Recognition of Lower Limb Muscle EMG Patterns by using Neural Networks during the Postural Balance Control

We recognized EMG signal patterns of lower limb muscles by using neural networks and performed feature evaluation during the recovery of postural balance of human body. Surface electrodes were attached to lower limb and EMG signals were collected during the balance recovery process from a perturbation without permitting compensatory stepping. A waist pulling system was used to apply transient perturbations in five horizontal directions. The EMG signals of fifty repetitions of five motions were analyzed for ten subjects. Twenty features were extracted from EMG signals of one event. Feature evaluation was also performed by using DB (Davies-Bouldin) index. By using neural networks, EMG signals were classified into five categories, such as forward perturbation, backward perturbation, lateral perturbation and two oblique perturbations. As results, motions were recognized with mean success rates of 75 percent. With the neural networks classifier of this study, the EMG patterns of lower limb muscles during the recovery of postural balance can be classified with high accuracy of recognition.

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Use of Musculoskeletal Modeling to Examine Lower Limb Muscle Contribution to Gait Balance Control: Effects of Overweight

10.1109/icdh52753.2021.00056 ◽

2021 ◽

Author(s):

Hyun Kyung Kim ◽

Li-Shan Chou

Keyword(s):

Lower Limb ◽

Balance Control ◽

Musculoskeletal Modeling ◽

Lower Limb Muscle ◽

Limb Muscle

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Augmented reality-assisted training with selected Tai-Chi movements improves balance control and increases lower limb muscle strength in older adults: A prospective randomized trial

Journal of Exercise Science & Fitness ◽

10.1016/j.jesf.2020.05.003 ◽

2020 ◽

Vol 18 (3) ◽

pp. 142-147

Author(s):

Po-Jung Chen ◽

I-Wen Penn ◽

Shun-Hwa Wei ◽

Long-Ren Chuang ◽

Wen-Hsu Sung

Keyword(s):

Older Adults ◽

Muscle Strength ◽

Augmented Reality ◽

Randomized Trial ◽

Lower Limb ◽

Tai Chi ◽

Balance Control ◽

Prospective Randomized Trial ◽

Lower Limb Muscle ◽

Limb Muscle

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Lower limb muscle fatigability is not associated with changes in movement strategies for balance control in the upright stance

Human Movement Science ◽

10.1016/j.humov.2020.102588 ◽

2020 ◽

Vol 70 ◽

pp. 102588

Author(s):

Patricia Sant'Anna do Carmo Aprigio ◽

Igor Ramathur Telles de Jesus ◽

Carla Porto ◽

Thiago Lemos ◽

Arthur de Sá Ferreira

Keyword(s):

Lower Limb ◽

Balance Control ◽

Lower Limb Muscle ◽

Limb Muscle ◽

Upright Stance ◽

Movement Strategies

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Correlation between static postural balance, falls and pick torque isokinetic of extensors and flexors of the knee in elderly

Manual Therapy Posturology & Rehabilitation Journal ◽

10.17784/mtprehabjournal.2017.15.469 ◽

2020 ◽

pp. 1-6

Author(s):

Marieli Ramos Stocco ◽

Deise Aparecida de Almeida Pires-Oliveira ◽

Laís Campus de Oliveira ◽

Raphael Gonçalves de Oliveira ◽

Fábio Antônio Néia Martini ◽

...

Keyword(s):

Muscle Strength ◽

Lower Limb ◽

Postural Balance ◽

The Elderly ◽

Knee Extension ◽

Knee Extensors ◽

Strong Positive Correlation ◽

Lower Limb Muscle ◽

Limb Muscle ◽

Positive Correlation

Introduction: Declines of static postural balance and muscle strength, especially of lower limbs are strong predictors of falls in the elderly. Objective: The objective of this study was to identify the possible correlation between static postural balance, falls and isokinetic torque peak of knee extensors and flexors in the elderly. Methods: A cross-sectional study with anthropometric evaluation of static postural balance in unipodal limb support was performed using the force platform, flexural strength test and knee extension of the dominant limb using the isokinetic dynamometer and the application of a structured questionnaire on falls. They agreed to participate in the study 106 volunteers of both sexes through the signing of the free and informed consent. The data were treated in the Statistical Package for the Social Sciences program version 20.0. Results: There was a weak positive correlation between center of pressure (COP) area and peak flexion torque (r=0.204, p=0.041) and extension (r=0.228; p=0.022) of the knee, as well as peak extension (r=0.319, p=0.001) and lateral mean (r=0.324, p=0.001). A moderate positive correlation between COP area and anteroposterior velocity (r=0.694, p=0.000) and lateral mean (r = 0.646; p = 0.000) and strong positive correlation was found only between peak flexion torque and knee extension (r=0.719, p=0.000). Conclusion: There was a weak correlation between static postural balance and dominant lower limb muscle strength, and there was no correlation between falls and lower limb muscle strength, or between falls and static postural balance in the studied sample.

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