Adaptive Algorithms as Control Strategies of Smart Upper Limb Orthosis: A Protocol for a Systematic Scoping Review

Frontiers in Neuroscience

Júlia A. de Amorim¹  Danilo A. P. Nagem¹  Ricardo A. de M. Valentim¹  Edgard Morya²  Ana Paula M. Fernandes⁴  Severino P. Nunes Netto⁴  Aryel M. Matias⁴  Ledycnarf J. Holanda⁴  Ana Raquel Lindquist⁴ 

[1] Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, Brazil;Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, Macaiba, Brazil;Laboratory of Intervention and Analysis of Movement, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil;Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil;

关键词: adaptive algorithms;    upper limb orthosis;    upper limb rehabilitation;    functionality;    movement;   

DOI  :  10.3389/fnins.2021.660141

来源: DOAJ

【 摘 要 】

Introduction: Adaptive algorithms for controlling orthosis emerged to overcome significant problems with automatic biosignal classification and personalized rehabilitation. Smart orthoses are evolving fast and need a better human-machine interaction performance since biosignals, feedback, and motor control dynamically change and must be adaptive. This manuscript outlines a scoping review protocol to systematically review the smart upper limb (UL) orthoses based on adaptive algorithms and feasibility tests.Materials and Methods: This protocol was developed based on the York framework. A field-specific structure was defined to achieve each phase. Eleven scientific databases (PubMed, Web of Science, SciELO, Koreamed, Jstage, AMED, CENTRAL, PEDro, IEEE, Scopus, and Arxiv) and five patent databases (Patentscope, Patentlens, Google Patents, Kripis, J-platpat) were searched. The developed framework will extract data (i.e., orthosis description, adaptive algorithms, tools used in the usability test, and benefits to the general population) from the selected studies using a rigorous approach. Data will be described quantitatively using frequency and trend analysis methods. Heterogeneity between the included studies will be assessed using the Chi-test and I-statistic. The risk of bias will be summarized using the latest Prediction Model Study Risk of Bias Assessment Tool.Discussion: This review will identify, map, and synthesize the advances about the description of adaptive algorithms for control strategies of smart UL orthosis using data extracted from patents and articles.

【 授权许可】

Unknown