Changes in the Behavior of the Ankle Plantar Flexor Motor Unit Due to Knee Assistance for Heel-Raise
2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech)(2022)
Faculty of Health Science | Graduate Course of Health and Social Services
Abstract
The heel-rise is frequently performed to train patients who are unable to plantar flex their ankle joints. Patients are often assisted by therapists because their wholebody muscle strength is impaired. However, it is unclear how the muscle activity of the ankle plantar flexors changes with the assistance. Furthermore, since patients often suffer from neurological disorders, it is important to observe not only the amplitude of the compound action potential but also the behavior of the motor units. In this study, we examined the number and frequency of motor unit firings in the ankle planter flexors during the heel-raise in 14 healthy adults with and without a knee contracture orthosis. In addition, the Peason's correlation coefficient was used to verify whether the same motor units were detected across conditions; r > 0.8 was considered identical. The high-density surface electromyogram used to detect the motor units. Correspondence t-test was used for comparison between conditions. As a result, the number of motor unit firings of the soleus was higher under the condition with orthosis (p = 0.03). On the other hand, there was no significant difference in the frequency of firing of motor units between the conditions. In addition, the number of the same motor units detected between the conditions was only 16.84%. We cannot directly conclude the efficacy of using the orthosis during training, and further verification is necessary because of the possible limitation of detecting motor units from four electrodes of the measurement device.
MoreTranslated text
Key words
Training,Neurological diseases,Electrodes,Correlation coefficient,Flexible printed circuits,Firing,Conferences
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2015
被引用14 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper