scholarly journals The Accuracy and Precision of Gait Spatio-Temporal Parameters Extracted from an Instrumented Sock during Treadmill and Overground Walking in Healthy Subjects and Patients with a Foot Impairment Secondary to Psoriatic Arthritis

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6179
Author(s):  
Roua Walha ◽  
Karina Lebel ◽  
Nathaly Gaudreault ◽  
Pierre Dagenais ◽  
Andrea Cereatti ◽  
...  
Keyword(s):  
Psoriatic Arthritis ◽  
Motion Capture ◽  
Treadmill Walking ◽  
Cycle Duration ◽  
Motion Capture System ◽  
Overground Walking ◽  
Temporal Parameters ◽  
Parameter Estimations ◽  
Accuracy And Precision ◽  
Spatio Temporal

The objectives of this study were to assess the accuracy and precision of a system combining an IMU-instrumented sock and a validated algorithm for the estimation of the spatio-temporal parameters of gait. A total of 25 healthy participants (HP) and 21 patients with foot impairments secondary to psoriatic arthritis (PsA) performed treadmill walking at three different speeds and overground walking at a comfortable speed. HP performed the assessment over two sessions. The proposed system’s estimations of cadence (CAD), gait cycle duration (GCD), gait speed (GS), and stride length (SL) obtained for treadmill walking were validated versus those estimated with a motion capture system. The system was also compared with a well-established multi-IMU-based system for treadmill and overground walking. The results showed a good agreement between the motion capture system and the IMU-instrumented sock in estimating the spatio-temporal parameters during the treadmill walking at normal and fast speeds for both HP and PsA participants. The accuracy of GS and SL obtained from the IMU-instrumented sock was better compared to the established multi-IMU-based system in both groups. The precision (inter-session reliability) of the gait parameter estimations obtained from the IMU-instrumented sock was good to excellent for overground walking and treadmill walking at fast speeds, but moderate-to-good for slow and normal treadmill walking. The proposed IMU-instrumented sock offers a novel form factor addressing the wearability issues of IMUs and could potentially be used to measure spatio-temporal parameters under clinical conditions and free-living conditions.

Influence of the overground walking speed control modality: Modification to the walk ratio and spatio-temporal parameters of gait

2021 ◽  
Vol 83 ◽  
pp. 256-261
Author(s):  
T. Legrand ◽  
H. Younesian ◽  
C. Gélinas-Trudel ◽  
C.V. Barthod ◽  
A. Campeau-Lecours ◽  
...  
Keyword(s):  
Walking Speed ◽  
Speed Control ◽  
Overground Walking ◽  
Temporal Parameters ◽  
Walk Ratio ◽  
Spatio Temporal

Is gait variability reliable? An assessment of spatio-temporal parameters of gait variability during continuous overground walking

2014 ◽  
Vol 39 (1) ◽  
pp. 615-617 ◽  
Author(s):  
N. König ◽  
N.B. Singh ◽  
J. von Beckerath ◽  
L. Janke ◽  
W.R. Taylor
Keyword(s):  
Gait Variability ◽  
Overground Walking ◽  
Temporal Parameters ◽  
Spatio Temporal

scholarly journals Overground Walking in a Fully Immersive Virtual Reality: A Comprehensive Study on the Effects on Full-Body Walking Biomechanics

2021 ◽  
Vol 9 ◽  
Author(s):  
Brian Horsak ◽  
Mark Simonlehner ◽  
Lucas Schöffer ◽  
Bernhard Dumphart ◽  
Arian Jalaeefar ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Real World ◽  
Gait Training ◽  
Gait Rehabilitation ◽  
Overground Walking ◽  
Convenience Sample ◽  
Single Measure ◽  
The Real ◽  
Temporal Parameters ◽  
Spatio Temporal

