Delta-alpha ratio correlates with level of recovery after neurorehabilitation in patients with acquired brain injury
ABSTRACT To explore the relationship between three QEEG global indexes and their association with functional outcome after neurorehabilitation in non-acute acquired brain injury (ABI) patients (traumatic brain injury and stroke).
Twenty-one adult ABI patients in post-acute phase were studied. Delta-alpha ratio (DAR), Power Ratio Index (PRI) and Mean Brain Symmetry Index (mBSI) were calculated from resting-state EEG taken at admission. These indexes and other clinical variables were correlated with functional recovery achieved after six months of neurorehabilitation.
DAR showed the highest strength of association with the functional outcome measure (rho=-0.65, P=0.002). The other QEEG indexes and clinical variables showed modest non-significant correlations. A posteriori group analysis showed higher DAR in patients with poor recovery as compared to good recovery patients.
Functional recovery after neurorehabilitation appears to be associated with a number of clinical and neurophysiological variables. Among the latter, the ratio between delta and alpha may play a significant role in predicting and monitoring functional rehabilitation outcome.
Neurophysiological assessment of ABI patients may be an important tool in monitoring and predicting outcomes after neurorehabilitation.
- SourceAvailable from: Umberto Leon-Dominguez
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- "Details on the exact EEG analysis procedure are given elsewhere  . "
ABSTRACT: The design of neurorehabilitation therapy to treat subjects with altered consciousness provides opportunities and challenges to professionals involved with the care for these severely ill patients. While there is an increased interest in determining methods to restore consciousness in these patients, the process is complex and challenging, due in part to the diverse aetiology of these states of consciousness, and also to the intricate cerebral connectivity involved in their treatment. The present case study examines a patient who showed signs of emergence from the vegetative state after neurorehabilitation using The Combined Method Therapy (CMT). In this case, neurorehabilitation therapy was applied simultaneously with pharmacological treatment, stimulation, and neuroimaging techniques to help adjust drug dosage. The results of this study suggest that this combined approach to treatment promoted connectivity among posterior and anterior cortical regions aiding emergence from the vegetative state.Current pharmaceutical design 09/2013; DOI:10.2174/13816128113196660651 · 3.29 Impact Factor
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- "New embedded technologies are making possible the increased monitoring of daily life activities (Participation) –. Advances in brain imaging are improving monitoring options of relevant brain activation patterns (Health Condition) –. However, there does not exist a framework for integrating the outcomes of these measuring instruments into a holistic assessment of the effect of a chosen movement therapy on a patient. "
ABSTRACT: New motion capture technologies are allowing detailed, precise and complete monitoring of movement through real-time kinematic analysis. However, a clinically relevant understanding of movement impairment through kinematic analysis requires the development of computational models that integrate clinical expertise in the weighing of the kinematic parameters. The resulting kinematics based measures of movement impairment would further need to be integrated with existing clinical measures of activity disability. This is a challenging process requiring computational solutions that can extract correlations within and between three diverse data sets: human driven assessment of body function, kinematic based assessment of movement impairment and human driven assessment of activity. We propose to identify and characterize different sensorimotor control strategies used by normal individuals and by hemiparetic stroke survivors acquiring a skilled motor task. We will use novel quantitative approaches to further our understanding of how human motor function is coupled to multiple and simultaneous modes of feedback. The experiments rely on a novel interactive tasks environment developed by our team in which subjects are provided with rich auditory and visual feedback of movement variables to drive motor learning. Our proposed research will result in a computational framework for applying virtual information to assist motor learning for complex tasks that require coupling of proprioception, vision audio and haptic cues. We shall use the framework to devise a computational tool to assist with therapy of stroke survivors. This tool will utilize extracted relationships in a pre-clinical setting to generate effective and customized rehabilitation strategies.Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:1399-402. DOI:10.1109/IEMBS.2011.6090329
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- "Research on the resting EEG has found lower magnitudes with higher frequencies for patients in MC compared to patients with severe neurocognitive but intact consciousness. Similarly the delta-alpha ratio correlates with the level of recovery after neurorehabilitation (Leon-Carrion et al., 2009). As the alpha rhythm (8-12 Hz) is considered to be strongly related to attention and alertness, differential responses in the alpha range to deviant stimuli can be expected. "
ABSTRACT: Disorders of consciousness were amply studied in the recent years. At this regards new methodologies and technologies were applied to explore the diagnostic and prognostic criteria that may be applied to the patients. Specifically electrophysiological measures were used to verify the degree of awareness and responsiveness in coma, vegetative states (VS), minimal consciousness state (MC), and locked-in syndrome (LI). Recently, ERPs (event-related potentials) were adopted to integrate the classical neuroimaging measures. Between the others, MMN (mismatch negativity) and P300 deflections were found to represent a consistent index of the present state of consciousness and to be predictive of successive modifications of this state. Also frequency-based EEG measures, such as brain oscillations, were revealed to be relevant marker of consciousness and awareness, able to predict the future evolution of pathology.