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A vast researches are concentrated towards the development of EEG based human computer interface to enhance the quality of life for medical applications. There is a recent attraction to wireless EEG devices as they are cheaper and easily available in the market. The devices use dry electrodes and send signals via wireless, thus are easier to use and more comfortable to wear. Such technology can be...
Patient monitoring in intensive care units requires collection and processing of high volumes of data. High sensitivity of sensors leads to significant number of false alarms, which cause alarm fatigue. Reduction of false alarms can lead to better reaction time of medical personnel. This paper aims to develop a method for false alarm suppression and evaluate it on a publicly available data set with...
Electrocardiogram (ECG) is a test that represents electrical activity of heart and plays an important role in monitoring the condition of the heart. The diagnosis of cardiac condition is greatly dependent upon ECG signals. This paper presents a method of feature extraction and characterization of ECG signals for normal sinus rhythm and three different types of cardiovascular arrhythmia, namely Slow...
We present a mixed-signal system for extracting hemodynamic parameters in real-time from noisy electrical bioimpedance (EBI) measurements in an energy-efficient manner. The proof-of-concept system consists of floating-gate-based analog signal processing (ASP) electronics implemented on a field programmable analog array (FPAA) chip interfaced with an on-chip low-power microcontroller. Physiological...
The paper emphasizes the need for teaching and learning mathematically intensive theory subjects using very powerful software tools. Under Electrical Engineering discipline, there are subjects like Signals & systems, Control Systems, Digital Signal/Image Processing etc. where teachers need to spend a considerable amount of time in classroom, teaching the mathematical concepts, ending up with very...
Brain Functional Networks (BFNs), graph theoretical models of brain activity data, provide a systems perspective of complex functional connectivity within the brain. Neurological disorders are known to have basis in abnormal functional activities that could be captured in terms of network markers. Schizophrenia is a pathological condition characterized with altered brain functional state. We created...
The amount of audio data on public networks like Internet is increasing in huge volume daily. So to access these media, we need to efficiently index and annotate them. Due to non-stationary nature and discontinuities present in the audio signal, segmentation and classification of audio signal has really become a challenging task. Automatic music classification and annotation is also one of the challenging...
With the emerging and intense use of Online Social Networks (OSNs) amongst young children and teenagers (youngsters), safe networking and socializing on the Web has faced extensive scrutiny. Content and interactions which are considered safe for adult OSN users might embed potentially threatening and malicious information when it comes to underage users. This work is motivated by the strong need to...
This research is motivated through the demand to create routing in indoor environment based on activity recognition approach. A model to discriminate between walking, climbing up stair, and climbing down stair is introduced. Data was collected from a group of participants performing walking up stairs, walking down stairs, and walking on normal path inside the building. 35 features are considered in...
Developing fields such as Brain Computer Interface, Virtual Reality are now a day's in research are using brain signal as an equipment for a good start to differentiate tasks. It created new break points in aiding wellness training, rehabilitation, games, education, entertainment etc. Here, the content has been summarized about the technology, which had been developed for acquisition of brain signal,...
Identification of musical instruments from the acoustic signal using speech signal processing methods is a challenging problem. Further, whether this identification can be carried out by a single musical note, like humans are able to do, is an interesting research issue that has several potential applications in the music industry. Attempts have been made earlier using the spectral and temporal features...
Two practical inevitabilities for diagnostic systems are the abilities of incremental learning in non-stationary environments and diagnosing under the class imbalance condition. The class imbalance condition has been widely occurred in real applications where system usually works in the normal state and it is not easy to collect the representative patterns of faulty classes. This work aims to adapt...
Shotgun sequencing has facilitated the analysis of complex microbial communities. However, clustering and visualising these communities without prior taxonomic information is a major challenge. Feature descriptor methods can be utilised to extract these taxonomic relations from the data. Here, we present a novel approach consisting of local binary patterns (LBP) coupled with randomised singular value...
A novel method of classifying Power quality (PQ) events using Wavelet Packet Transform (WPT) and Extreme Learning Machines (ELM) has been proposed. In recent times, the power quality has been a major research concern due to changing regulations, liberalized distribution market and increased use of power electronic based equipment. The first step of any remedial action requires proper identification...
Features selection (FS) techniques have an apparent need in many complex engineering applications especially the bearing fault diagnosis of low-speed industrial motor. The main goal of an FS algorithm is to select the most discriminant features subset from a high-dimension features vector that increases the model performance by reducing the redundant and irrelevant fault features. This paper proposes...
For cardiologists, the detection of cardiac abnormalities is a very delicate and crucial task for the treatment of a patient's condition. This task that requires electronic systems of medical assistance that is more precise, faster and reliable to help cardiologists to analyze and make the right decisions. These medical assistance systems tend to model the human expertise and perception using signal...
Sleep Apnea is a potentially serious sleep disorder in which you have one or more pauses in breathing or shallow breaths while you sleep. It is classified into 3 main types: Obstructive sleep apnea, Central sleep apnea, and Complex sleep apnea syndrome. Obstructive sleep apnea (OSA) represents 80% of the apnea cases which makes it the most common type. Polysomnography is the current traditional method...
Classifier allows the user to classify between different classes based on the features acquired. The goals and applications of different classifiers are different. As the feature selection is one of the important criteria. In this paper we introduce a method of ranking the features of one class with respect to another and it tells the user that in the training set which feature has higher ranking...
Vehicle detection method based on traffic video surveillance is a fundamental element of Intelligent Transportation System (ITS), due to its inclusive vehicle behavior data collection capabilities. In recent years, video processing have been extensively used in traffic management. From video monitoring systems, detection of vehicles can be achieved. Detection of vehicles in frames is done in most...
In this era, the password-based system is not enough to secure important data. It has, in general, the disadvantage that passwords are either too hard to remember or too easy to guess. It is necessary to apply a higher level of security. This can be achieved by using the biometrics i.e. behavioral biometrics such as using mouse dynamics. In the existing system, the user needs to perform a specified...
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