Virtual reality (VR) is an emerging technology offering tremendous opportunities to aid gait rehabilitation. To this date, real walking with users immersed in virtual environments with head-mounted displays (HMDs) is either possible with treadmills or room-scale (overground) VR setups. Especially for the latter, there is a growing interest in applications for interactive gait training as they could allow for more self-paced and natural walking. This study investigated if walking in an overground VR environment has relevant effects on 3D gait biomechanics. A convenience sample of 21 healthy individuals underwent standard 3D gait analysis during four randomly assigned walking conditions: the real laboratory (RLab), a virtual laboratory resembling the real world (VRLab), a small version of the VRlab (VRLab−), and a version which is twice as long as the VRlab (VRLab+). To immerse the participants in the virtual environment we used a VR-HMD, which was operated wireless and calibrated in a way that the virtual labs would match the real-world. Walking speed and a single measure of gait kinematic variability (GaitSD) served as primary outcomes next to standard spatio-temporal parameters, their coefficients of variant (CV%), kinematics, and kinetics. Briefly described, participants demonstrated a slower walking pattern (−0.09 ± 0.06 m/s) and small accompanying kinematic and kinetic changes. Participants also showed a markedly increased gait variability in lower extremity gait kinematics and spatio-temporal parameters. No differences were found between walking in VRLab+ vs. VRLab−. Most of the kinematic and kinetic differences were too small to be regarded as relevant, but increased kinematic variability (+57%) along with increased percent double support time (+4%), and increased step width variability (+38%) indicate gait adaptions toward a more conservative or cautious gait due to instability induced by the VR environment. We suggest considering these effects in the design of VR-based overground training devices. Our study lays the foundation for upcoming developments in the field of VR-assisted gait rehabilitation as it describes how VR in overground walking scenarios impacts our gait pattern. This information is of high relevance when one wants to develop purposeful rehabilitation tools.

scholarly journals Augmented Reality–Based Rehabilitation of Gait Impairments: Case Report (Preprint)

2020 ◽  
Author(s):  
Jeremia Philipp Oskar Held ◽  
Kevin Yu ◽  
Connor Pyles ◽  
Janne Marieke Veerbeek ◽  
Felix Bork ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Motion Capture ◽  
Performance Feedback ◽  
Neurological Diseases ◽  
Gait Pattern ◽  
Motion Capture System ◽  
Overground Walking ◽  
Gait Adaptation ◽  
Gait Impairments

BACKGROUND Gait and balance impairments are common in neurological diseases, including stroke, and negatively affect patients’ quality of life. Improving balance and gait are among the main goals of rehabilitation. Rehabilitation is mainly performed in clinics, which lack context specificity; therefore, training in the patient’s home environment is preferable. In the last decade, developed rehabilitation technologies such as virtual reality and augmented reality (AR) have enabled gait and balance training outside clinics. Here, we propose a new method for gait rehabilitation in persons who have had a stroke in which mobile AR technology and a sensor-based motion capture system are combined to provide fine-grained feedback on gait performance in real time. OBJECTIVE The aims of this study were (1) to investigate manipulation of the gait pattern of persons who have had a stroke based on virtual augmentation during overground walking compared to walking without AR performance feedback and (2) to investigate the usability of the AR system. METHODS We developed the ARISE (Augmented Reality for gait Impairments after StrokE) system, in which we combined a development version of HoloLens 2 smart glasses (Microsoft Corporation) with a sensor-based motion capture system. One patient with chronic minor gait impairment poststroke completed clinical gait assessments and an AR parkour course with patient-centered performance gait feedback. The movement kinematics during gait as well as the usability and safety of the system were evaluated. RESULTS The patient changed his gait pattern during AR parkour compared to the pattern observed during the clinical gait assessments. He recognized the virtual objects and ranked the usability of the ARISE system as excellent. In addition, the patient stated that the system would complement his standard gait therapy. Except for the symptom of exhilaration, no adverse events occurred. CONCLUSIONS This project provided the first evidence of gait adaptation during overground walking based on real-time feedback through visual and auditory augmentation. The system has potential to provide gait and balance rehabilitation outside the clinic. This initial investigation of AR rehabilitation may aid the development and investigation of new gait and balance therapies.

scholarly journals Agreement between Inertia and Optical Based Motion Capture during the VU-Return-to-Play- Field-Test

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 831
Author(s):  
Chris Richter ◽  
Katherine A. J. Daniels ◽  
Enda King ◽  
Andrew Franklyn-Miller
Keyword(s):  
Motion Capture ◽  
Field Test ◽  
Sagittal Plane ◽  
Inertial Sensor ◽  
Frontal Plane ◽  
Return To Play ◽  
Motion Capture System ◽  
Ankle Kinematics ◽  
Accuracy And Precision ◽  
Hip Flexion

