Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement. (17th January 2016)
- Record Type:
- Journal Article
- Title:
- Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement. (17th January 2016)
- Main Title:
- Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement
- Authors:
- Caimmi, Marco
Visani, Elisa
Digiacomo, Fabio
Scano, Alessandro
Chiavenna, Andrea
Gramigna, Cristina
Molinari Tosatti, Lorenzo
Franceschetti, Silvana
Molteni, Franco
Panzica, Ferruccio - Other Names:
- Moreno Juan C. Academic Editor.
- Abstract:
- Abstract : Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of robotic interventions on selected patients, which in turn determine the necessity for new investigating instruments supporting the treatment decision-making process and customization. The objective of the work presented in this preliminary study was to verify that fully robot assistance would not affect the physiological oscillatory cortical activity related to a functional movement in healthy subjects. Further, the clinical results following the robotic treatment of a chronic stroke patient, who positively reacted to the robotic intervention, were analyzed and discussed. First results show that there is no difference in EEG activation pattern between assisted and no-assisted movement in healthy subjects. Even more importantly, the patient's pretreatment EEG activation pattern in no-assisted movement was completely altered, while it recovered to a quasi-physiological one in robot-assisted movement. The functional improvement following treatment was large. Using pretreatment EEG recording during robot-assisted movement might be a valid approach to assess the potential ability of the patient for recovering.
- Is Part Of:
- BioMed research international. Volume 2016(2016)
- Journal:
- BioMed research international
- Issue:
- Volume 2016(2016)
- Issue Display:
- Volume 2016, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 2016
- Issue:
- 2016
- Issue Sort Value:
- 2016-2016-2016-0000
- Page Start:
- Page End:
- Publication Date:
- 2016-01-17
- Subjects:
- Medicine -- Periodicals
Biology -- Periodicals
Biotechnology -- Periodicals
Life sciences -- Periodicals
610.5 - Journal URLs:
- https://www.hindawi.com/journals/bmri/ ↗
- DOI:
- 10.1155/2016/7051340 ↗
- Languages:
- English
- ISSNs:
- 2314-6133
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 22851.xml