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Combining non-invasive monitoring of action-related brain signals with the invasive recordings of the nerve motor output could provide robust natural and bidirectional multimodal Brain-Machine interfaces. One 26 years old, right-handed male who had suffered traumatic trans-radial amputation of the left arm was connected in a bidirectional way with a robotic hand prostheses. Cortical signals related...
Deep brain stimulation is an increasingly prevalent surgical option in the treatment of a multitude of neurological conditions, most notably Parkinson's disease. The development of a neurofeedback device is driven primarily by stimulator habituation, surgical risk factors, the cost of battery replacement, and reported neuropsychiatric side-effects under prolonged chronic administration. Here we present...
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...
In this study, we target to automatically detect behavioral patterns of patients with autism. Many stereotypical behavioral patterns may hinder their learning ability as a child and patterns such as self-injurious behaviors (SIB) can lead to critical damages or wounds as they tend to repeatedly harm one single location. Our custom designed accelerometer based wearable sensor can be placed at various...
A real-time method using only accelerometer data is developed for classifying basic human static postures, namely sitting, standing, and lying, as well as dynamic transitions between them. The algorithm uses discrete wavelet transform (DWT) in combination with a fuzzy logic inference system (FIS). Data from a single three-axis accelerometer integrated into a wearable headband is transmitted wirelessly,...
This paper describes an approach for the real-time detection of stumble for use in an intelligent lower limb prosthesis, using accelerometers mounted on the prosthesis, and also describes an algorithm that classifies the stumble response as either an elevating or lowering type response. In order to validate the proposed approach, the investigators collected stumble data on 10 healthy subjects using...
Electrocardiographic T wave peak-to-end interval (TpTe) is one parameter of T wave morphology, which contains indicators for hypoglycaemia. This paper shows the corrected TpTe (TpTec) interval as one of the inputs contributing to detect hypoglycaemia. Support vector machine (SVM) and fuzzy support vector machine (FSVM) utilizing radial basis function (RBF) are used as the classification methods in...
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...
The analgesic effect of morphine is highly individual, calling for objective methods to predict the subjective pain relief. Such methods might be based on alteration of brain response caused by morphine during painful stimuli. The study included 11 healthy volunteers subjectively quantifying perception of painful electrical stimulations in the esophagus. Brain evoked potentials following stimulations...
The current work describes a methodology to automatically detect the severity of bradykinesia in motor disease patients using wireless, wearable accelerometers. This methodology was tested with cross validation through a sample of 20 Parkinson's disease patients. The assessment of methodology was carried out through some daily living activities which were detected using an activity recognition algorithm...
It has been demonstrated that negative emotions have adverse effects on the immune system of a person. This contributes to increased morbidity and mortality in the elderly population and has a direct impact on quality of life. Positive emotions on the other hand may not only undo the harmful effects of negative emotions but also protect against certain diseases. Hence the use of technology to facilitate...
In this paper, we present a method for extracting footfall locations from three dimensional voxel data created from a pair of silhouettes. With the growth of the elderly population, there is a need for passive monitoring of physical activity to allow older adults to continue living in independent settings. Prior research using anonymized video data has shown good results in passively acquiring information...
Currently, the best way to reduce the mortality of cancer is to detect and treat it in its early stages. Automatic decision support systems, such as automatic diagnosis systems, are very helpful in this task but their performance is constrained by the integrity of the clinical input data. This could be a problem since clinical databases, in which these systems are based on, are commonly built up containing...
Practical issues such as accuracy with various subjects, number of sensors, and time for training are important problems of existing brain-computer interface (BCI) systems. In this paper, we propose a hybrid framework for the BCI system that can make machine control more practical. The electrooculogram (EOG) is employed to control the machine in the left and right directions while the electroencephalogram...
An algorithm to detect automatically drowsiness episodes has been developed. It uses only one EEG channel to differentiate the stages of alertness and drowsiness. In this work the vectors features are building combining Power Spectral Density (PDS) and Wavelet Transform (WT). The feature extracted from the PSD of EEG signal are: Central frequency, the First Quartile Frequency, the Maximum Frequency,...
Vertical ground reaction force (vGRF) has been commonly used in human gait analysis making possible the study of mechanical overloads in the locomotor system. This study aimed at applying the principal component (PC) analysis and two Artificial Neural Networks (ANN), multi-layer feed forward (FF) and self organized maps (SOM), for classifying and clustering gait patterns from normal subjects (CG)...
This paper presents a new application of the Particle Swarm Optimization (PSO) algorithm to optimize Mel Frequency Cepstrum Coefficients (MFCC) parameters, in order to extract an optimal feature set for diagnosis of hypothyroidism in infants using Multi-Layer Perceptrons (MLP) neural network. MFCC features is influenced by the number of filter banks (fb) and the number of coefficients (nc) used. These...
Different biological labs conduct similar experiments on same diseases. It is highly desirable to have a better model based on more experimental results than that on a single result. In this paper, we propose a method for integrating microarray data from multiple sources for building classification models. To test the method, we use three real world microarray data sets from different labs with different...
A current problem in deoxyribonucleic acid (DNA) sequence analysis is to determine the exact locations of the genes and also in eukaryotes, the protein-coding regions in the mRNA primary transcript (pre-mRNA).The conversion into discrete numerical values of the symbols associated to the nucleotides of these sequences allows for a signal to address the problems related to localization and annotation...
Summary form only given. An overview is presented of different studies on monitoring and detection of drowsiness and microsleep (MS)during driving simulation. At first a framework is presented how to utilize methods of pattern recognition and of computational intelligence in order to detect and to predict MS. Secondly, different biosignals are compared due to their value for MS detection. Data fusion...
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