Analysis of gait and coordination for arthroplasty outcome evaluation using body-fixed sensors

The importance of evaluation of an orthopedic operation such as hip or knee arthroplasty has long been recognized. Many definitions of outcome and scoring questionnaires have been used in the past to assess the outcome of joint replacement. However, these assessments are subjective and not accurate enough. In addition, orthopedic surgeons require now more subtle comparisons between potentially efficacious treatments (e.g. two types of prostheses). Therefore, the use of objective instruments that have a better sensitivity and specificity than traditional scoring systems is needed. Gait analysis is one of the most currently used instrumented techniques in this respect. However, a gait analysis system is accessible only in a few specialized laboratories, as it is complex, expensive, need a lot of room space and fixed devices, and not convenient for the patient. In this thesis, we proposed an ambulatory system based on kinematic sensors attached on the lower limbs to overcome the limitations of the previously mentioned techniques. Technically the device is portable, easily mountable, non-invasive, and capable of continuously recording data in long term without hindrance to natural gait. The goal was to provide gait parameters as a new objective method to assess Total Knee Replacement (TKR). New solutions to fusing the data of accelerometers and gyroscopes were proposed to accurately measure lower limbs orientations and joint angles. The methods propose a minimal sensor configuration with one sensor module mounted on each segment. The models consider anatomical aspects and biomechanical constraints. In the proposed techniques, the angles are found without the need for integration, so absolute angles can be obtained which are free from any source of drift. These data were then used to develop a gait analysis system providing spatio-temporal parameters, kinematic curves, and a visualization tool to animate the motion data as synthetic skeletons performing the same actions as the subjects. Moreover, a new algorithm was proposed for assessing and quantification of inter-joint coordination during gait. The coordination model captures the whole dynamics of the lower limbs movements and shows the kinematic synergies at various walking speeds. The model imposes a relationship among lower limb joint angles (hips and knees) to parameterize the dynamics of locomotion for each individual. It provides a coordination score at various walking speeds which is ranged between 0 and 10. An integration of different analysis tools such as Harmonic Analysis, Principal Component Analysis, and Artificial Neural Network helped overcome high-dimensionality, temporal dependence, and non-linear relationships of the gait patterns. In order to show the effectiveness of the proposed methods in outcome evaluation, we have considered a clinical study where the outcomes of two types of knee prostheses were compared. We conducted a randomized controlled study, including 54 patients, to assess TKR outcome between patients with fixed bearing and mobile bearing tibial plates of implants. The patients were tested preoperatively and postoperatively at 6 weeks, 3 months, 6 months, and 1 year. Various statistical analyses were done to compare the outcomes of the two groups. Finally, we provided objective criteria, using ambulatory gait analysis, for assessing functional recovery following TKR procedure. We showed significant difference between the two groups where the standard clinical evaluation was unable to detect such a difference.

Assessment of Foot Signature Using Wearable Sensors for Clinical Gait Analysis and Real-Time Activity Recognition

Benoît Mariani

Locomotion is one of the most important abilities of humans. Actually, gait locomotion provides mobility, and symbolizes freedom and independence. However, gait can be affected by several pathologies, due to aging, neurodegenerative disease, or trauma. The evaluation and treatment of mobility diseases thus requires clinical gait assessment, which is commonly done by using either qualitative analysis based on subjective observations and questionnaires, or expensive analysis established in complex motion laboratories settings. This thesis presents a new wearable system and algorithmic methods for gait assessment in natural conditions, addressing the limitations of existing methods. The proposed system provides quantitative assessment of gait performance through simple and precise outcome measures. The system includes wireless inertial sensors worn on the foot, that record data unobtrusively over long periods of time without interfering with subject's walking. Signal processing algorithms are presented for the automatic calibration and online virtual alignment of sensor signals, the detection of temporal parameters and gait phases, and the estimation of 3D foot kinematics during gait based on fusion methods and biomechanical assumptions. The resulting 3D foot trajectory during one gait cycle is defined as Foot Signature, by analogy with hand-written signature. Spatio-temporal parameters of interest in clinical assessment are derived from foot signature, including commonly parameters, such as stride velocity and gait cycle time, as well as original parameters describing inner-stance phases of gait, foot clearance, and turning. Algorithms based on expert and machine learning methods have been also adapted and implemented in real-time to provide input features to recognize locomotion activities including level walking, stairs, and ramp locomotion. Technical validation of the presented methods against gold standard systems was carried out using experimental protocols on subjects with normal and abnormal gait. Temporal aspects and quantitative estimation of foot-flat were evaluated against pressure insoles in subjects with ankle treatments during long-term gait. Furthermore, spatial parameters and foot clearance were compared in young and elderly persons to data obtained from an optical motion capture system during forward gait trials at various speeds. Finally, turning was evaluated in children with cerebral palsy and people with Parkinson's disease against optical motion capture data captured during timed up and go and figure-of-8 tests. Overall, the results demonstrated that the presently proposed system and methods were precise and accurate, and showed agreement with reference systems as well as with clinical evaluations of subjects' mobility disease using classical scores. Currently, no other methods based on wearable sensors have been validated with such precision to measure foot signature and subsequent parameters during unconstrained walking. Finally, we have used the proposed system in a large-scale clinical application involving more than 1800 subjects from age 7 to 77. This analysis provides reference data of common and original gait parameters, as well as their relationship with walking speed, and allows comparisons between different groups of subjects with normal and abnormal gait. Since the presented methods can be used with any foot-worn inertial sensors, or even combined with other systems, we believe our work to open the door to objective and quantitative routine gait evaluations in clinical settings for supporting diagnosis. Furthermore, the present studies have high potential for further research related to rehabilitation based on real-time devices, the investigation of new parameters' significance and their association with various mobility diseases, as well as for the evaluation of clinical interventions.

