Myoelectric, Myo-Oxygenation, and Myotonometry Changes during Robot-Assisted Bilateral Arm Exercises with Varying Resistances Article Swipe
Hsiao‐Lung Chan
,
Ling-Fu Meng
,
Yung-An Kao
,
Ya‐Ju Chang
,
Hao-Wei Chang
,
Szi-Wen Chen
,
Ching‐Yi Wu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/s24041061
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/s24041061
Robot-assisted bilateral arm training has demonstrated its effectiveness in improving motor function in individuals post-stroke, showing significant enhancements with increased repetitions. However, prolonged training sessions may lead to both mental and muscle fatigue. We conducted two types of robot-assisted bimanual wrist exercises on 16 healthy adults, separated by one week: long-duration, low-resistance workouts and short-duration, high-resistance exercises. Various measures, including surface electromyograms, near-infrared spectroscopy, heart rate, and the Borg Rating of Perceived Exertion scale, were employed to assess fatigue levels and the impacts of exercise intensity. High-resistance exercise resulted in a more pronounced decline in electromyogram median frequency and recruited a greater amount of hemoglobin, indicating increased muscle fatigue and a higher metabolic demand to cope with the intensified workload. Additionally, high-resistance exercise led to increased sympathetic activation and a greater sense of exertion. Conversely, engaging in low-resistance exercises proved beneficial for reducing post-exercise muscle stiffness and enhancing muscle elasticity. Choosing a low-resistance setting for robot-assisted wrist movements offers advantages by alleviating mental and physiological loads. The reduced training intensity can be further optimized by enabling extended exercise periods while maintaining an approximate dosage compared to high-resistance exercises.
Related Topics
Concepts
Rating of perceived exertion
Workload
Physical medicine and rehabilitation
Resistance training
Muscle fatigue
Physical therapy
Wrist
Heart rate
Circuit training
Exertion
Medicine
Exercise intensity
Electromyography
Psychology
Blood pressure
Computer science
Internal medicine
Surgery
Operating system
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s24041061
- https://www.mdpi.com/1424-8220/24/4/1061/pdf?version=1707228996
- OA Status
- gold
- Cited By
- 1
- References
- 63
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391563014
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391563014Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s24041061Digital Object Identifier
- Title
-
Myoelectric, Myo-Oxygenation, and Myotonometry Changes during Robot-Assisted Bilateral Arm Exercises with Varying ResistancesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-06Full publication date if available
- Authors
-
Hsiao‐Lung Chan, Ling-Fu Meng, Yung-An Kao, Ya‐Ju Chang, Hao-Wei Chang, Szi-Wen Chen, Ching‐Yi WuList of authors in order
- Landing page
-
https://doi.org/10.3390/s24041061Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/24/4/1061/pdf?version=1707228996Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/24/4/1061/pdf?version=1707228996Direct OA link when available
- Concepts
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Rating of perceived exertion, Workload, Physical medicine and rehabilitation, Resistance training, Muscle fatigue, Physical therapy, Wrist, Heart rate, Circuit training, Exertion, Medicine, Exercise intensity, Electromyography, Psychology, Blood pressure, Computer science, Internal medicine, Surgery, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- References (count)
-
63Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.demonstrated | 5 |
| abstract_inverted_index.enhancements | 17 |
| abstract_inverted_index.post-stroke, | 14 |
| abstract_inverted_index.repetitions. | 20 |
| abstract_inverted_index.Additionally, | 120 |
| abstract_inverted_index.effectiveness | 7 |
| abstract_inverted_index.near-infrared | 62 |
| abstract_inverted_index.physiological | 164 |
| abstract_inverted_index.post-exercise | 143 |
| abstract_inverted_index.spectroscopy, | 63 |
| abstract_inverted_index.Robot-assisted | 0 |
| abstract_inverted_index.electromyogram | 95 |
| abstract_inverted_index.long-duration, | 50 |
| abstract_inverted_index.low-resistance | 51, 137, 152 |
| abstract_inverted_index.robot-assisted | 38, 155 |
| abstract_inverted_index.High-resistance | 86 |
| abstract_inverted_index.high-resistance | 55, 121, 186 |
| abstract_inverted_index.short-duration, | 54 |
| abstract_inverted_index.electromyograms, | 61 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5048639337, https://openalex.org/A5068995498 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I173093425, https://openalex.org/I3020100970 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.6899999976158142 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.46869996 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |