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Single motor unit activity study is a major research interest because changes of MUAP morphology, MU activation, and MU recruitment provide the most informative part in diagnosis and treatment of neuromuscular disorders. Intramuscular recordings often provide a more than one motor unit activities, thus MUAP discrimination is a crucial task to study single unit activities. Most neurology laboratories...
This study developed a method of discriminating real-time motion from electromyogram (EMG) signals. We previously proposed a real-time motion discrimination method using hyper-sphere models that discriminated five motions (open, grasp, pinching, wrist extension, and wrist flexion) above 90% and quickly learned EMG signals. Our method prevents elbow motions from interfering with hand motion discrimination...
This paper presents a comparison between two different technologies of acquisition systems (BrainNet36 and Emotiv Epoc) for an Independent-BCI based on Steady-State Visual Evoked Potential (SSVEP). Two stimuli separated by a viewing angle < 1° were used. Multivariate Synchronization Index (MSI) technique was used as feature extractor and five subjects participated in the experiments. The class...
Regular electrocardiogram beat classification system usually based on single lead ECG signal. This study designated to add a second lead of ECG signal to the system and apply higher-order statistics and inter-lead cross-correlation features to study the influence of the second lead to the recognition rates and noise-tolerance of the classifier. Discrete wavelet transformation is employed to decompose...
Electronic Fetal Monitoring in the form of cardiotocography is routinely used for fetal assessment both during pregnancy and delivery. However its interpretation requires a high level of expertise and even then the assessment is somewhat subjective as it has been proven by the high inter and intra-observer variability. Therefore the scientific community seeks for more objective methods for its interpretation...
This preliminary study investigated the use of cardiac information or more specifically, heart rate variability (HRV), for automatic deep sleep detection throughout the night. The HRV data can be derived from cardiac signals, which were obtained from polysomnography (PSG) recordings. In total 42 features were extracted from the HRV data of 15 single-night PSG recordings (from 15 healthy subjects)...
In this study we propose a novel atrial activity-based method for atrial fibrillation (AF) identification that detects the absence of normal sinus rhythm (SR) P-waves from the surface ECG. The proposed algorithm extracts nine features from P-waves during SR and develops a statistical model to describe the distribution of the features. The Expectation-Maximization algorithm is applied to a training...
The T and P waves of electrocardiogram signals are excellent indicators in the analysis and interpretation of cardiac arrhythmia. As such, the need to address and develop an accurate delineation technique for the detection of these waves is necessary. In this paper, we present a novel robust and adaptive T and P wave delineation method for real-time analysis and nonstandard ECG morphologies. The proposed...
Diabetic retinopathy (DR) is one of the most common causing of vision loss in developed countries. In early stage of DR, some signs like exudates appear in the retinal images. An automatic screening system must be capable to detect these signs properly so that the treatment of the patients may begin in time. The appearance of exudates shows a rich variety regarding their shape and size making automatic...
Diabetic retinopathy (DR) is a visual complication of diabetes, which has become one of the leading causes of preventable blindness in the world. Exudate detection is an important problem in automatic screening systems for detection of diabetic retinopathy using color fundus photographs. In this paper, we present a method for detection of exudates in color fundus photographs, which combines several...
It is important to classify retinal blood vessels into arterioles and venules for computerised analysis of the vasculature and to aid discovery of disease biomarkers. For instance, zone B is the standardised region of a retinal image utilised for the measurement of the arteriole to venule width ratio (AVR), a parameter indicative of microvascular health and systemic disease. We introduce a Least Square-Support...
The biomedical community has shown a continued interest in automated detection of Diabetic Retinopathy (DR), with new imaging techniques, evolving diagnostic criteria, and advancing computing methods. Existing state of the art for detecting DR-related lesions tends to emphasize different, specific approaches for each type of lesion. However, recent research has aimed at general frameworks adaptable...
This paper presents a novel approach of finding corner features between retinal fundus images. Such images are relatively textureless and comprising uneven shades which render state-of-the-art approaches e.g., SIFT to be ineffective. Many of the detected features have low repeatability (< 10%), especially when the viewing angle difference in the corresponding images is large. Our approach is based...
Intracoronary optical coherence tomography (OCT) is a new invasive imaging system which produces highresolution images of coronary arteries. Preliminary data suggests that the atherosclerotic disease can be detected from the intracoronary OCT images. However, manual assessment of the intracoronary OCT images is time-consuming and subjective. In this work, we present an automatic atherosclerotic disease...
In this work an attempt has been made to enhance the edges and segment the boundary of intima-media layer of Common Carotid Artery (CCA) using anisotropic diffusion filter and level set method. Ultrasound B mode longitudinal images of normal and abnormal images of common carotid arteries are used in this study. The images are subjected to anisotropic diffusion filter to generate edge map. This edge...
Obstructive Sleep Apnea (OSA) is the most common form of sleep disorder breathing. It is estimated that this insidious disease affects 15% of the US adult population. Current procedure of diagnosing OSA requires polysomnography (NPSG) conducted in accredited sleep laboratories and the data getting scored by certified sleep technicians, a costly process that is not readily available in all areas. Ultrasonic...
Polysomnography (PSG) studies are considered the “gold standard” for the diagnosis of Sleep Apnoea (SA). Identifying cessations of breathing from long-lasting PSG recordings manually is a labour-intensive and time-consuming task for sleep specialist, associated with inter-scorer variability. In this study a simplified, semi-automatic, three-channel method for detection of SA patients is proposed in...
A wearable depression monitoring system is proposed with an application-specific system-on-chip (SoC) solution. The SoC is designed to accelerate the filtering and feature extraction of heart-rate variability (HRV) from the electrocardiogram (ECG). Thanks to the SoC solution and planar-fashionable circuit board (P-FCB), the monitoring system becomes a low-power wearable system. Its dimension is 14cm...
A new smart fall-down detector for senior healthcare system using inertial microsensors and Wi-Fi technology has been designed, prototyped and characterized in this work. The detector can reduce the risk of severe injury or death caused by falling down with minimum false alarm rate. The different patterns of motion are sensed by a set of inertial sensors composed of a tri-axial accelerometer and a...
Down syndrome is the most common chromosomal condition that presents characteristic facial morphology and texture patterns. The early detection of Down syndrome through an automatic, non-invasive and simple way is desirable and critical to provide the best health management to newborns. In this study, we propose such a computer-aided diagnosis system for Down syndrome from photography based on facial...
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