Muscle Contracture Modeling and Optimal Control for Crouch Gait Prediction

Author(s):  
Matilde Tomasi ◽  
Alessio Artoni

Abstract Prediction of human movement, and especially of pathological gait, is nowadays an important and mostly unsolved research challenge. In this work, a recently developed computational framework based on optimal control was adopted and explored to assess its potential for predicting a pathological gait pattern, in particular the crouch gait typical of subjects affected by cerebral palsy. To this end, the generic musculoskeletal model on which this optimal control framework is based was made representative of such pathological case by modeling contracture of relevant muscle groups commonly associated with crouch gait, namely knee and hip flexors. All the conducted simulations succeeded in inducing the model into a crouch gait pattern, despite their diversity in cost functions. Moreover, the obtained joint angle trajectories correlated well with the experimental ones obtained from a CP child walking in crouch. These kinematic results suggest that optimal control techniques and proper tuning of musculotendon parameters are an important pairing for predictive simulations of human walking. On the other hand, the obtained results confirm that estimation of muscle activations is strongly dependent on the selected objective function and still requires deeper investigations.

2013 ◽  
Vol 29 (2) ◽  
pp. 127-134 ◽  
Author(s):  
Smita Rao ◽  
Fred Dietz ◽  
H. John Yack

The purpose of this study was to compare estimates of gastrocnemius muscle length (GML) obtained using a segmented versus straight-line model in children. Kinematic data were acquired on eleven typically developing children as they walked under the following conditions: normal gait, crouch gait, equinus gait, and crouch with equinus gait. Maximum and minimum GML, and GML change were calculated using two models: straight-line and segmented. A two-way RMANOVA was used to compare GML characteristics. Results indicated that maximum GML and GML change during simulated pathological gait patterns were influenced by model used to calculate gastrocnemius muscle length (interaction: P = .004 and P = .026). Maximum GML was lower in the simulated gait patterns compared with normal gait (P < .001). Maximum GML was higher with the segmented model compared with the straight-line model (P = .030). Using either model, GML change in equinus gait and crouch with equinus gait was lower compared with normal gait (P < .001). Overall, minimum GML estimated with the segmented model was higher compared with the straight-line model (P < .01). The key findings of our study indicate that GML is significantly affected by both gait pattern and method of estimation. The GML estimates tended to be lower with the straight-line model versus the segmented model.


Author(s):  
Mohamed M. Alhneaish ◽  
Mohamed L. Shaltout ◽  
Sayed M. Metwalli

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.


Author(s):  
Saugat Bhattacharyya ◽  
Maureen Clerc ◽  
Mitsuhiro Hayashibe

Functional Electrical Stimulation (FES) provides a neuroprosthetic interface to non-recovered muscle groups by stimulating the affected region of the human body. FES in combination with Brain-machine interfacing (BMI) has a wide scope in rehabilitation because this system directly links the cerebral motor intention of the users with its corresponding peripheral muscle activations. In this paper, we examine the effect of FES on the electroencephalography (EEG) during motor imagery (left- and right-hand movement) training of the users. Results suggest a significant improvement in the classification accuracy when the subject was induced with FES stimuli as compared to the standard visual one.


2020 ◽  
Vol 15 (3) ◽  
pp. 3-14
Author(s):  
Péter Müller ◽  
Ádám Schiffer

Examining a human movement can provide a wealth of information about a patient’s medical condition. The examination process can be used to diagnose abnormal changes (lesions), ability development and monitor the rehabilitation process of people with reduced mobility. There are several approaches to monitor people, among other things with sensors and various imaging and processing devices. In this case a Kinect V2 sensor and a self-developed LabView based application was used, to examine the movement of the lower limbs. The ideal gait pattern was recorded in the RoboGait training machine and the measured data was used to identify the phases of the human gait. During the evaluation, the position of the skeleton model, the associated body joints and angles can be calculated. The pre-recorded ideal and natural gait cycle can be compared.With the self-developed method the pre-recorded ideal and natural gait cycle can be compared and processed for further evaluation. The evaluated measurement data confirm that a reliable and mobile solution for gait analysis has been created.


2015 ◽  
Vol 42 ◽  
pp. S35
Author(s):  
A. Pouliot-Laforte ◽  
A. Parent ◽  
P. Marois ◽  
R. Hamdy ◽  
M. Lemay ◽  
...  

Author(s):  
Anup Nandy ◽  
Saikat Chakraborty ◽  
Jayeeta Chakraborty ◽  
Gentiane Venture

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