Following major accidents or illness, some patients may lose partially or completely some of their mental or physical function. Rehabilitation approaches and systems play an important role in patients’ recovery. This article focuses on rehabilitation systems. We provide insights on major and recent approaches, signals, and systems used to assist patient recovery. In order to help researchers, engineers, or physicians, this article provides a comprehensive survey on recent approaches and systems used in the rehabilitation process. By highlighting the advantages and drawbacks of existing rehabilitation systems, this contribution can support initial studies or projects and encourage young researchers, as well as biomedical companies, to investigate and invest in new technologies. We hope that our study will participate in the global efforts paid to reduce patient suffering and help health care centers in their activities. To achieve this goal, we consider in our study recent technologies, such as machine learning, artificial intelligence, and signal processing, without missing to highlight various biomedical signals and exploring several developed systems.

A Comprehensive Survey on Advanced Technologies Introduced for Rehabilitation / Rong, Yue; Crippa, Paolo; Mansour, Ali; Al-Jumaily, Adel. - In: IEEE SENSORS REVIEWS. - ISSN 2995-7478. - 2:(2025), pp. 265-291. [10.1109/sr.2025.3572443]

A Comprehensive Survey on Advanced Technologies Introduced for Rehabilitation

Crippa, Paolo;
2025-01-01

Abstract

Following major accidents or illness, some patients may lose partially or completely some of their mental or physical function. Rehabilitation approaches and systems play an important role in patients’ recovery. This article focuses on rehabilitation systems. We provide insights on major and recent approaches, signals, and systems used to assist patient recovery. In order to help researchers, engineers, or physicians, this article provides a comprehensive survey on recent approaches and systems used in the rehabilitation process. By highlighting the advantages and drawbacks of existing rehabilitation systems, this contribution can support initial studies or projects and encourage young researchers, as well as biomedical companies, to investigate and invest in new technologies. We hope that our study will participate in the global efforts paid to reduce patient suffering and help health care centers in their activities. To achieve this goal, we consider in our study recent technologies, such as machine learning, artificial intelligence, and signal processing, without missing to highlight various biomedical signals and exploring several developed systems.
2025
Artificial intelligence, blind source separation, dedicated hardware and software, electrocardiogram (ECG), electroencephalography (EEG), electromyography (EMG), empirical mode decomposition (EMD), extra training, image processing, independent component analysis (ICA), machine learning, myoelectric signals, rehabilitation, signal processing, singular value decomposition, surface EMG (sEMG), wearable devices
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/345615
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