Technology Acceptance Model for Exoskeletons for Rehabilitation of the Upper Limbs from Therapists' Perspectives.

Pearson’s correlation integrated sensor systems multiple linear regression neuro-rehabilitation rehabilitation exoskeletons technology acceptance model therapists

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
03 Feb 2023
Historique:
received: 09 01 2023
revised: 27 01 2023
accepted: 02 02 2023
entrez: 11 2 2023
pubmed: 12 2 2023
medline: 15 2 2023
Statut: epublish

Résumé

Over the last few years, exoskeletons have been demonstrated to be useful tools for supporting the execution of neuromotor rehabilitation sessions. However, they are still not very present in hospitals. Therapists tend to be wary of this type of technology, thus reducing its acceptability and, therefore, its everyday use in clinical practice. The work presented in this paper investigates a novel point of view that is different from that of patients, which is normally what is considered for similar analyses. Through the realization of a technology acceptance model, we investigate the factors that influence the acceptability level of exoskeletons for rehabilitation of the upper limbs from therapists' perspectives. We analyzed the data collected from a pool of 55 physiotherapists and physiatrists through the distribution of a questionnaire. Pearson's correlation and multiple linear regression were used for the analysis. The relations between the variables of interest were also investigated depending on participants' age and experience with technology. The model built from these data demonstrated that the perceived usefulness of a robotic system, in terms of time and effort savings, was the first factor influencing therapists' willingness to use it. Physiotherapists' perception of the importance of interacting with an exoskeleton when carrying out an enhanced therapy session increased if survey participants already had experience with this type of rehabilitation technology, while their distrust and the consideration of others' opinions decreased. The conclusions drawn from our analyses show that we need to invest in making this technology better known to the public-in terms of education and training-if we aim to make exoskeletons genuinely accepted and usable by therapists. In addition, integrating exoskeletons with multi-sensor feedback systems would help provide comprehensive information about the patients' condition and progress. This can help overcome the gap that a robot creates between a therapist and the patient's human body, reducing the fear that specialists have of this technology, and this can demonstrate exoskeletons' utility, thus increasing their perceived level of usefulness.

Identifiants

pubmed: 36772758
pii: s23031721
doi: 10.3390/s23031721
pmc: PMC9919869
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Beatrice Luciani (B)

Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy.
NeuroEngineering And Medical Robotics Laboratory (NEARLab), Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy.

Francesco Braghin (F)

Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy.

Alessandra Laura Giulia Pedrocchi (ALG)

NeuroEngineering And Medical Robotics Laboratory (NEARLab), Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy.
WE-COBOT Lab, Politecnico di Milano, Polo Territoriale di Lecco, Via G. Previati, 1/c, 23900 Lecco, Italy.

Marta Gandolla (M)

Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy.
NeuroEngineering And Medical Robotics Laboratory (NEARLab), Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy.
WE-COBOT Lab, Politecnico di Milano, Polo Territoriale di Lecco, Via G. Previati, 1/c, 23900 Lecco, Italy.

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