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An assistive technology developed for "hands free" control of electrical devices to be used by severely impaired people within their environment, relies upon using signal processing techniques for analyzing eyes closed (EC) and eyes open (EO) states in the electroencephalography (EEG) signal. Here, we apply a signal processing technique used in continuous chaotic modeling to investigate differences in the EEG time series between EC and EO states. This method is used to detect the degree of variability from a second-order difference plot, and quantifying this using a central tendency measures. The study used EEG time series of EO and EC states from 33 able-bodied and 17 spinal cord injured participants. The results found an increased EEG variability in brain activity during EC compared to EO. This increased EEG variability occurred in the O2 electrode, which overlays the primary visual cortex V1, and could be a result of the replacement of the coherent information obtained during EO by noise. A continuous measure of the variability was then used to demonstrate that this technique has the potential to be used as a switching mechanism for assistive technologies. [ABSTRACT FROM AUTHOR]

Abstract: We perform an analysis of cardiac data using multiscale entropy as proposed in Costa et al. [Multiscale entropy analysis of complex physiological time series, Phys. Rev. Lett. 89 (2002) 068102]. We reproduce the signatures of the multiscale entropy for the three cases of young healthy hearts, atrial fibrillation and congestive heart failure. We show that one has to be cautious how to interpret these signatures in terms of the underlying dynamics. In particular, we show that different dynamical systems can exhibit the same signatures depending on the sampling time, and that similar systems may have different signatures depending on the time scales involved. Besides the total amount of data we identify the sampling time, the correlation time and the period of possible nonlinear oscillations as important time scales which have to be involved in a detailed analysis of the signatures of multiscale entropies. We illustrate our ideas with the Lorenz equation as a simple deterministic chaotic system. [Copyright &y& Elsevier]

Research and development has been conducted on a "hands-free" brain wave activity (electroencephalography-based) assistive technology device called the Mind Switch. It has been designed to provide a severely disabled person (such as someone with tetraplegia) with the ability to switch using their brain activity and thus activate devices in the environment. An area of concern has been the time it takes to complete set-up of the system before individual use, as well as the occurrence of errors in switching rates. In order to improve the user friendliness of the system, this study compared the efficacy of detecting electroencephalography (EEG) changes in brain signals that occur with eye closure and used as a "switch", with two different methods of processing the EEG. Using data from spinal cord injured participants, fractal analysis, that is, the change in fractal dimension of the EEG wave during eye closure was compared to the original method of using spectral analysis change. In comparison to the spectral technique, the fractal dimension technique improved set up time, and was substantially improved in reducing the number of false positive and false negative errors when activating the device. Furthermore, the time to switch was also marginally reduced when using fractal dimension processing. Implications for improving the viability of an EEG based environmental control system for the severely neurologically injured are discussed. [ABSTRACT FROM AUTHOR]

Traumatic injuries can have long-term negative impacts on health, especially psychological health. A biopsychosocial approach is recommended to identify those likely to experience psychosocial stress, however large individual differences exist in stress reactivity and post-injury health that remain unexplored. Therefore, we investigated autonomic nervous system (ANS) stress responses and pre-existing psychosocial vulnerability as contributors to health in individuals who sustained a traffic-related injury. 120 adults with traffic-related injury and 112 non-injury controls underwent an integrative ANS (cardiac and skin conductance) assessment and a health-related assessment at 3–6 weeks post-injury. Propensity score matching based on six pre-injury psychosocial vulnerability factors (age, sex, education, prior mental/physical health, socioeconomic status) guided the definition of high vulnerability (HV) and low vulnerability (LV) injury subgroups, with the LV subgroup having similar propensity scores to non-injury controls. A three-group comparative analysis of ANS responsivity (baseline, reactivity, recovery/rebound) and post-injury health was performed. The HV subgroup exhibited the most negative immediate post-injury mental health profile and less adaptive ANS response patterns, indicating greater stress vulnerability/reactivity. Significant differences were found for psychological health (elevated psychological distress and catastrophizing), but not physical health (injury factors, pain, fatigue, physical wellbeing). HV participants showed sympathetic predominance at resting baseline (lower parasympathetic activity and/or elevated heart rate) compared to the LV and control groups, as well as smaller parasympathetic decrease during a cognitive task compared to controls. Despite preserved capacity for restoring initial homeostasis in both injury subgroups during recovery, there was some indication of blunted post-task sympathetic deactivation (larger sympathetic decrease) and reduced overall ANS adaptability (reduction in total power of heart rate variability spectrum), suggesting relative reduced capacity to face stressors compared to controls. Findings suggest that baseline resting ANS regulation, particularly parasympathetic activity, and pre-injury psychosocial factors are key contributors to individual psycho-biological responses following traumatic injury, and are therefore potential stress vulnerability markers. Post-stress recovery patterns may represent a novel physiological signature for a "biological intrinsic" vulnerability early after the injury. These findings provide direction for improved early identification and management of injured individuals, including innovative preventive interventions that target ANS regulation. • Resting autonomic regulation and pre-injury vulnerability were associated with psychological adjustment to traumatic injury. • Individuals with higher pre-injury vulnerability exhibited less adaptive psycho-biological responses to the injury. • Autonomic recovery patterns suggested a reduced capacity to deal with stressors immediately post-injury. [ABSTRACT FROM AUTHOR]