Timing-Specific Transfer of Adapted Muscle Activity After Walking in an Elastic Force Field

2009 ◽  
Vol 102 (1) ◽  
pp. 568-577 ◽  
Author(s):  
Andreanne Blanchette ◽  
Laurent J. Bouyer
Keyword(s):  
Force Field ◽  
Lower Limb ◽  
Neural Control ◽  
Gait Cycle ◽  
Human Locomotion ◽  
Emg Activity ◽  
Field Exposure ◽  
Limb Kinematics ◽  
Increased Activity ◽  
Lower Limb Kinematics

Human locomotion results from interactions between feedforward (central commands from voluntary and automatic drive) and feedback (peripheral commands from sensory inputs) mechanisms. Recent studies have shown that locomotion can be adapted when an external force is applied to the lower limb. To better understand the neural control of this adaptation, the present study investigated gait modifications resulting from exposure to a position-dependent force field. Ten subjects walked on a treadmill before, during, and after exposure to a force field generated by elastic tubing that pulled the foot forward and up during swing. Lower limb kinematics and electromyographic (EMG) activity were recorded during each walking period. During force field exposure, peak foot velocity was initially increased by 38%. As subjects adapted, peak foot velocity gradually returned to baseline in ≤125 strides. In the adapted state, hamstring EMG activity started earlier (16% before toe off) and remained elevated throughout swing. After force field exposure, foot velocity was initially reduced by 22% and returned to baseline in 9–51 strides. Aftereffects in hamstring EMGs consisted of increased activity around toe off. Contrary to the adapted state, this increase was not maintained during the rest of swing. Together, these results suggest that while the neural control of human locomotion can adapt to force field exposure, the mechanisms underlying this adaptation may vary according to the timing in the gait cycle. Adapted hamstring EMG activity may rely more on feedforward mechanisms around toe off and more on feedback mechanisms during the rest of swing.

scholarly journals Lower-limb kinematics and kinetics during continuously varying human locomotion

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Emma Reznick ◽  
Kyle R. Embry ◽  
Ross Neuman ◽  
Edgar Bolívar-Nieto ◽  
Nicholas P. Fey ◽  
...  
Keyword(s):  
Lower Limb ◽  
Human Locomotion ◽  
Lower Limbs ◽  
Stair Climbing ◽  
Constant Acceleration ◽  
Stair Ascent ◽  
Limb Kinematics ◽  
Kinetics Of ◽  
Lower Limb Kinematics ◽  
Kinematics And Kinetics

AbstractHuman locomotion involves continuously variable activities including walking, running, and stair climbing over a range of speeds and inclinations as well as sit-stand, walk-run, and walk-stairs transitions. Understanding the kinematics and kinetics of the lower limbs during continuously varying locomotion is fundamental to developing robotic prostheses and exoskeletons that assist in community ambulation. However, available datasets on human locomotion neglect transitions between activities and/or continuous variations in speed and inclination during these activities. This data paper reports a new dataset that includes the lower-limb kinematics and kinetics of ten able-bodied participants walking at multiple inclines (±0°; 5° and 10°) and speeds (0.8 m/s; 1 m/s; 1.2 m/s), running at multiple speeds (1.8 m/s; 2 m/s; 2.2 m/s and 2.4 m/s), walking and running with constant acceleration (±0.2; 0.5), and stair ascent/descent with multiple stair inclines (20°; 25°; 30° and 35°). This dataset also includes sit-stand transitions, walk-run transitions, and walk-stairs transitions. Data were recorded by a Vicon motion capture system and, for applicable tasks, a Bertec instrumented treadmill.

scholarly journals Stable Coordination Variability in Overground Walking and Running at Preferred and Fixed Speeds

2021 ◽  
pp. 1-5
Author(s):  
Hannah E. Wyatt ◽  
Gillian Weir ◽  
Carl Jewell ◽  
Richard E.A. van Emmerik ◽  
Joseph Hamill
Keyword(s):  
Lower Limb ◽  
Stance Phase ◽  
Three Dimensional ◽  
Human Locomotion ◽  
Overground Walking ◽  
Vector Coding ◽  
Limb Kinematics ◽  
Recreational Runners ◽  
Lower Limb Kinematics ◽  
Insufficient Number

Coordination variability (CV) is commonly analyzed to understand dynamical qualities of human locomotion. The purpose of this study was to develop guidelines for the number of trials required to inform the calculation of a stable mean lower limb CV during overground locomotion. Three-dimensional lower limb kinematics were captured for 10 recreational runners performing 20 trials each of preferred and fixed speed walking and running. Stance phase CV was calculated for 9 segment and joint couplings using a modified vector coding technique. The number of trials required to achieve a CV mean within 10% of 20 strides average was determined for each coupling and individual. The statistical outputs of mode (walking vs running) and speed (preferred vs fixed) were compared when informed by differing numbers of trials. A minimum of 11 trials were required for stable mean stance phase CV. With fewer than 11 trials, CV was underestimated and led to an oversight of significant differences between mode and speed. Future overground locomotion CV research in healthy populations using a vector coding approach should use 11 trials as a standard minimum. Researchers should be aware of the notable consequences of an insufficient number of trials for overall study findings.

