Sensorimotor Rhythm-Brain Computer Interface With Audio-Cue, Motor Observation and Multisensory Feedback for Upper-Limb Stroke Rehabilitation: A Controlled Study.

Xin Li,Lu Wang,Si Miao,Zan Yue,Liujie Su,Zulin Dou,Jing Wang,Yadan Zheng,Xiangzhen Wu,Zhiming Tang,Shan Wang

doi:10.3389/fnins.2022.808830

Abstract

Several studies have shown the positive clinical effect of brain computer interface (BCI) training for stroke rehabilitation. This study investigated the efficacy of the sensorimotor rhythm (SMR)-based BCI with audio-cue, motor observation and multisensory feedback for post-stroke rehabilitation. Furthermore, we discussed the interaction between training intensity and training duration in BCI training. Twenty-four stroke patients with severe upper limb (UL) motor deficits were randomly assigned to two groups: 2-week SMR-BCI training combined with conventional treatment (BCI Group, BG, n = 12) and 2-week conventional treatment without SMR-BCI intervention (Control Group, CG, n = 12). Motor function was measured using clinical measurement scales, including Fugl-Meyer Assessment-Upper Extremities (FMA-UE; primary outcome measure), Wolf Motor Functional Test (WMFT), and Modified Barthel Index (MBI), at baseline (Week 0), post-intervention (Week 2), and follow-up week (Week 4). EEG data from patients allocated to the BG was recorded at Week 0 and Week 2 and quantified by mu suppression means event-related desynchronization (ERD) in mu rhythm (8–12 Hz). All functional assessment scores (FMA-UE, WMFT, and MBI) significantly improved at Week 2 for both groups (p < 0.05). The BG had significantly higher FMA-UE and WMFT improvement at Week 4 compared to the CG. The mu suppression of bilateral hemisphere both had a positive trend with the motor function scores at Week 2. This study proposes a new effective SMR-BCI system and demonstrates that the SMR-BCI training with audio-cue, motor observation and multisensory feedback, together with conventional therapy may promote long-lasting UL motor improvement.Clinical Trial Registration: [http://www.chictr.org.cn], identifier [ChiCTR2000041119].

Highlights

Stroke is a leading cause of mortality and disability worldwide (Johnson et al, 2019; Zhou et al, 2019)
This study investigated the efficacy of the sensorimotor rhythm (SMR)-based brain computer interface (BCI) with audio-cue, motor observation and multisensory feedback for post-stroke rehabilitation
This study presents the results from a clinical study investigating the efficacy of the SMR-BCI with audio-cue, motor observation, and multisensory feedback compared with conventional therapy for upper limb stroke rehabilitation

Summary

Introduction

Stroke is a leading cause of mortality and disability worldwide (Johnson et al, 2019; Zhou et al, 2019). Up to 66% of stroke survivors experience upper limb (UL) motor impairments, which result in functional limitations in activities of daily living and decreased life quality (Kwah et al, 2013; Morris et al, 2013). Electroencephalography (EEG)-based sensorimotor rhythm (SMR) brain computer interface (BCI) is a novel technology that can enhance activity-dependent neuroplasticity and restore motor function for stroke survivors (Ang et al, 2014a; Lazarou et al, 2018; Jeunet et al, 2019). Task-related modulation in EEG-based SMRs is usually manifested as event-related desynchronization (ERD) or event-related synchronization (ERS) in low-frequency components [mu rhythm (8–12 Hz) and beta rhythm (13– 26 Hz)] (Pfurtscheller and Lopes da Silva, 1999), which forms the basis of neural control in EEG-based SMR-BCI (Yuan and He, 2014). Patients with stroke or spinal cord lesions can control physical or virtual devices via SMR-BCI (Prasad et al, 2010; Caria et al, 2011; Ang et al, 2014a,b; Dodakian et al, 2014; McCrimmon et al, 2014; Ono et al, 2014; Yuan and He, 2014; Ang and Guan, 2015; Bartur et al, 2015; Pichiorri et al, 2015; Zich et al, 2015; Shu et al, 2017, 2018; Barsotti et al, 2018; Biasiucci et al, 2018; Lazarou et al, 2018; Lee et al, 2018; Norman et al, 2018; Jeunet et al, 2019; Song and Kim, 2019; Chen et al, 2020; Foong et al, 2020), which raises the possibility of SMR-BCI training for stroke rehabilitation

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Discussion

Conclusion