Chronic low back pain patients walk with locally altered spinal kinematics

Various studies have reported alterations of spinal kinematics in patients with chronic low back pain (CLBP) during gait. However, while recent findings stressed the importance of multi-segment analysis, most of prior gait studies modelled the lumbar spine as one segment, when it was not the entire trunk that was considered as a single segment. Therefore, there is a need for comprehensive multi-segment research that could improve our understanding of CLBP pathomechanism and thus possibly contribute to better care for CLBP. This study aimed at characterizing the angle patterns at the lower lumbar (LLS), upper lumbar (ULS), lower thoracic (LTS) and upper thoracic (UTS) joints in the three anatomical planes and at comparing CLBP patients and asymptomatic subjects. Spinal kinematics of 11 CLBP patients and 11 controls was measured using a marker-based motion capture system and described according to a previously proposed multi-segment biomechanical model. Characteristic patterns were observed at the UTS, LTS and ULS joints in the transverse plane and at the UTS, ULS and LLS joints in the frontal plane. CLBP patients walked with smaller frontal-plane LLS range of motion than controls. The results also suggested that patients had more asymmetrical LTS motion in the transverse plane. In conclusion, this work extended prior literature by showing specific CLBP-related alterations in multi-segment spinal kinematics during gait. Further research is necessary to understand the factors influencing kinematics alterations and how treatment strategies might improve motor behaviour in CLBP patients. (C) 2017 Elsevier Ltd. All rights reserved.

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

3D gait assessment in young and elderly subjects using foot-worn inertial sensors

Kamiar Aminian, Benoît Mariani

This study describes the validation of a new wearable system for assessment of 3D spatial parameters of gait. The new method is based on the detection of temporal parameters, coupled to optimized fusion and de-drifted integration of inertial signals. Composed of two wirelesses inertial modules attached on feet, the system provides stride length, stride velocity, foot clearance, and turning angle parameters at each gait cycle, based on the computation of 3D foot kinematics. Accuracy and precision of the proposed system were compared to an optical motion capture system as reference. Its repeatability across measurements (test-retest reliability) was also evaluated. Measurements were performed in 10 young (mean age 26.1 +/- 2.8 years) and 10 elderly volunteers (mean age 71.6 +/- 4.6 years) who were asked to perform U-shaped and 8-shaped walking trials, and then a 6-min walking test (6 MWT). A total of 974 gait cycles were used to compare gait parameters with the reference system. Mean accuracy +/- precision was 1.5 +/- 6.8 cm for stride length, 1.4 +/- 5.6 cm/s for stride velocity, 1.9 +/- 2.0 cm for foot clearance, and 1.6 +/- 6.1 degrees for turning angle. Difference in gait performance was observed between young and elderly volunteers during the 6 MWT particularly in foot clearance. The proposed method allows to analyze various aspects of gait, including turns, gait initiation and termination, or inter-cycle variability. The system is lightweight, easy to wear and use, and suitable for clinical application requiring objective evaluation of gait outside of the lab environment. (C) 2010 Elsevier Ltd. All rights reserved.

Elsevier2010

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

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

Benoît Mariani

EPFL2012