EPFL2012

Evaluation of a mixed approach combining stationary and wearable systems to monitor gait over long distance

Kamiar Aminian, Xavier Crevoisier, Julien Favre

Thanks to decades of research, gait analysis has become an efficient tool. However, mainly due to the price of the motion capture systems, standard gait laboratories have the capability to measure only a few consecutive steps of ground walking. Recently, wearable systems were proposed to measure human motion without volume limitation. Although accurate, these systems are incompatible with most of existing calibration procedures and several years of research will be necessary for their validation. A new approach consisting of using a stationary system with a small capture volume for the calibration procedure and then to measure gait using a wearable system could be very advantageous. It could benefit from the knowledge related to stationary systems, allow long distance monitoring and provide new descriptive parameters. The aim of this study was to demonstrate the potential of this approach. Thus, a combined system was proposed to measure the 3D lower body joints angles and segmental angular velocities. It was then assessed in terms of reliability towards the calibration procedure, repeatability and concurrent validity. The dispersion of the joint angles across calibrations was comparable to those of stationary systems and good reliability was obtained for the angular velocities. The repeatability results confirmed that mean cycle kinematics of long distance walks could be used for subjects' comparison and pointed out an interest for the variability between cycles. Finally, kinematics differences were observed between participants with different ankle conditions. In conclusion, this study demonstrated the potential of a mixed approach for human movement analysis. (C) 2010 Elsevier Ltd. All rights reserved.

Elsevier2010

The effects of dual tasks on gait in children with cerebral palsy

Kamiar Aminian, Stéphane Armand, Lena Carcreff

Aim: To assess the gait and cognitive performances of children with cerebral palsy (CP) during dual tasks (DT) in comparison to typically developing (TD) children. Method: This prospective, observational, case-control study included 18 children with CP (7 girls, 11 boys; median age 12 [10:13] years and 19 controls (9 girls, 10 boys; median age 12 [10:13y6mo] years). Performances were recorded during a simple walking task, 5 DT (walking + cognitive tasks with increasing cognitive load), and 5 simple cognitive tasks (while sitting). Gait parameters were computed using an optoelectronic system during walking tasks. Six parameters were selected for analysis by a principal component analysis. Cognitive performance was measured for each cognitive task. The dual-task cost (DTC) was calculated for each DT. Results: Gait performance decreased in both groups as DT cognitive load increased (e.g., walking speed normalized by leg length, in simple task: 1.25 [1.15:1.46] s −1 for CP, 1.53 [1.38:1.62] s −1 for TD; DT with highest load: 0.64 [0.53:0.80] s −1 for CP, 0.95 [0.75:1.08] s −1 for TD). The CP group performed significantly worse than TD group in every task (including the simple task), but DTC were similar in both groups. A task effect was found for the majority of the gait parameters. Interpretation: The reduced gait performance induced by DT may generate underestimated difficulties for children with CP in daily-life situations, where DT are common. This should be considered in clinical assessments.

2019

Assessment of Foot Signature Using Wearable Sensors for Clinical Gait Analysis and Real-Time Activity Recognition

Benoît Mariani

EPFL2012