Literature DB >> 1514893

Computer algorithms to characterize individual subject EMG profiles during gait.

R A Bogey1, L A Barnes, J Perry.   

Abstract

Three methods of precisely determining onset and cessation times of gait EMG were investigated. Subjects were 24 normal adults and 32 individuals with gait pathologies. Soleus muscle EMG during free speed level walking was obtained with fine wires, and was normalized by manual muscle test (%MMT). Linear envelopes were generated from the rectified, integrated EMG at each percent gait cycle (%GC) of each stride in individual gait trials. Three methods were used to generate EMG profiles for each tested subject. The ensemble average (EAV) was determined for each subject from the mean relative intensity of the linear envelopes. Low relative intensity or short duration EMG was removed from the ensemble average to create the intensity filtered average (IFA). The packet analysis method (PAC) created an EMG profile from the linear envelopes in successive strides whose respective centroid %GC locations were within +/- 15%GC of each other. Control values for onset and cessation times of individual gait trials were calculated after spurious outliers were removed. Mean onset and cessation times across subjects for control values and the experimental methods (EAV, IFA, and PAC) were calculated. Dunnett's test (p less than .05) was performed to compare control and experimental groups in patient and normal trials. EAV differed from control values for onsets (p less than .01), cessations (p less than .01), and durations (p less than .01) in both normal and patient trials. IFA and PAC had no significant differences from control value means. IFA was selected for clinical use as automatic analysis could be performed on all trials and a minimum number of decision rules were needed.

Entities:  

Mesh:

Year:  1992        PMID: 1514893

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  11 in total

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2.  Neuromuscular activation patterns during treadmill walking after space flight.

Authors:  C S Layne; P V McDonald; J J Bloomberg
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3.  Abnormal leg muscle latencies and relationship to dyscoordination and walking disability after stroke.

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Journal:  Rehabil Res Pract       Date:  2010-12-29

4.  Robust muscle activity onset detection using an unsupervised electromyogram learning framework.

Authors:  Jie Liu; Dongwen Ying; William Z Rymer; Ping Zhou
Journal:  PLoS One       Date:  2015-06-03       Impact factor: 3.240

5.  Wearable Monitoring Devices for Biomechanical Risk Assessment at Work: Current Status and Future Challenges-A Systematic Review.

Authors:  Ranavolo Alberto; Francesco Draicchio; Tiwana Varrecchia; Alessio Silvetti; Sergio Iavicoli
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6.  Recovery of post stroke proximal arm function, driven by complex neuroplastic bilateral brain activation patterns and predicted by baseline motor dysfunction severity.

Authors:  Svetlana Pundik; Jessica P McCabe; Ken Hrovat; Alice Erica Fredrickson; Curtis Tatsuoka; I Jung Feng; Janis J Daly
Journal:  Front Hum Neurosci       Date:  2015-07-22       Impact factor: 3.169

7.  A pilot study on the feasibility of robot-aided leg motor training to facilitate active participation.

Authors:  Chandramouli Krishnan; Rajiv Ranganathan; Yasin Y Dhaher; William Z Rymer
Journal:  PLoS One       Date:  2013-10-11       Impact factor: 3.240

8.  Biomechanical comparison of menisci from different species and artificial constructs.

Authors:  Gunther H Sandmann; Christopher Adamczyk; Eduardo Grande Garcia; Stefan Doebele; Andreas Buettner; Stefan Milz; Andreas B Imhoff; Stefan Vogt; Rainer Burgkart; Thomas Tischer
Journal:  BMC Musculoskelet Disord       Date:  2013-11-17       Impact factor: 2.362

9.  Estimates of individual muscle power production in normal adult walking.

Authors:  Ross A Bogey; Lee A Barnes
Journal:  J Neuroeng Rehabil       Date:  2017-09-11       Impact factor: 4.262

10.  Spasticity assessment based on the Hilbert-Huang transform marginal spectrum entropy and the root mean square of surface electromyography signals: a preliminary study.

Authors:  Baohua Hu; Xiufeng Zhang; Jingsong Mu; Ming Wu; Yong Wang
Journal:  Biomed Eng Online       Date:  2018-02-27       Impact factor: 2.819

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