Improving the acceptability to enhance the efficiency of stroke rehabilitation procedures based on brain-computer interfaces
Améliorer l'acceptabilité pour optimiser l'efficience des interfaces cerveau-ordinateur dans le cadre de la rééducation motrice post-accident vasculaire cérébral (AVC)
Résumé
Stroke leaves around 40% of surviving patients dependent in their activities of daily living, notably due to severe motor disabilities [Inserm, 2019]. Brain-Computer Interfaces (BCIs) have been shown to be efficient for improving motor recovery after stroke [Cervera et al., 2018], but this efficiency is still far from the level required to achieve the clinical breakthrough expected by both clinicians and patients. While technical levers of improvement have been identified, they are insufficient: fully optimised BCIs are pointless if patients and clinicians do not want to use them [Blain-Moraes et al., 2012].We hypothesise that improving BCI acceptability and acceptance, by better informing stakeholders about BCI functioning and by personalising the BCI-based rehabilitation procedures to each patient, respectively, will favour engagement in the rehabilitation process and result in an increased efficiency.Our first objective was to identify the factors influencing the intention to use (IU) BCIs [Davis, 1989]. Based on the literature, we constructed a model of BCI acceptability and adapted it in questionnaires addressed to the general population (n=753) and post-stroke patients (n=33). Videos were included, one about the general functioning of BCIs, the second about their relevance for rehabilitation.We used random forest algorithms to explain IU based on our model's factors. After the first video, IU was mainly explained by subjective and personal factors, i.e., perceived usefulness (PU), perceived ease of use (PEOU) and BCI playfulness for the general population, and PU, autonomy and engagement in the rehabilitation for the patients. After the second video, the explanatory factors became more scientific/rational, with PU, cost-benefits ratio and scientific relevance for the general population, and PU, scientific relevance and ease of learning for patients.The shift of main explanatory factors (before/after second video) from subjective representations to scientific arguments highlights the impact of providing patients with clear information regarding BCIs.
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