The validity of an inertial sensor-based motion capture system (IMC) has not been examined within the demands of a sports-specific field movement test. This study examined the validity of an IMC during a field test (VU®) by comparing it to an optical marker-based motion capture system (MMC). Expected accuracy and precision benchmarks were computed by comparing the outcomes of a linear and functional joint fitting model within the MMC. The kinematics from the IMC in sagittal plane demonstrated correlations (r2) between 0.76 and 0.98 with root mean square differences (RMSD) < 5°, only the knee bias was within the benchmark. In the frontal plane, r2 ranged between 0.13 and 0.80 with RMSD < 10°, while the knee and hip bias was within the benchmark. For the transversal plane, r2 ranged 0.11 to 0.93 with RMSD < 7°, while the ankle, knee and hip bias remained within the benchmark. The findings indicate that ankle kinematics are not interchangeable with MMC, that hip flexion and pelvis tilt higher in IMC than MMC, while other measures are comparable to MMC. Higher pelvis tilt/hip flexion in the IMC can be explained by a one sensor tilt estimation, while ankle kinematics demonstrated a considerable level of disagreement, which is likely due to four reasons: A one sensor estimation, sensor/marker attachment, movement artefacts of shoe sole and the ankle model used.

Tracking of Markers for 2D and 3D Gait Analysis Using Home Video Cameras

2013 ◽  
Vol 4 (3) ◽  
pp. 36-52 ◽  
Author(s):  
Sandro Mihradi ◽  
Ferryanto ◽  
Tatacipta Dirgantara ◽  
Andi I. Mahyuddin
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Motion Capture System ◽  
Distance Method ◽  
Home Video ◽  
Video Cameras ◽  
Optical Motion ◽  
Spatio Temporal ◽  
Optical Motion Capture ◽  
2D And 3D

This work presents the development of an affordable optical motion-capture system which uses home video cameras for 2D and 3D gait analysis. The 2D gait analyzer system consists of one camcorder and one PC while the 3D gait analyzer system uses two camcorders, a flash and two PCs. Both systems make use of 25 fps camcorder, LED markers and technical computing software to track motions of markers attached to human body during walking. In the experiment for 3D gait analyzer system, the two cameras are synchronized by using flash. The recorded videos for both systems are extracted into frames and then converted into binary images, and bridge morphological operation is applied for unconnected pixel to facilitate marker detection process. Least distance method is then employed to track the markers motions, and 3D Direct Linear Transformation is used to reconstruct 3D markers positions. The correlation between length in pixel and in the real world resulted from calibration process is used to reconstruct 2D markers positions. To evaluate the reliability of the 2D and 3D optical motion-capture system developed in the present work, spatio-temporal and kinematics parameters calculated from the obtained markers positions are qualitatively compared with the ones from literature, and the results show good compatibility.

scholarly journals Augmented Reality–Based Rehabilitation of Gait Impairments: Case Report

10.2196/17804 ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. e17804
Author(s):  
Jeremia Philipp Oskar Held ◽  
Kevin Yu ◽  
Connor Pyles ◽  
Janne Marieke Veerbeek ◽  
Felix Bork ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Motion Capture ◽  
Performance Feedback ◽  
Neurological Diseases ◽  
Gait Pattern ◽  
Motion Capture System ◽  
Overground Walking ◽  
Gait Adaptation ◽  
Gait Impairments

Background Gait and balance impairments are common in neurological diseases, including stroke, and negatively affect patients’ quality of life. Improving balance and gait are among the main goals of rehabilitation. Rehabilitation is mainly performed in clinics, which lack context specificity; therefore, training in the patient’s home environment is preferable. In the last decade, developed rehabilitation technologies such as virtual reality and augmented reality (AR) have enabled gait and balance training outside clinics. Here, we propose a new method for gait rehabilitation in persons who have had a stroke in which mobile AR technology and a sensor-based motion capture system are combined to provide fine-grained feedback on gait performance in real time. Objective The aims of this study were (1) to investigate manipulation of the gait pattern of persons who have had a stroke based on virtual augmentation during overground walking compared to walking without AR performance feedback and (2) to investigate the usability of the AR system. Methods We developed the ARISE (Augmented Reality for gait Impairments after StrokE) system, in which we combined a development version of HoloLens 2 smart glasses (Microsoft Corporation) with a sensor-based motion capture system. One patient with chronic minor gait impairment poststroke completed clinical gait assessments and an AR parkour course with patient-centered performance gait feedback. The movement kinematics during gait as well as the usability and safety of the system were evaluated. Results The patient changed his gait pattern during AR parkour compared to the pattern observed during the clinical gait assessments. He recognized the virtual objects and ranked the usability of the ARISE system as excellent. In addition, the patient stated that the system would complement his standard gait therapy. Except for the symptom of exhilaration, no adverse events occurred. Conclusions This project provided the first evidence of gait adaptation during overground walking based on real-time feedback through visual and auditory augmentation. The system has potential to provide gait and balance rehabilitation outside the clinic. This initial investigation of AR rehabilitation may aid the development and investigation of new gait and balance therapies.

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