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A Narrative Review on Multi-Domain Instrumental Approaches to Evaluate Neuromotor Function in Rehabilitation.
Scano, Alessandro; Guanziroli, Eleonora; Brambilla, Cristina; Amendola, Caterina; Pirovano, Ileana; Gasperini, Giulio; Molteni, Franco; Spinelli, Lorenzo; Molinari Tosatti, Lorenzo; Rizzo, Giovanna; Re, Rebecca; Mastropietro, Alfonso.
Afiliação
  • Scano A; Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Via A. Corti 12, 20133 Milan, Italy.
  • Guanziroli E; Villa Beretta Rehabilitation Center, Via N. Sauro 17, 23845 Costa Masnaga, Italy.
  • Brambilla C; Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Via A. Corti 12, 20133 Milan, Italy.
  • Amendola C; Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
  • Pirovano I; Institute of Biomedical Technologies (ITB), Italian National Research Council (CNR), Via Fratelli Cervi 93, 20054 Segrate, Italy.
  • Gasperini G; Villa Beretta Rehabilitation Center, Via N. Sauro 17, 23845 Costa Masnaga, Italy.
  • Molteni F; Villa Beretta Rehabilitation Center, Via N. Sauro 17, 23845 Costa Masnaga, Italy.
  • Spinelli L; Institute for Photonics and Nanotechnology (IFN), Italian National Research Council (CNR), Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
  • Molinari Tosatti L; Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Via A. Corti 12, 20133 Milan, Italy.
  • Rizzo G; Institute of Biomedical Technologies (ITB), Italian National Research Council (CNR), Via Fratelli Cervi 93, 20054 Segrate, Italy.
  • Re R; Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
  • Mastropietro A; Institute for Photonics and Nanotechnology (IFN), Italian National Research Council (CNR), Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Healthcare (Basel) ; 11(16)2023 Aug 13.
Article em En | MEDLINE | ID: mdl-37628480
ABSTRACT
In clinical scenarios, the use of biomedical sensors, devices and multi-parameter assessments is fundamental to provide a comprehensive portrait of patients' state, in order to adapt and personalize rehabilitation interventions and support clinical decision-making. However, there is a huge gap between the potential of the multidomain techniques available and the limited practical use that is made in the clinical scenario. This paper reviews the current state-of-the-art and provides insights into future directions of multi-domain instrumental approaches in the clinical assessment of patients involved in neuromotor rehabilitation. We also summarize the main achievements and challenges of using multi-domain approaches in the assessment of rehabilitation for various neurological disorders affecting motor functions. Our results showed that multi-domain approaches combine information and measurements from different tools and biological signals, such as kinematics, electromyography (EMG), electroencephalography (EEG), near-infrared spectroscopy (NIRS), and clinical scales, to provide a comprehensive and objective evaluation of patients' state and recovery. This multi-domain approach permits the progress of research in clinical and rehabilitative practice and the understanding of the pathophysiological changes occurring during and after rehabilitation. We discuss the potential benefits and limitations of multi-domain approaches for clinical decision-making, personalized therapy, and prognosis. We conclude by highlighting the need for more standardized methods, validation studies, and the integration of multi-domain approaches in clinical practice and research.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Healthcare (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Healthcare (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Itália