Analysis of the Relationships between Balance Ability and Walking in Terms of Muscle Activities and Lower Limb Kinematics and Kinetics

Biomechanics ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 190-201
Author(s):  
Pathmanathan Cinthuja ◽  
Graham Arnold ◽  
Rami J. Abboud ◽  
Weijie Wang
Keyword(s):  
Regression Analysis ◽  
Lower Limb ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression Analysis ◽  
Vastus Medialis ◽  
Balance Test ◽  
Balance Ability ◽  
Limb Kinematics ◽  
Lower Limb Kinematics ◽  
Kinematics And Kinetics

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.

Rate of loading, but not lower limb kinematics or muscle activity, is moderated by limb and aerial variation when surfers land aerials

2021 ◽  
pp. 1-9
Author(s):  
James R. Forsyth ◽  
Christopher J. Richards ◽  
Ming-Chang Tsai ◽  
John W. Whitting ◽  
Diane L. Riddiford-Harland ◽  
...  
Keyword(s):  
Lower Limb ◽  
Muscle Activity ◽  
Limb Kinematics ◽  
Lower Limb Kinematics ◽  
Rate Of Loading

Changes in drive phase lower limb kinematics during a 60min cycling time trial

2012 ◽  
Vol 15 (2) ◽  
pp. 169-174 ◽  
Author(s):  
Mark G.L. Sayers ◽  
Amanda L. Tweddle ◽  
Joshua Every ◽  
Aaron Wiegand
Keyword(s):  
Lower Limb ◽  
Time Trial ◽  
Cycling Time Trial ◽  
Limb Kinematics ◽  
Lower Limb Kinematics ◽  
Cycling Time

scholarly journals Effects of gait retraining with focus on impact versus gait retraining with focus on cadence on pain, function and lower limb kinematics in runners with patellofemoral pain: Protocol of a randomized, blinded, parallel group trial with 6-month follow-up

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 ◽  
...  
Keyword(s):  
Lower Limb ◽  
Intervention Group ◽  
Patellofemoral Pain ◽  
Control Group ◽  
Gait Retraining ◽  
Positive Effects ◽  
Clinical Applicability ◽  
Limb Kinematics ◽  
Lower Limb Kinematics

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.

scholarly journals Estimating Lower Limb Kinematics Using a Lie Group Constrained Extended Kalman Filter with a Reduced Wearable IMU Count and Distance Measurements

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6829
Author(s):  
Luke Wicent F. Sy ◽  
Nigel H. Lovell ◽  
Stephen J. Redmond
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Lie Group ◽  
Lower Limb ◽  
Sagittal Plane ◽  
Ultra Wideband ◽  
Distance Measurements ◽  
Limb Kinematics ◽  
Mean Square Errors ◽  
Lower Limb Kinematics

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.

scholarly journals Time-Frequency Linearization of Reactive Cortical Responses for the Early Detection of Balance Losses

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Giovanni Mezzina ◽  
Daniela De Venuto
Keyword(s):  
Lower Limb ◽  
Fall Detection ◽  
Time Frequency ◽  
Average Value ◽  
Cortical Responses ◽  
Loss Of Balance ◽  
Spectrum Density ◽  
System Functioning ◽  
Limb Kinematics ◽  
Lower Limb Kinematics

Aiming at finding a fast and accurate preimpact fall detection (PIFD) strategy, this paper proposes a novel methodology that precociously discriminates the occurrence of unexpected loss of balance from the steady walking, by analyzing the subject’s cortical signal modifications (at the scalp level) in the time-frequency domain. In this study, the subjects were asked to walk at their preferred speed on the treadmill platform programmed to provide unexpected bilateral slippages. The proposed PIFD method exploits synchronously recorded electromyographic (EMG: 2 channels from the same lower limb muscle bundle, bilaterally) and electro-encephalographic (EEG: 13 channels from motor, sensory-motor and parietal cortex areas) signals. To validate the method offline, also, the lower limb kinematics has been reconstructed via a motion capture system (23 reflective markers and 8 fixed cameras). During the PIFD system functioning, the EMG signals from the lateral gastrocnemii are first translated in a binary waveform and then used to trigger the EEG analysis. Once enabled via EMG (every gait cycle), the EEG computation branch extracts and linearizes the rate of variation in the EEG power spectrum density (PSD) for five bands of interests: θ (4–7 Hz), α (8–12 Hz), β I, β II, β III rhythms (13–15 Hz, 16–20 Hz, and 21–28 Hz). The slope of the linearized trend identifies, in this context, the cortical responsiveness parameter. Experimental results from six subjects revealed that the proposed system can distinguish the loss of balance with an overall accuracy of ~96% (average value between sensitivity and specificity). The discrimination process requests, on average, 370.6 ms. This value could be considered suitable for the implementation of countermeasures aimed at restoring the balance of the subject.

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