Knee joint moment estimation using lower limb joint angle without using ground reaction force

2019 ◽  
Vol 2019 (0) ◽  
pp. 458
Author(s):  
Ami OGAWA ◽  
Akira MITA ◽  
Koichi SATO ◽  
Takayuki ISHII
2012 ◽  
Vol 59 (5) ◽  
pp. 1480-1487 ◽  
Author(s):  
Suncheol Kwon ◽  
Hyung-Soon Park ◽  
C. J. Stanley ◽  
Jung Kim ◽  
Jonghyun Kim ◽  
...  

2019 ◽  
Vol 126 (5) ◽  
pp. 1315-1325 ◽  
Author(s):  
Andrew B. Udofa ◽  
Kenneth P. Clark ◽  
Laurence J. Ryan ◽  
Peter G. Weyand

Although running shoes alter foot-ground reaction forces, particularly during impact, how they do so is incompletely understood. Here, we hypothesized that footwear effects on running ground reaction force-time patterns can be accurately predicted from the motion of two components of the body’s mass (mb): the contacting lower-limb (m1 = 0.08mb) and the remainder (m2 = 0.92mb). Simultaneous motion and vertical ground reaction force-time data were acquired at 1,000 Hz from eight uninstructed subjects running on a force-instrumented treadmill at 4.0 and 7.0 m/s under four footwear conditions: barefoot, minimal sole, thin sole, and thick sole. Vertical ground reaction force-time patterns were generated from the two-mass model using body mass and footfall-specific measures of contact time, aerial time, and lower-limb impact deceleration. Model force-time patterns generated using the empirical inputs acquired for each footfall matched the measured patterns closely across the four footwear conditions at both protocol speeds ( r2 = 0.96 ± 0.004; root mean squared error  = 0.17 ± 0.01 body-weight units; n = 275 total footfalls). Foot landing angles (θF) were inversely related to footwear thickness; more positive or plantar-flexed landing angles coincided with longer-impact durations and force-time patterns lacking distinct rising-edge force peaks. Our results support three conclusions: 1) running ground reaction force-time patterns across footwear conditions can be accurately predicted using our two-mass, two-impulse model, 2) impact forces, regardless of foot strike mechanics, can be accurately quantified from lower-limb motion and a fixed anatomical mass (0.08mb), and 3) runners maintain similar loading rates (ΔFvertical/Δtime) across footwear conditions by altering foot strike angle to regulate the duration of impact. NEW & NOTEWORTHY Here, we validate a two-mass, two-impulse model of running vertical ground reaction forces across four footwear thickness conditions (barefoot, minimal, thin, thick). Our model allows the impact portion of the impulse to be extracted from measured total ground reaction force-time patterns using motion data from the ankle. The gait adjustments observed across footwear conditions revealed that runners maintained similar loading rates across footwear conditions by altering foot strike angles to regulate the duration of impact.


Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6533
Author(s):  
Xinxin Li ◽  
Zuojun Liu ◽  
Xinzhi Gao ◽  
Jie Zhang

A novel method for recognizing the phases in bicycling of lower limb amputees using support vector machine (SVM) optimized by particle swarm optimization (PSO) is proposed in this paper. The method is essential for enhanced prosthetic knee joint control for lower limb amputees in carrying out bicycling activity. Some wireless wearable accelerometers and a knee joint angle sensor are installed in the prosthesis to obtain data on the knee joint and ankle joint horizontal, vertical acceleration signal and knee joint angle. In order to overcome the problem of high noise content in the collected data, a soft-hard threshold filter was used to remove the noise caused by the vibration. The filtered information is then used to extract the multi-dimensional feature vector for the training of SVM for performing bicycling phase recognition. The SVM is optimized by PSO to enhance its classification accuracy. The recognition accuracy of the PSO-SVM classification model on testing data is 93%, which is much higher than those of BP, SVM and PSO-BP classification models.


2016 ◽  
Vol 23 (4) ◽  
Author(s):  
Isabel Forner-Cordero ◽  
Fabianne Furtado ◽  
Juan Cervera-Deval ◽  
Arturo Forner-Cordero

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yi Wang ◽  
Wing-Kai Lam ◽  
Lok-Yee Pak ◽  
Charis K.-W. Wong ◽  
Mohammad F. Tan ◽  
...  

While colour of red can play a significant role in altering human perception and performances, little is known about its perceptual-motor effect on running mechanics. This study examined the effects of variations in insole colours on impact forces, ankle kinematics, and trial-to-trial reliability at various running speeds. Sixteen male recreational runners ran on instrumented treadmill at slow (90%), preferred (100%), and fast (110%) running speeds when wearing insoles in red, blue, and white colours. We used synchronized force platform and motion capturing system to measure ground reaction force, ankle sagittal and frontal kinematics, and movement variability. A two-way (colour x speed) ANOVA with repeated measures was performed with Bonferroni adjusted post hoc comparisons, with alpha set at 0.05. Data analyses indicated that participants demonstrated higher impact and maximum loading rate of ground reaction force, longer stride length, shorter contact time, and smaller touchdown ankle inversion as well as larger ankle sagittal range of motion (RoM), but smaller frontal RoM in fast speed as compared with preferred P < 0.05 and slow speeds P < 0.001 . Although insole colour had minimal effect on mean values of any tested variables P > 0.05 , participants wearing red-coloured orthoses showed higher coefficient of variation values for maximum loading rate than wearing blue insoles P = 0.009 . These results suggest that running at faster speed would lead to higher impact loading and altered lower-limb mechanics and that colour used on the tops of insoles influences the wearers’ movement repeatability, with implications for use of foot insole in running.


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