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Review

Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

1
Software Research Group, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia
2
School of Computer Science, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia
3
Department of Electrical and Information Engineering, Polytechnic University of Bari, 70126 Bari, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Lorenzo Chiari
Sensors 2021, 21(6), 2146; https://doi.org/10.3390/s21062146
Received: 31 December 2020 / Revised: 4 March 2021 / Accepted: 6 March 2021 / Published: 18 March 2021
(This article belongs to the Special Issue Electronics for E-health Sensor Systems)
Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology. View Full-Text
Keywords: robotic exoskeletons; wearable devices; artificial intelligence (AI); artificial neural networks (ANN); adaptive algorithms; upper limbs; rehabilitation; healthcare; control strategies robotic exoskeletons; wearable devices; artificial intelligence (AI); artificial neural networks (ANN); adaptive algorithms; upper limbs; rehabilitation; healthcare; control strategies
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MDPI and ACS Style

Vélez-Guerrero, M.A.; Callejas-Cuervo, M.; Mazzoleni, S. Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review. Sensors 2021, 21, 2146. https://doi.org/10.3390/s21062146

AMA Style

Vélez-Guerrero MA, Callejas-Cuervo M, Mazzoleni S. Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review. Sensors. 2021; 21(6):2146. https://doi.org/10.3390/s21062146

Chicago/Turabian Style

Vélez-Guerrero, Manuel A., Mauro Callejas-Cuervo, and Stefano Mazzoleni. 2021. "Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review" Sensors 21, no. 6: 2146. https://doi.org/10.3390/s21062146

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