Literature DB >> 29994006

Advances in Automation Technologies for Lower Extremity Neurorehabilitation: A Review and Future Challenges.

Wenhao Deng, Ioannis Papavasileiou, Zhi Qiao, Wenlong Zhang, Kam-Yiu Lam, Song Han.   

Abstract

The world is experiencing an unprecedented, enduring, and pervasive aging process. With more people who need walking assistance, the demand for lower extremity gait rehabilitation has increased rapidly over the years. The current clinical gait rehabilitative training requires heavy involvement of both medical doctors and physical therapists, and thus, are labor intensive, subjective, and expensive. To address these problems, advanced automation techniques, especially along with the proliferation of smart sensing and actuation devices and big data analytics platforms, have been introduced into this field to make the gait rehabilitation convenient, efficient, and personalized. This survey paper provides a comprehensive review on recent technological advances in wearable sensors, biofeedback devices, and assistive robots. Empowered by the emerging networking and computing technologies in the big data era, these devices are being interconnected into smart and connected rehabilitation systems to provide nonintrusive and continuous monitoring of physical and neurological conditions of the patients, perform complex gait analysis and diagnosis, and allow real-time decision making, biofeedback, and control of assistive robots. For each technology category, a detailed comparison among the existing solutions is provided. A thorough discussion is also presented on remaining open problems and future directions to further improve the safety, efficiency, and usability of the technologies.

Entities:  

Mesh:

Year:  2018        PMID: 29994006     DOI: 10.1109/RBME.2018.2830805

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  5 in total

1.  Assessing the Involvement of Users During Development of Lower Limb Wearable Robotic Exoskeletons: A Survey Study.

Authors:  Anna L Ármannsdóttir; Philipp Beckerle; Juan C Moreno; Edwin H F van Asseldonk; Maria-Teresa Manrique-Sancho; Antonio J Del-Ama; Jan F Veneman; Kristín Briem
Journal:  Hum Factors       Date:  2020-01-13       Impact factor: 2.888

Review 2.  EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots.

Authors:  Madiha Tariq; Pavel M Trivailo; Milan Simic
Journal:  Front Hum Neurosci       Date:  2018-08-06       Impact factor: 3.169

Review 3.  Meta-Analysis of Integrated Therapeutic Methods in Noninvasive Lower Back Pain Therapy (LBP): The Role of Interdisciplinary Functional Diagnostics.

Authors:  Aleksandra Bitenc-Jasiejko; Krzysztof Konior; Danuta Lietz-Kijak
Journal:  Pain Res Manag       Date:  2020-03-19       Impact factor: 3.037

4.  Embodiment of supernumerary robotic limbs in virtual reality.

Authors:  Ken Arai; Hiroto Saito; Masaaki Fukuoka; Sachiyo Ueda; Maki Sugimoto; Michiteru Kitazaki; Masahiko Inami
Journal:  Sci Rep       Date:  2022-06-27       Impact factor: 4.996

5.  Mu-Beta event-related (de)synchronization and EEG classification of left-right foot dorsiflexion kinaesthetic motor imagery for BCI.

Authors:  Madiha Tariq; Pavel M Trivailo; Milan Simic
Journal:  PLoS One       Date:  2020-03-17       Impact factor: 3.240

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.