Literature DB >> 12485787

Automatic vs hand-controlled walking of paraplegics.

Dejan Popović1, Milovan Radulović, Laszlo Schwirtlich, Novak Jauković.   

Abstract

A rule-based control and its application in functional electrical stimulation (FES) assisted walking of subjects with paraplegia are described in this paper. The design of rules for control comprises the following two steps: (1) determination of muscle activation patterns by using a fully customized spatial (3D) model of paraplegic walking, and (2) learning of rules, that is, correlation between the muscle activation patterns and kinematics of walking by means of an artificial neural network. The adopted FES system activated eight muscle groups with surface electrodes. The only joints allowing movement in the coronal plane were the hips, and externally controlled joints in sagittal plane were ankles, knees and hips. The simulation minimized the tracking error of the joint angles and the total activation of all eight muscles being stimulated. A radial-basis function artificial neural network was applied for learning of rules. Three automatically controlled modes (slow, near-normal, and near-ballistic) and hand-controlled walking were evaluated in six subjects with a complete spinal cord lesion (T8-T10). The performance of walking was assessed by the following: (1) energy consumption based on oxygen uptake, (2) physiological cost index, (3) maximum speed of walking, and (4) a questionnaire. The results showed that all modes of walking are achievable and that automatic control leads to more efficient and faster walking. The speed of walking achieved by automatic control was almost three times bigger compared with the speed of hand-controlled walking. The energy cost and rate decreased significantly when automatic control was applied; yet, they were still much bigger than the values measured in able-bodied subjects. The objective outcome measures suggest that the near-ballistic walking was the most effective, yet a questionnaire shows that most subjects preferred slow walking. The most likely reason for the preference of lower efficiency walking over the faster end energy efficient near-ballistic walking was that paraplegic patients had difficulties in synchronizing the voluntary movement of the trunk and arms to the artificially controlled movements of legs.

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Year:  2003        PMID: 12485787     DOI: 10.1016/s1350-4533(02)00188-1

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  8 in total

Review 1.  Restoring standing capabilities with feedback control of functional neuromuscular stimulation following spinal cord injury.

Authors:  Raviraj Nataraj; Musa L Audu; Ronald J Triolo
Journal:  Med Eng Phys       Date:  2017-02-15       Impact factor: 2.242

2.  A biomechanical model to estimate corrective changes in muscle activation patterns for stroke patients.

Authors:  Qi Shao; Thomas S Buchanan
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3.  From neuromuscular activation to end-point locomotion: An artificial neural network-based technique for neural prostheses.

Authors:  Chia-Lin Chang; Zhanpeng Jin; Hou-Cheng Chang; Allen C Cheng
Journal:  J Biomech       Date:  2009-04-22       Impact factor: 2.712

4.  Intraspinal microstimulation produces over-ground walking in anesthetized cats.

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Journal:  J Neural Eng       Date:  2016-09-13       Impact factor: 5.379

5.  Online assessment of human-robot interaction for hybrid control of walking.

Authors:  Antonio J del-Ama; Juan C Moreno; Angel Gil-Agudo; Ana de-los-Reyes; José L Pons
Journal:  Sensors (Basel)       Date:  2011-12-27       Impact factor: 3.576

6.  Reflex control of robotic gait using human walking data.

Authors:  Catherine A Macleod; Lin Meng; Bernard A Conway; Bernd Porr
Journal:  PLoS One       Date:  2014-10-27       Impact factor: 3.240

7.  Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton.

Authors:  Antonio J del-Ama; Angel Gil-Agudo; José L Pons; Juan C Moreno
Journal:  J Neuroeng Rehabil       Date:  2014-03-04       Impact factor: 4.262

Review 8.  A Muscle Synergy-Inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis.

Authors:  Naji A Alibeji; Nicholas Andrew Kirsch; Nitin Sharma
Journal:  Front Bioeng Biotechnol       Date:  2015-12-21
  8 in total

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