Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
Visuomotor discordance in virtual reality: effects on online motor control.
Virtual reality (VR) applications are rapidly permeating fields such as medicine, rehabilitation, research, and military training. However, VR-induced effects on human performance remain poorly understood, particularly in relation to fine-grained motor control of the hand and fingers. We designed a novel virtual reality environment suitable for hand-finger interactions and examined the ability to use visual feedback manipulations in VR to affect online motor performance. ⋯ The latency of these modifications was similar across conditions. These findings demonstrate that a VR-based platform may be a robust medium for presenting visuomotor discordances to engender a sense of ownership and drive sensorimotor adaptation for (retraining motor skills. This may prove to be particularly important for retraining motor skills in patients with neurologically-based movement disorders.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
Service oriented architecture to support real-time implementation of artifact detection in critical care monitoring.
The quality of automated real-time critical care monitoring is impacted by the degree of signal artifact present in clinical data. This is further complicated when different clinical rules applied for disease detection require source data at different frequencies and different signal quality. ⋯ The framework is instantiated through a Neonatal Intensive Care case study which assesses signal quality of physiological data streams prior to detection of late-onset neonatal sepsis. In this case study requirements and provisions of artifact and clinical event detection are determined for real-time clinical implementation, which forms the second important contribution of this paper.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
Biometric and mobile gait analysis for early diagnosis and therapy monitoring in Parkinson's disease.
Parkinson's disease (PD) is the most frequent neurodegenerative movement disorder. Early diagnosis and effective therapy monitoring is an important prerequisite to treat patients and reduce health care costs. Objective and non-invasive assessment strategies are an urgent need in order to achieve this goal. ⋯ The presented system is able to classify patients and controls (for early diagnosis) with a sensitivity of 88% and a specificity of 86%. In addition it is possible to distinguish mild from severe gait impairment (for therapy monitoring) with 100% sensitivity and 100% specificity. This system may be able to objectively classify PD gait patterns providing important and complementary information for patients, caregivers and therapists.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
Phase-based measures of cross-frequency coupling in brain electrical dynamics under general anesthesia.
The state of general anesthesia (GA) is associated with an increase in spectral power in scalp electroencephalogram (EEG) at frequencies below 40 Hz, including spectral peaks in the slow oscillation (SO, 0.1-1 Hz) and α (8-14 Hz) bands. Because conventional power spectral analyses are insensitive to possible cross-frequency coupling, the relationships among the oscillations at different frequencies remain largely unexplored. Quantifying such coupling is essential for improving clinical monitoring of anesthesia and understanding the neuroscience of this brain state. ⋯ The waking and two distinct states under GA could be discriminated by projecting in a two-dimensional phase space defined by the SynchFastSlow and the preferred SO phase of α activity. Our results show that a stereotyped pattern of phase-amplitude coupling accompanies multiple stages of anesthetic-induced unconsciousness. These findings suggest that modulogram analysis can improve EEG based monitoring of brain state under GA.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2011
iSyNCC: an intelligent system for patient monitoring & clinical decision support in Neuro-Critical-Care.
Close monitoring and timely treatment are extremely crucial in Neuro Intensive/Critical Care Units (NICUs) to prevent patients from secondary brain damages. However, the current clinical practice is labor-intensive, prone to human errors and ineffective. ⋯ The requirements of the system were investigated through interviews and discussions with neurosurgeons, neuroclinicians and nurses. Based on the summarized requirements, a modular 2-tier system is developed. iSyNCC integrates and stores crucial patient information ranging from demographic details, clinical & treatment records to continuous physiological monitoring data. iSyNCC enables remote and centralized patient monitoring and provides computational intelligence to facilitate clinical decision makings.