Predicted Decreased Sensorimotor Rhythm Regulation by Increased Heart Rate Variability - Duc Truong Than (Drugs and Cell Therapies in Hematology, 2021)
Sensorimotor rhythms (SMR, 8-12 Hz) may be controlled voluntarily, which can be utilized to operate an artificial hand exoskeleton via a brain-computer interface (BCI), for example, in the case of finger paralysis following a stroke. Stroke survivors are typically encouraged to participate in motor imagining (MI) or to attempt moving the paralyzed fingers, resulting in the task- or event-related desynchronization (ERD) of SMR and the regaining of SMR control (SMR-ERD). BCI control ability might degrade significantly with time due to the cognitive demands of these activities, which is especially true for stroke patients who are suffering from cognitive deficits. It would thus be necessary to find biomarkers that indicate a reduction in BCI control performance during a current session to optimize the man-machine interface scheme in the future. This study aims to investigate the relationship between BCI control performance over time and heart rate variability (HRV). We explored whether HRV could be utilized as a biomarker to predict deterioration during voluntary control of SMR-ERD in 17 healthy volunteers by applying Granger causality to the data. On a computer screen, SMR-ERD was visibly presented. During two consecutive runs of 8.5 minutes each, the participants were directed to engage in MI-based SMR-ERD control exercises. During the second run, the complexity of the job was incrementally raised. While control performance (p = 0.18) and heart rate variability (p = 0.16) were identical among individuals throughout the first run, both measures deteriorated gradually at high correlation during the second run (performance: -0.61%/10s, p = 0; HRV: -0.007ms/10s, p.001). A significant correlation was established between HRV Granger-induced BCI control performance and predictive features of HRV at the individual participant level (p.001). It appears that HRV can anticipate a reduction in BCI performance, opening the door to adaptive BCI control paradigms, such as those used to individualize and improve assistive BCI systems in stroke patients, among other applications.