Heart rate variability predicts decline in sensorimotor rhythm control.

Objective.Voluntary control of sensorimotor rhythms (SMRs, 8-12 Hz) can be used for brain-computer interface (BCI)-based operation of an assistive hand exoskeleton, e.g. in finger paralysis after stroke. To gain SMR control, stroke survivors are usually instructed to engage in motor imagery (MI) or to attempt moving the paralyzed fingers resulting in task- or event-related desynchronization (ERD) of SMR (SMR-ERD). However, as these tasks are cognitively demanding, especially for stroke survivors suffering from cognitive impairments, BCI control performance can deteriorate considerably over time. Therefore, it would be important to identify biomarkers that predict decline in BCI control performance within an ongoing session in order to optimize the man-machine interaction scheme.Approach.Here we determine the link between BCI control performance over time and heart rate variability (HRV). Specifically, we investigated whether HRV can be used as a biomarker to predict decline of SMR-ERD control across 17 healthy participants using Granger causality. SMR-ERD was visually displayed on a screen. Participants were instructed to engage in MI-based SMR-ERD control over two consecutive runs of 8.5 min each. During the 2nd run, task difficulty was gradually increased.Main results.While control performance (p= .18) and HRV (p= .16) remained unchanged across participants during the 1st run, during the 2nd run, both measures declined over time at high correlation (performance: -0.61%/10 s,p= 0; HRV: -0.007 ms/10 s,p< .001). We found that HRV exhibited predictive characteristics with regard to within-session BCI control performance on an individual participant level (p< .001).Significance.These results suggest that HRV can predict decline in BCI performance paving the way for adaptive BCI control paradigms, e.g. to individualize and optimize assistive BCI systems in stroke.

Development of a multichannel current-EMG system for coherence modulation with visual biofeedback.

By means of biofeedback, neuromotor control can be modified. Recent biofeedback experiments have used the power of the electromyogram of one muscle in different frequency bands to control a two-dimensional cursor. However, the human body usually requires coherent activation of multiple muscles to achieve daily life tasks. Additionally, electromyography (EMG) instrumentation has remained the same for decades, and might not be the most suitable to measure coherent activations from pennated muscles according to recent experiments by von Tscharner and colleagues. In this study, we propose the development of a multichannel current-based EMG amplifier to use intermuscular coherence as the control feature of a visual biofeedback system. The system was used in a leg extension protocol to voluntarily increase intermuscular coherence between the vastii muscles. Results from ten subjects show that it is possible to increase intermuscular coherence through visual biofeedback. Such a system can have applications in endurance training and rehabilitation.