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A signal quality classification algorithm is presented to evaluate signal quality in ambulatory monitoring system. Acoustic based signal is classified as good signal, weak signal or noisy signal. Certain features in the acquired signal are extracted and analyzed to differentiate the class of signal quality. With this classification, wrong physiological estimation due to poor signal quality can be...
Cochlear implant patients often complain about their difficulty in understanding speech in noisy environments. Currently a fixed noise suppression algorithm is used in cochlear implants regardless of the characteristics of the speech or noise environment. Access to an intelligent mechanism to determine the noise environment on-the-fly in order to automatically switch between different noise suppression...
A system for diagnosing health problems from gait patterns of elderly to support their independent living is proposed in this paper. Motion capture system, which consists of tags attached to the body and sensors situated in the apartment, is used to capture gait of elderly. Position of the tags is acquired by the sensors and the resulting time series of position coordinates are analyzed with machine...
Due to the artifacts in electroencephalography (EEG) data, the performance of brain-computer interface (BCI) is degraded. On the other hand, in the motor imagery based BCI system, EEG signals are usually contaminated by the misleading trials caused by improper imagination of a movement. In this paper, we present a novel algorithm to detect the abnormal EEG data using genetic algorithm (GA). After...
A novel method for screening obstructive sleep apnea syndrome (OSAs) based on nocturnal acoustic signal is proposed. Full-night audio signals from sixty subjects were segmented into snore, noise and silence events using semi-automatic algorithm based on Gaussian mixture models which achieves more than 90% (92%) sensitivity (specificity) and produces an average of 2,000 snores per subject. A classification...
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