hip replacement

Kamiar Aminian, Hooman Dejnabadi, Bijan Najafi, Philippe Robert

Spatial and temporal parameters of gait have clinical relevance in the assessment of motor pathologies, particularly in orthopaedics. A new gait analysis system is proposed which consists of (a) an ambulatory device (Physilog(R)) including a set of miniature gyroscopes and a portable datalogger, and (b) an algorithm for gait analysis. The aim of this study was the validation of this system, for accuracy and clinical applicability. Eleven patients with coxarthrosis, eight patients with total hip arthroplasty and nine control subjects were studied using this portable system and also a reference motion analyzer and force plate. The small differences in the stance period (19 +/- 31 ms), stride length and velocity (0.4 +/- 9.6 cm and 2.5 +/- 8.3 cm/s, respectively), as well as thigh and shank rotations (2.4 +/- 4.3degrees and 0.3 +/- 3.3degrees, respectively), confirmed good agreement of the proposed system with the reference system. In addition, nearly the same accuracy was obtained for all three groups. Gait analysis based on Physilog(R) was also in agreement with their Harris Hip Scores (HHS): the subjects with lower scores had a greater limp, a slower walking speed and a shorter stride. This ambulatory gait analysis system provides an easy, reproducible and objective method of quantifying changes in gait after joint replacement surgery for coxarthrosis. (C) 2003 Elsevier B.V. All rights reserved.

2004

Ambulatory monitoring of motor functions in patients with Parkinson's disease using kinematic sensors

Arash Salarian

Parkinson's disease (PD) is the second most common neurodegenerative disease in the general population. Cardinal symptoms of Parkinson's disease are resting tremor, rigidity, akinesia and bradykinesia and in advanced stages, gait impairments, postural instability and complications of chronic treatment with levodopa such as motor dysfunctions and dyskinesia. Multitude and complexity of these motor symptoms and their variability over the time have made assessment of them a difficult task. Moreover, following the fluctuations of motor performance (ON/OFF fluctuations) of the PD patients throughout their daily activities by quantifying their motor symptoms is a major challenge. The aim of this thesis was to design and validate a portable ambulatory movement analysis system for long-term monitoring and qualitative and quantitative assessment of motor abnormalities of PD patients during daily activities. We have designed a new measurement system consisting of five independent, lightweight, autonomous sensing units based on kinematic sensors that can continuously record body movements during daily life. Using this system and by performing several clinical studies, both in controlled conditions and on free moving patients, we have prepared a database of different movement patterns of PD patients. This database was the basis to design several new algorithms for the analysis of tremor, bradykinesia, gait and posture. An accurate algorithm based on spectral estimation has been proposed to detect and quantify tremor during daily activities of PD patients with a resolution down to three seconds using gyroscopes attached to the forearms. By quantifying the speed, range and the frequency of the movements, we have proposed a new method to assess the bradykinesia and tested it both in controlled and free conditions. We found out that in the free moving patients, the outcomes of this algorithm show significant and good correlation to the established clinical scores. Regarding the detection and analysis of gait, we have developed and tested a method based on four sensors attached to the lower limbs that provided spatio-temporal parameters of gait with good accuracy. We further improved our method using a new biomechanical model that could predict the movements of thighs from the movements of shanks during walking. This way we could reduce the number of sensor sites on the body while keeping the same accuracy in estimation of the spatio-temporal parameters of gait. By combining a statistical classifier, to detect transitions between sitting and standing postures, and a fuzzy classifier, to detect the basic body postures, we have developed an algorithm to classify basic body posture allocations both in PD patients and aged matched healthy subjects. Finally, while currently no other objective ambulatory method exists to accurately detect the periods of ON and OFF in PD patients, by combining the outcomes of the above algorithms (tremor, gait, bradykinesia and posture) using a statistical approach, we have proposed a method to detect periods of these two states with a resolution of 10 minutes in free moving patients. We believe that the proposed system has a high potential both for the clinical applications and research purposes related to the patient with Parkinson's disease and possibly other neurological movement disorders.

EPFL2006

Falling Risk Evaluation in Elderly Using Miniature Gyroscope: Relation Between Gait and Risk of Falling

Kamiar Aminian, Bijan Najafi, Philippe Robert

Falls are the leading cause of injury-related morbidity and mortality among elderlypersons and are associated with significant adverse psychological andphysical consequences [1].Evaluating fall risk is important because it allows better targeting for preventiveand assistive interventions to at risk subjects. Most falls occur during walkingand several studies have demonstrated an association between changes in gaitand risk of falling in older adults [2]. Despite these findings, fall risk is mainlyassessed by using questionnaires or semi-objective performance measuresbecause no simple objective method is available for routine gait analysis.Overcoming problems of reliability and subjectivity of currently used methodscould lead to substantial improvements in the accuracy of fall risk assessment[3].Relation of posture transition with risk of failing based on an ambulatory systemhas been shown before [4]. In this paper, we describe a new ambulatorymethod in gait analysis. In addition we present results of a validation test of thissystem against a footswitch-based gait analysis system, and describe the performanceof this system in stratifying fall risk in a sample of older persons.

2001

Ambulatory monitoring of motor functions in patients with Parkinson's disease using kinematic sensors

Arash Salarian

EPFL2006