- Title
- AI and IoT-Enabled smart exoskeleton system for rehabilitation of paralyzed people in connected communities
- Creator
- Jacob, Sunil; Alagirisamy, Mukil; Xi, Chen; Balasubramanian, Venki; Srinivasan, Ram
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/177466
- Identifier
- vital:15299
- Identifier
-
https://doi.org/10.1109/ACCESS.2021.3083093
- Identifier
- ISBN:2169-3536 (ISSN)
- Abstract
- In recent years, the number of cases of spinal cord injuries, stroke and other nervous impairments have led to an increase in the number of paralyzed patients worldwide. Rehabilitation that can aid and enhance the lives of such patients is the need of the hour. Exoskeletons have been found as one of the popular means of rehabilitation. The existing exoskeletons use techniques that impose limitations on adaptability, instant response and continuous control. Also most of them are expensive, bulky, and requires high level of training. To overcome all the above limitations, this paper introduces an Artificial Intelligence (AI) powered Smart and light weight Exoskeleton System (AI-IoT-SES) which receives data from various sensors, classifies them intelligently and generates the desired commands via Internet of Things (IoT) for rendering rehabilitation and support with the help of caretakers for paralyzed patients in smart and connected communities. In the proposed system, the signals collected from the exoskeleton sensors are processed using AI-assisted navigation module, and helps the caretakers in guiding, communicating and controlling the movements of the exoskeleton integrated to the patients. The navigation module uses AI and IoT enabled Simultaneous Localization and Mapping (SLAM). The casualties of a paralyzed person are reduced by commissioning the IoT platform to exchange data from the intelligent sensors with the remote location of the caretaker to monitor the real time movement and navigation of the exoskeleton. The automated exoskeleton detects and take decisions on navigation thereby improving the life conditions of such patients. The experimental results simulated using MATLAB shows that the proposed system is the ideal method for rendering rehabilitation and support for paralyzed patients in smart communities. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramanian” is provided in this record**
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- IEEE Access Vol. 9, no. (2021), p. 80340-80350
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright © 2013 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
- Rights
- Open Access
- Subject
- 08 Information and Computing Sciences; 09 Engineering; 10 Technology; Artificial intelligence; Assistive technology; Deep learning; Exoskeleton; Internet of Things; Smart connected community
- Full Text
- Reviewed
- Funder
- This work was supported in part by the National Social Science Foundation of China under Grant 21ZDA033, in part by the National Natural Science Foundation of China under Grant 71771118 and Grant 72071104, in part by the Ministry of Education Humanities and Social Sciences Foundation of China under Grant 18YJCZH146, and in part by the Key Project of Jiangsu Social Science Foundation under Grant 20GLA007.
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