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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...
Pattern recognition based myoelectric prostheses (MP) need a training procedure for calibrating the classifier. Due to the non-stationarity inhered in surface electromyography (sEMG) signals, the system should be retrained day by day in long-term use of MP. To boost the training procedure in later periods, we propose a method, namely Mixed-LDA, which computes the parameters of LDA through combining...
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...
Emotional or non-emotional image stimulus is recently applied to event-related potential (ERP) based brain computer interfaces (BCI). Though the classification performance is over 80% in a single trial, a discrimination between those ERPs has not been considered. In this research we tried to clarify the discriminability of four-class ERP-based BCI target data elicited by desk, seal, spider images...
Falls are a major cause of death and morbidity in older adults. In recent years many researchers have examined the role of wearable inertial sensors (accelerometers and/or gyroscopes) to automatically detect falls. The primary goal of such fall monitors is to alert care providers of the fall event, who can then commence earlier treatment. Although such fall detection systems may reduce time until...
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...
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)...
Disconnection from mechanical ventilation, called the weaning process, is an additional difficulty in the management of patients in intensive care units (ICU). Unnecessary delays in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we propose an extubation index based on the power of the respiratory flow signal (Pi). A total of 132 patients...
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...
Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification...
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...
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...
This paper proposes an automatic method for the detection of lumen contours in intravascular OCT images with guide wire shadow artifacts. This algorithm is divided into five main procedures: pre-processing, an Otsu binarization approach, an intensity curve approach, a lumen contour position correction, and image reconstruction and contour extraction. The 30 IVOCT images from six anonymous patients...
Automated processing of digital histopathology slides has the potential to streamline patient care and provide new tools for cancer classification and grading. Before automatic analysis is possible, quality control procedures are applied to ensure that each image can be read consistently. One important quality control step is color normalization of the slide image, which adjusts for color variances...
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 five degree-of-freedom (DOF) miniature parallel robot has been developed to precisely and safely remove the thin internal limiting membrane in the eye ground during vitreoretinal surgery. A simulator has been developed to determine the design parameters of this robot. The developed robot's size is 85 mm × 100 mm × 240 mm, and its weight is 770 g. This robot incorporates an emergency instrument retraction...
Improving activity recognition, with special focus on fall-detection, is the subject of this study. We show that Kalman smoothed in-painting of missing pose information and task-specific dimensionality reduction of activity feature vectors leads to significantly improved activity classification performance. We illustrate our findings by applying common classification algorithms to dimensionally reduced...
ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification...
Successful brain-computer interfaces (BCIs) swiftly and accurately communicate the user's intention to a computer. Typically, information transfer rate (ITR) is used to measure the performance of a BCI. We propose a multi-step process to speed up detection and classification of the user's intent and maximize ITR. Users randomly looked at 4 frequency options on the interface in two sessions, one without...
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