scholarly journals Estimating Lower Limb Kinematics using Distance Measurements with a Reduced Wearable Inertial Sensor Count

Author(s):  
Luke Sy ◽  
Nigel H. Lovell ◽  
Stephen J. Redmond
Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6829
Author(s):  
Luke Wicent F. Sy ◽  
Nigel H. Lovell ◽  
Stephen J. Redmond

Tracking the kinematics of human movement usually requires the use of equipment that constrains the user within a room (e.g., optical motion capture systems), or requires the use of a conspicuous body-worn measurement system (e.g., inertial measurement units (IMUs) attached to each body segment). This paper presents a novel Lie group constrained extended Kalman filter to estimate lower limb kinematics using IMU and inter-IMU distance measurements in a reduced sensor count configuration. The algorithm iterates through the prediction (kinematic equations), measurement (pelvis height assumption/inter-IMU distance measurements, zero velocity update for feet/ankles, flat-floor assumption for feet/ankles, and covariance limiter), and constraint update (formulation of hinged knee joints and ball-and-socket hip joints). The knee and hip joint angle root-mean-square errors in the sagittal plane for straight walking were 7.6±2.6∘ and 6.6±2.7∘, respectively, while the correlation coefficients were 0.95±0.03 and 0.87±0.16, respectively. Furthermore, experiments using simulated inter-IMU distance measurements show that performance improved substantially for dynamic movements, even at large noise levels (σ=0.2 m). However, further validation is recommended with actual distance measurement sensors, such as ultra-wideband ranging sensors.


2017 ◽  
Vol 57 ◽  
pp. 236-240 ◽  
Author(s):  
Kenji Tanimoto ◽  
Makoto Takahashi ◽  
Kazuki Tokuda ◽  
Tomonori Sawada ◽  
Masaya Anan ◽  
...  

Author(s):  
Luke Wicent F. Sy ◽  
Nigel H. Lovell ◽  
Stephen J. Redmond

Tracking the kinematics of human movement usually requires the use of equipment that constrains the user within a room (e.g., optical motion capture systems), or requires the use of a conspicuous body-worn measurement system (e.g., inertial measurement units (IMUs) attached to each body segment). This paper presents a novel Lie group constrained extended Kalman filter to estimate lower limb kinematics using IMU and inter-IMU distance measurements in a reduced sensor count configuration. The algorithm iterates through the prediction (kinematic equations), measurement (pelvis height assumption/inter-IMU distance measurements, zero velocity update for feet/ankles, flat-floor assumption for feet/ankles, and covariance limiter), and constraint update (formulation of hinged knee joints and ball-and-socket hip joints). The knee and hip joint angle root-mean-square errors in the sagittal plane for straight walking were 7.6±2.6∘ and 6.6±2.7∘, respectively, while the correlation coefficients were 0.95±0.03 and 0.87±0.16, respectively. Furthermore, experiments using simulated inter-IMU distance measurements show that performance improved substantially for dynamic movements, even at large noise levels (σ=0.2 m). However, further validation is recommended with actual distance measurement sensors, such as ultra-wideband ranging sensors.


Biomechanics ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 190-201
Author(s):  
Pathmanathan Cinthuja ◽  
Graham Arnold ◽  
Rami J. Abboud ◽  
Weijie Wang

There is a lack of evidence about the ways in which balance ability influences the kinematic and kinetic parameters and muscle activities during gait among healthy individuals. The hypothesis is that balance ability would be associated with the lower limb kinematics, kinetics and muscle activities during gait. Twenty-nine healthy volunteers (Age 32.8 ± 9.1; 18 males and 11 females) performed a Star Excursion Balance test to measure their dynamic balance and walked for at least three trials in order to obtain a good quality of data. A Vicon® 3D motion capture system and AMTI® force plates were used for the collection of the movement data. The selected muscle activities were recorded using Delsys® Electromyography (EMG). The EMG activities were compared using the maximum values and root mean squared (RMS) values within the participants. The joint angle, moment, force and power were calculated using a Vicon Plug-in-Gait model. Descriptive analysis, correlation analysis and multivariate linear regression analysis were performed using SPSS version 23. In the muscle activities, positive linear correlations were found between the walking and balance test in all muscles, e.g., in the multifidus (RMS) (r = 0.800 p < 0.0001), vastus lateralis (RMS) (r = 0.639, p < 0.0001) and tibialis anterior (RMS) (r = 0.539, p < 0.0001). The regression analysis models showed that there was a strong association between balance ability (i.e., reaching distance) and the lower limb muscle activities (i.e., vastus medialis–RMS) (R = 0.885, p < 0.0001), and also between balance ability (i.e., reaching distance) and the lower limb kinematics and kinetics during gait (R = 0.906, p < 0.0001). In conclusion, the results showed that vastus medialis (RMS) muscle activity mainly contributes to balance ability, and that balance ability influences the lower limb kinetics and kinematics during gait.


2021 ◽  
pp. 1-9
Author(s):  
James R. Forsyth ◽  
Christopher J. Richards ◽  
Ming-Chang Tsai ◽  
John W. Whitting ◽  
Diane L. Riddiford-Harland ◽  
...  

2012 ◽  
Vol 15 (2) ◽  
pp. 169-174 ◽  
Author(s):  
Mark G.L. Sayers ◽  
Amanda L. Tweddle ◽  
Joshua Every ◽  
Aaron Wiegand

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250965
Author(s):  
José Roberto de Souza Júnior ◽  
Pedro Henrique Reis Rabelo ◽  
Thiago Vilela Lemos ◽  
Jean-Francois Esculier ◽  
João Pedro da Silva Carto ◽  
...  

Patellofemoral pain (PFP) is one of the most prevalent injuries in runners. Unfortunately, a substantial part of injured athletes do not recover fully from PFP in the long-term. Although previous studies have shown positive effects of gait retraining in this condition, retraining protocols often lack clinical applicability because they are time-consuming, costly for patients and require a treadmill. The primary objective of this study will be to compare the effects of two different two-week partially supervised gait retraining programs, with a control intervention; on pain, function and lower limb kinematics of runners with PFP. It will be a single-blind randomized clinical trial with six-month follow-up. The study will be composed of three groups: a group focusing on impact (group A), a group focusing on cadence (group B), and a control group that will not perform any intervention (group C). The primary outcome measure will be pain assessed using the Visual Analog Pain scale during running. Secondary outcomes will include pain during daily activities (usual), symptoms assessed using the Patellofemoral Disorders Scale and lower limb running kinematics in the frontal (contralateral pelvic drop; hip adduction) and sagittal planes (foot inclination; tibia inclination; ankle dorsiflexion; knee flexion) assessed using the MyoResearch 3.14—MyoVideo (Noraxon U.S.A. Inc.). The study outcomes will be evaluated before (t0), immediately after (t2), and six months (t24) after starting the protocol. Our hypothesis is that both partially supervised gait retraining programs will be more effective in reducing pain, improving symptoms, and modifying lower limb kinematics during running compared with the control group, and that the positive effects from these programs will persist for six months. Also, we believe that one gait retraining group will not be superior to the other. Results from this study will help improve care in runners with PFP, while maximizing clinical applicability as well as time and cost-effectiveness.


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