neurobiofeedback (NBF)
Research Papers
EEG-NeuroBioFeedback Treatment of Patients with Brain Injury Part 4: Duration of Treatments as a Function of Both the Initial Load of Clinical Symptoms and the Rate of Rehabilitation
Background. Twenty-seven patients with brain injury, primarily from car accidents and stroke, were treated by computer-assisted electroencephalographic NeuroBioFeedback (EEG-NBF). Methods. Patients were distributed into five clinical classes, and changes in power spectra and in cardiovascular parameters were surveyed. A rationale was proposed for the calculation of the load of symptoms for each patient of each class, which in turn provided indices of rehabilitation rates. Results. Statistically significant correlations were observed between the number of NeuroBioFeedback (NBF) treatment sessions (SN#) needed and both the initial load of symptoms (SL%) and the final rate of improvement of patients' clinical status (IMP%). When patients were considered in all five classes of defined SL%, the relationship exhibited a hyperbolic shape, although linearity could not be totally rejected, due to the variability of data. The improvement rates could be subdivided into two major classes, in which number (SN#) was hyperbolically related to the improvement rates. In addition, finger temperature responsiveness exhibited a significant correlation with the number of NBF sessions. Conclusion. The work suggests a rationale for the prediction of the duration of treatment, by considering the patients' initial clinical status and the levels of improvement and rehabilitation considered achievable.
View Full Paper →EEG-NeuroBioFeedback Treatment of Patients with Brain Injury: Part 1: Typological Classification of Clinical Syndromes
Background. A group of 27 patients with brain injury were treated by electroencephalographic (EEG) NeuroBioFeedback under drug-free conditions. They were studied for distribution in classes of major syndromes for evaluation of treatment efficiency and rehabilitation rates with respect to associated EEG and other physiological changes. Methods. A total of 48 clinical symptoms were listed, each present in at least one patient. Classes of clinical signs have been computed using both medical and statistical criteria. Claimed and presented chief complaints, secondary complaints and all associated signs were incorporated in multivariate analysis. Results. Substantial intersection of medical and statistical distributions was observed. This provided a classification of symptoms into six classes representing the following syndromes of impaired functions: Q1 = motor; Q2 = language; Q3 = cognitive; Q4 = psychosocial; Q5 = pain-related; Q6(a & b) = neuropsychiatric; Q7 = metabolic. Membership of a patient in a defined clinical class was based on a numerical index computed from: (a) a weighted coefficient for the patient's chief and secondary complaints, and (b) an index for both symptoms represented in the class and symptoms not represented in the class. Patients were unambiguously distributed in all classes except Q7. Conclusions. Using anon-selected group of head injured patients, this work provides a rationale for the membership of each patient in a set of classes of syndromes determined by the whole set of clinical signs specifically exhibited by this group of patients. Class-average rehabilitation rates ranged from 59% up to 87% following an average 23 to 132 treatment sessions, depending on syndromes.
View Full Paper →EEG-NeuroBioFeedback Treatment of Patients with Brain Injury: Part 2: Changes in EEG Parameters versus Rehabilitation
Background. A sample of 27 patients with brain injury distributed in five clinical classes was examined for pre- and post-treatment symptoms and associated power spectra. Methods. Changes in electroencephalographic (EEG) compressed spectral arrays were analyzed with respect to the rate of rehabilitation and correlated with a checklist of symptoms for each patient and the group as a whole. Results. Targeted decreases in slower (3–7 Hz) and higher (24–32 Hz) frequencies, and EMG (70–90 Hz), and increases of alpha (8–12 Hz) and mid-range beta frequencies (15–18 Hz) were achieved following Neuro-BioFeedback (NBF) treatment using positive reward tones and a simultaneous visual reward. The impact of gender and age class influence was assessed against treatment results. Single lead EEG power spectra changes were analyzed for hemispherectomized patients, stroke, car accident and trauma patients. A common EEG pattern was observed for a group of patients exhibiting vertigo with two subgroups in which vertigo resolved or did not resolve showing EEG differences. Conclusions. EEG NeuroBioFeedback can successfully treat patients with brain injury with highly clinically-meaningful clinical results. Changes in Cz power spectra generally occur, but do not always immediately follow resolution of symptoms. Since EEG-NBF is limited to recording cortical surface potentials, it is possible that changes induced by the treatment which result in clinical changes may not always be reflected at the cortical surface and hence may not be available for recording and analysis there, despite subcortical integration.
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