JMIR Publications

ABSTRACT

Background:

The high incidence and prevalence of upper limb impairment post-stroke highlights the need for advancements in rehabilitation. Brain-Computer Interfaces (BCIs) represent a promising technology by directly training the central nervous system. The integration of motor imagery (MI) and motor observation (MO) through virtual reality (VR) using BCIs provides valuable opportunities for rehabilitation. However, the diversity in intervention designs demonstrates the lack of guiding recommendations integrating neurorehabilitation principles for BCI.

Objective:

This study aims to develop recommendations for BCI interventions using task specificity and ecological validity through simulated VR tasks for upper limb stroke survivors, by gathering tacit knowledge from neurorehabilitation experts, patients’ experiences, and engineers’ expertise to ensure a comprehensive approach.

Methods:

A multi-perspective qualitative study was conducted through collaborative design workshops involving stroke survivors (N=17), neurorehabilitation experts (N=13) and biomedical engineers (N=3), totaling 33 participants. This innovative approach aimed to actively engage stakeholders in developing multifaceted solutions for complex health interventions.

Results:

Six themes emerged from the thematic analysis: i) Importance of patient-centered approach; ii) Clinical evaluation and patient selection; iii) Recommendations for task design; iv) Guidelines for structuring BCI intervention; v) Key factors influencing motivation; and vi) Technology features. From these themes, the following recommendations (R) are established: R1 - VR-BCI interventions must be conducted through a Patient-Centered Approach, based on individualized preferences, needs and goals of the user, by an interdisciplinary team; R2 - Selection criteria must include upper limb impairment, cognitive and communication assessment and clinical traits like motor imagery capacity, neglect and depression must be assessed since it might influence intervention outcomes; R3 - Tasks to perform should preferably be based on daily living activities including unilateral and bilateral tasks and a variety of tasks must be available for selection to ensure meaningfulness for the user and suitability to clinical traits; R4 - Intervention must be structured by different progressing levels starting with simple, gross movements and adding complexity through additional movement features, cognitive demand or motor imagery difficulty; R5 - Optimal levels of motivation must be sustained through task variability, gamification elements and task demand adequacy; R6 - Multisensorial potential of VR-BCI must be effectively harnessed through the adequate adjustment of visual, haptic and proprioceptive feedback modalities to the patient.

Conclusions:

Current results contribute to establishing clear guidelines on patient selection, task design, intervention structuring, motivation factors and tailoring of sensory feedback. This framework presents a foundation for optimal implementation of VR-BCI based interventions that associate MI and MO, optimizing cortical activity during the intervention, patients’ engagement and clinical outcomes. Future research should explore the application of these guidelines for validation and investigate BCI’s efficacy according to different combinations of patients’ profiles, task characteristics and technology features.