Abstract
ObjectiveThe aim of this study was to determine the EEG changes induced by emotional non-verbal sounds using nonlinear signals' features and also to examine the subjective emotional response in patients with different neurological and psychiatric disorders.Methods141 subjects participated in our study: patients after moderate TBI, patients in acute coma, patients after stroke, patients with schizophrenia and controls. 7 types of emotionally charged stimuli were presented. Non-comatose participants were asked to assess the levels of experienced emotions. We analyzed fractal dimension, signal's envelope parameters and Hjorth mobility and complexity.ResultsThe Hjorth parameters were negatively correlated with irritation. The fractal dimension was positively correlated with arousal and empathy levels. The only presentation of laughter to post-stroke patients induced the reaction similar to the control group.ConclusionsThe results showed that the investigated nonlinear features of resting state EEG are quite group-specific and also specific to the emotional state.SignificanceThe investigated features could serve to diagnose emotional impairments.
Highlights
In this study we examined a set of time-domain and nonlinear features of EEG signal in patients with different neurological and psychiatric disorders
5 groups of adult subjects participated in our study (N = 141): healthy, patients after moderate TBI, patients in acute coma, patients after stroke in the left middle cerebral artery and patients with schizophrenia
Comatose patients had higher 2–7 Hz PSD compared to other groups of subjects (F(4, 141) = 8.928, p < 0.00001) in all electrodes
Summary
In this study we examined a set of time-domain and nonlinear features of EEG signal in patients with different neurological and psychiatric disorders. To show the effectiveness of these features to diagnose a concussion, in an approach similar to power analysis, the features can be calculated for both usual EEG frequency bands (rhythms) and individual EEG frequencies (2-Hz wide bands). This method came from a study on concussed athletes [2]. The investigated signal features: time domain Hjorth parameters, approximate entropy, and the Hurst exponent, didn’t differ between the groups of the athletes and their healthy peers if calculated in the rhythm-band filtered case but they did differ in the narrow-band filtered case
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
