- Title
- IoT-powered deep learning brain network for assisting quadriplegic people
- Creator
- Vinoj, P.; Jacob, Sunil; Menon, Varun; Balasubramanian, Venki; Piran, Md Jalil
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/176881
- Identifier
- vital:15212
- Identifier
-
https://doi.org/10.1016/j.compeleceng.2021.107113
- Identifier
- ISBN:0045-7906 (ISSN)
- Abstract
- Brain-Computer Interface (BCI) systems have recently emerged as a prominent technology for assisting paralyzed people. Recovery from paralysis in most patients using the existing BCI-based assistive devices is hindered due to the lack of training and proper supervision. The system's continuous usage results in mental fatigue, owing to a higher user concentration required to execute the mental commands. Moreover, the false-positive rate and lack of constant control of the BCI systems result in user frustration. The proposed framework integrates BCI with a deep learning network in an efficient manner to reduce mental fatigue and frustration. The Deep learning Brain Network (DBN) recognizes the patient's intention for upper limb movement by a deep learning model based on the features extracted during training. DBN correlates and maps the different Electroencephalogram (EEG) patterns of healthy subjects with the identified pattern's upper limb movement. The stroke-affected muscles of the paralyzed are then activated using the obtained superior pattern. The implemented DBN consisting of four healthy subjects and a quadriplegic patient achieved 94% accuracy for various patient movement intentions. The results show that DBN is an excellent tool for providing rehabilitation, and it delivers sustained assistance, even in the absence of caregivers. © 2021
- Publisher
- Elsevier Ltd
- Relation
- Computers and Electrical Engineering Vol. 92, no. (2021), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright @ 2021 Elsevier Ltd.
- Subject
- 0803 Computer Software; 0805 Distributed Computing; 0906 Electrical and Electronic Engineering; BCI; DBN, Deep learning; EEG; Intelligent system; Rehabilitation
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