A Statistical Approach for the Assessment of Muscle Activation Patterns during Gait in Parkinson’s Disease Article Swipe
Giulia Pacini Panebianco
,
Davide Ferrazzoli
,
Giuseppe Frazzitta
,
M. Fonsato
,
Maria Cristina Bisi
,
Silvia Fantozzi
,
Rita Stagni
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/electronics9101641
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/electronics9101641
Recently, the statistical analysis of muscle activation patterns highlighted that not only one, but several activation patterns can be identified in the gait of healthy adults, with different occurrence. Although its potential, the application of this approach in pathological populations is still limited and specific implementation issues need to be addressed. This study aims at applying a statistical approach to analyze muscle activation patterns of gait in Parkinson’s Disease, integrating gait symmetry and co-activation. Surface electromyographic signal of tibialis anterior and gastrocnemius medialis were recorded during a 6-min walking test in 20 patients. Symmetry between right and left stride time series was verified, different activation patterns identified, and their occurrence (number and timing) quantified, as well as the co-activation of antagonist muscles. Gastrocnemius medialis presented five activation patterns (mean occurrence ranging from 2% to 43%) showing, with respect to healthy adults, the presence of a first shorted and delayed activation (between flat foot contact and push off, and in the final swing) and highlighting a new second region of anticipated activation (during early/mid swing). Tibialis anterior presented five activation patterns (mean occurrence ranging from 3% to 40%) highlighting absent or delayed activity at the beginning of the gait cycle, and generally shorter and anticipated activations during the swing phase with respect to healthy adults. Three regions of co-contraction were identified: from heel strike to mid-stance, from the pre- to initial swing, and during late swing. This study provided a novel insight in the analysis of muscle activation patterns in Parkinson’s Disease patients with respect to the literature, where unique, at times conflicting, average patterns were reported. The proposed integrated methodology is meant to be generalized for the analysis of muscle activation patterns in pathologic subjects.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/electronics9101641
- https://www.mdpi.com/2079-9292/9/10/1641/pdf?version=1602420774
- OA Status
- gold
- Cited By
- 5
- References
- 48
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3089841246
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3089841246Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/electronics9101641Digital Object Identifier
- Title
-
A Statistical Approach for the Assessment of Muscle Activation Patterns during Gait in Parkinson’s DiseaseWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-10-05Full publication date if available
- Authors
-
Giulia Pacini Panebianco, Davide Ferrazzoli, Giuseppe Frazzitta, M. Fonsato, Maria Cristina Bisi, Silvia Fantozzi, Rita StagniList of authors in order
- Landing page
-
https://doi.org/10.3390/electronics9101641Publisher landing page
- PDF URL
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https://www.mdpi.com/2079-9292/9/10/1641/pdf?version=1602420774Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2079-9292/9/10/1641/pdf?version=1602420774Direct OA link when available
- Concepts
-
Physical medicine and rehabilitation, Gait, Tibialis anterior muscle, Swing, STRIDE, Gait analysis, Electromyography, Medicine, Psychology, Anatomy, Skeletal muscle, Physics, AcousticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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5Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2022: 2, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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48Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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