Brain computer interface (BCI) system for restoration of hand function for stroke rehabilitation and EEG analysis using fuzzy approximate entropy (fApEn)

Ph.D. ; Motor Observation (MO), a mental practise of movement, activates brain structures usually involved in planning and execution of movements. Based on the mechanism of MO, a brain computer interface-based motor observation (BCI-MO) intervention was designed to facilitate functional recovery of the hand in stroke subjects. Eleven chronic stroke and nine unimpaired subjects were recruited to validated training effectiveness of this intervention. Three clinical scales, Fugl-Meyer Assessment-Upper Limb (FMAUL), Action Research Arm Test (ARAT), and Wolf Motor Function Test (WMFT), were used to compare the motor function of hand at pre- and post-training. Entropy-based algorithms have been suggested as robust estimators of electroencephalography (EEG) predictability or regularity which may elucidate the pathophysiological mechanisms in chronic stroke. Fuzzy approximate entropy (fApEn), a novel entropy-based algorithm designed to evaluate complexity in physiological systems, was applied to assess the EEG signals acquired from healthy and stroke subjects at pre- and post-training. Frequency band power, suppression, EEG topography, and time-frequency maps were also used in this study as complementary techniques to EEG fApEn. ; The results showed that, before training, stroke subjects had significantly lower EEG fApEn than unimpaired subjects (p < 0.05) in the motor cortical area of the brain (C3,C4, FC3, FC4, CP3, and CP4), in both hemispheres. However, after training, motor function of the paretic upper limb, assessed by FMA-UL, ARAT, and WMFT, improved significantly (p < 0.05) in stroke subjects. Furthermore, after training, the EEG fApEn in the stroke subjects increased considerably in the central area of the contralesional hemisphere (p < 0.05). A significant correlation was noted between clinical scales (FMA-UL, ARAT, and WMFT) and EEG fApEn in C3/C4 in the 5 contralesional hemisphere (p < 0.05). This finding suggests that the increase in EEG fApEn and higher complexity in the brain could be an ...