Posts Tagged Brain computer interfaces (BCI)
[Abstract + References] Soft Robotic Glove with Alpha Band Brain Computer Interface for Post-Stroke Hand Function Rehabilitation – Conference Publication
Posted by Kostas Pantremenos in Paretic Hand, REHABILITATION, Rehabilitation robotics on January 26, 2023
Abstract:
Loss of hand dexterity is a major challenge faced by post-stroke patients who strive to resume their ordinary daily lives. Effective hand function rehabilitation treatment for such population is therefore necessary. A soft robotic glove system operated through SSVEP-based BCI has been reported to be an effective tool for post-stroke hand motor function recovery. This study further evaluated the application of visual stimulation in the alpha band for SSVEP-assisted rehabilitation. We compared the treatment outcome with stimulations within the alpha band to that outside the band. A total of 20 post-stroke patients with severe upper limb dysfunction were randomly assigned to alpha band group and non-alpha band group. The experiment result was assessed with Fugl-Meyer upper limb Motor Assessment (FMAUE) and alpha EEG oscillation analysis. The alpha band group showed slightly but notably higher FMA-UE scores (P<0.05), and significantly increased alpha wave EEG oscillations (P<0.05). The result demonstrated the usefulness of alpha band SSVEP for post stroke hand function rehabilitation.
Published in: 2022 14th Biomedical Engineering International Conference (BMEiCON)
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[Abstract] SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation
Posted by Kostas Pantremenos in Paretic Hand, Rehabilitation robotics on June 27, 2022
Abstract:
Soft robotic glove with brain computer interfaces (BCI) control has been used for post-stroke hand function rehabilitation. Motor imagery (MI) based BCI with robotic aided devices has been demonstrated as an effective neural rehabilitation tool to improve post-stroke hand function. It is necessary for a user of MI-BCI to receive a long time training, while the user usually suffers unsuccessful and unsatisfying results in the beginning. To propose another non-invasive BCI paradigm rather than MI-BCI, steady-state visually evoked potentials (SSVEP) based BCI was proposed as user intension detection to trigger the soft robotic glove for post-stroke hand function rehabilitation. Thirty post-stroke patients with impaired hand function were randomly and equally divided into three groups to receive conventional, robotic, and BCI-robotic therapy in this randomized control trial (RCT). Clinical assessment of Fugl-Meyer Motor Assessment of Upper Limb (FMA-UL), Wolf Motor Function Test (WMFT) and Modified Ashworth Scale (MAS) were performed at pre-training, post-training and three months follow-up. In comparing to other groups, The BCI-robotic group showed significant improvement after training in FMA full score (10.05±8.03, p=0.001), FMA shoulder/elbow (6.2±5.94, p=0.0004) and FMA wrist/hand (4.3±2.83, p=0.007), and WMFT (5.1±5.53, p=0.037). The improvement of FMA was significantly correlated with BCI accuracy (r=0.714, p=0.032). Recovery of hand function after rehabilitation of SSVEP-BCI controlled soft robotic glove showed better result than solely robotic glove rehabilitation, equivalent efficacy as results from previous reported MI-BCI robotic hand rehabilitation. It proved the feasibility of SSVEP-BCI controlled soft robotic glove in post-stroke hand function rehabilitation.
TBI Rehabilitation 