Publicação
Decision support systems for lower limb rehabilitation using electrical stimulation—a review
| Resumo: | This paper presents a comprehensive review of Decision Support Systems (DSS) for lower limb rehabilitation using Electrical Stimulation (ES), employing a rigorous two-part methodology. The first part involves a bibliometric analysis of articles from 1980 to 2023, while the second part is a systematic review of studies from 2019 to 2023, addressing six key research questions. The review identifies the main characteristics of DSS, such as data usage, sensitive data protection, reasoning techniques, and validation processes. It highlights the development focus on joint control systems, increasing interest in biofeedback and AI applications, and significant interest in FES-Cycling. Despite advancements, “decision support” remains in the early stages with simple architectures and limited data handling. Conversely, studies show advanced ES control models validated with neurological patients. This article emphasizes the need for sophisticated DSS that integrate data protection, reasoning methods, and patient monitoring to enhance rehabilitation outcomes and identifies significant gaps for future research. |
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| Autores principais: | Franco, Tiago |
| Outros Autores: | Henriques, Pedro; Alves, Paulo; Pereira, Maria João |
| Assunto: | Decision support system Lower limb Rehabilitation Electrical stimulation Review |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | This paper presents a comprehensive review of Decision Support Systems (DSS) for lower limb rehabilitation using Electrical Stimulation (ES), employing a rigorous two-part methodology. The first part involves a bibliometric analysis of articles from 1980 to 2023, while the second part is a systematic review of studies from 2019 to 2023, addressing six key research questions. The review identifies the main characteristics of DSS, such as data usage, sensitive data protection, reasoning techniques, and validation processes. It highlights the development focus on joint control systems, increasing interest in biofeedback and AI applications, and significant interest in FES-Cycling. Despite advancements, “decision support” remains in the early stages with simple architectures and limited data handling. Conversely, studies show advanced ES control models validated with neurological patients. This article emphasizes the need for sophisticated DSS that integrate data protection, reasoning methods, and patient monitoring to enhance rehabilitation outcomes and identifies significant gaps for future research. |
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