On the role of visual feedback and physiotherapist-patient interaction in robot-assisted gait training: an eye-tracking and HD-EEG study

Abstract

Abstract Background Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor training to help the patient achieve a physiological gait pattern, reducing the physical effort required by therapist. By introducing the robot as a third agent to the traditional one-to-one physiotherapist-patient (Pht-Pt) relationship, the therapist might not be fully aware of the patient’s motor performance. This gap has been bridged by the integration in rehabilitation robots of a visual FeedBack (FB) that informs about patient’s performance. Despite the recognized importance of FB in t-RAGT, the optimal role of the therapist in the complex patient-robot interaction is still unclear. This study aimed to describe whether the type of FB combined with different modalities of Pht’s interaction toward Pt would affect the patients’ visual attention and emotional engagement during t-RAGT. Methods Ten individuals with incomplete Spinal Cord Injury (C or D ASIA Impairment Scale level) were assessed using eye-tracking (ET) and high-density EEG during seven t-RAGT sessions with Lokomat where (i) three types of visual FB (chart, emoticon and game) and (ii) three levels of Pht-Pt interaction (low, medium and high) were randomly combined. ET metrics (fixations and saccades) were extracted for each of the three defined areas of interest (AoI) (monitor, Pht and surrounding) and compared among the different experimental conditions (FB, Pht-Pt interaction level). The EEG spectral activations in theta and alpha bands were reconstructed for each FB type applying Welch periodogram to data localised in the whole grey matter volume using sLORETA. Results We found an effect of FB type factor on all the ET metrics computed in the three AoIs while the factor Pht-Pt interaction level also combined with FB type showed an effect only on the ET metrics calculated in Pht and surrounding AoIs. Neural activation in brain regions crucial for social cognition resulted for high Pht-Pt interaction level, while activation of the insula was found during low interaction, independently on the FB used. Conclusions The type of FB and the way in which Pht supports the patients both have a strong impact on patients’ engagement and should be considered in the design of a t-RAGT-based rehabilitation session.

Keywords

• Robot-assisted gait training
• Spinal cord injury
• Visual feedback
• EEG
• Eye-tracking