Literature DB >> 25910194

Monitoring Neuro-Motor Recovery From Stroke With High-Resolution EEG, Robotics and Virtual Reality: A Proof of Concept.

Silvia Comani, Lucia Velluto, Lorenzo Schinaia, Gianluigi Cerroni, Antonio Serio, Sandro Buzzelli, Sandro Sorbi, Biancamaria Guarnieri.   

Abstract

A novel system for the neuro-motor rehabilitation of upper limbs was validated in three sub-acute post-stroke patients. The system permits synchronized cortical and kinematic measures by integrating high-resolution EEG, passive robotic device and Virtual Reality. The brain functional re-organization was monitored in association with motor patterns replicating activities of daily living (ADL). Patients underwent 13 rehabilitation sessions. At sessions 1, 7 and 13, clinical tests were administered to assess the level of motor impairment, and EEG was recorded during rehabilitation task execution. For each session and rehabilitation task, four kinematic indices of motor performance were calculated and compared with the outcome of clinical tests. Functional source maps were obtained from EEG data and projected on the real patients' anatomy (MRI data). Laterality indices were calculated for hemispheric dominance assessment. All patients showed increased participation in the rehabilitation process. Cortical activation changes during recovery were detected in relation to different motor patterns, hence verifying the system's suitability to add quantitative measures of motor performance and neural recovery to classical tests. We conclude that this system seems a promising tool for novel robot-based rehabilitation paradigms tailored to individual needs and neuro-motor responses of the patients.

Entities:  

Mesh:

Year:  2015        PMID: 25910194     DOI: 10.1109/TNSRE.2015.2425474

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  12 in total

1.  The Impact of Electroacupuncture at Hegu, Shousanli, and Quchi Based on the Theory "Treating Flaccid Paralysis by Yangming Alone" on Stroke Patients' EEG: A Pilot Study.

Authors:  Fei Zou; Yi-Fang Lin; Shu-Geng Chen; Lei Cao; Hao-Ran Wang; Bin Ye; Qiang Wang; He Jie-Ying; Jie Jia
Journal:  Evid Based Complement Alternat Med       Date:  2020-11-24       Impact factor: 2.629

2.  Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

Authors:  Jianhua Zhang; Zhong Yin; Rubin Wang
Journal:  Front Neurosci       Date:  2017-03-17       Impact factor: 4.677

3.  A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings.

Authors:  Gabriella Tamburro; Patrique Fiedler; David Stone; Jens Haueisen; Silvia Comani
Journal:  PeerJ       Date:  2018-02-23       Impact factor: 2.984

Review 4.  Evaluating the use of robotic and virtual reality rehabilitation technologies to improve function in stroke survivors: A narrative review.

Authors:  William E Clark; Manoj Sivan; Rory J O'Connor
Journal:  J Rehabil Assist Technol Eng       Date:  2019-11-13

5.  Is Brain Dynamics Preserved in the EEG After Automated Artifact Removal? A Validation of the Fingerprint Method and the Automatic Removal of Cardiac Interference Approach Based on Microstate Analysis.

Authors:  Gabriella Tamburro; Pierpaolo Croce; Filippo Zappasodi; Silvia Comani
Journal:  Front Neurosci       Date:  2021-01-12       Impact factor: 4.677

6.  Weakened Effective Connectivity Related to Electroacupuncture in Stroke Patients with Prolonged Flaccid Paralysis: An EEG Pilot Study.

Authors:  Yi-Fang Lin; Xin-Hua Liu; Zheng-Yu Cui; Zuo-Ting Song; Fei Zou; Shu-Geng Chen; Xiao-Yang Kang; Bin Ye; Qiang Wang; Jing Tian; Jie Jia
Journal:  Neural Plast       Date:  2021-03-09       Impact factor: 3.599

7.  Improving motor function after chronic stroke by interactive gaming with a redesigned MR-compatible hand training device.

Authors:  Loukas G Astrakas; Gianluca De Novi; Mark P Ottensmeyer; Christian Pusatere; Shasha Li; Michael A Moskowitz; A Aria Tzika
Journal:  Exp Ther Med       Date:  2021-01-22       Impact factor: 2.447

8.  Backward Walking Induces Significantly Larger Upper-Mu-Rhythm Suppression Effects Than Forward Walking Does.

Authors:  Nan-Hung Lin; Chin-Hsuan Liu; Posen Lee; Lan-Yuen Guo; Jia-Li Sung; Chen-Wen Yen; Lih-Jiun Liaw
Journal:  Sensors (Basel)       Date:  2020-12-17       Impact factor: 3.576

Review 9.  EEG-Based Control for Upper and Lower Limb Exoskeletons and Prostheses: A Systematic Review.

Authors:  Maged S Al-Quraishi; Irraivan Elamvazuthi; Siti Asmah Daud; S Parasuraman; Alberto Borboni
Journal:  Sensors (Basel)       Date:  2018-10-07       Impact factor: 3.576

10.  Exoskeletons With Virtual Reality, Augmented Reality, and Gamification for Stroke Patients' Rehabilitation: Systematic Review.

Authors:  Omar Mubin; Fady Alnajjar; Nalini Jishtu; Belal Alsinglawi; Abdullah Al Mahmud
Journal:  JMIR Rehabil Assist Technol       Date:  2019-09-08
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.