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Epileptic seizure detection is traditionally done using video/electroencephalography monitoring, which is not applicable for long-term home monitoring. In recent years, attempts have been made to detect the seizures using other modalities. In this study, we investigated the application of four accelerometers (ACM) attached to the limbs and surface electromyography (sEMG) electrodes attached to upper...
Pediatric Pneumonia is one of the principal causes of death by year on children under the age of five worldwide. The diagnosis is commonly made by clinical criteria with support from imaging tools like radiography. Lung ultrasound has been considered a low-cost and portable alternative for pneumonia imaging; however, interpretation is subjective and requires adequate training. In the present work,...
Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a sleep related breathing disorder that has important consequences in the health and development of infants and young children. To enhance the early detection of OSAHS, we propose a methodology based on automated analysis of nocturnal blood oxygen saturation (SpO2) from respiratory polygraphy (RP) at home. A database composed of 50 SpO2 recordings...
This paper introduces a new method based on the Singular Values of EEG signals for the detection of epileptic seizures. Singular Value Decomposition was performed on an EEG signal in epochs of 8 seconds and Singular Values were extracted from each epoch. These singular values were fed into Support Vector Machine (SVM) for a binary classification between epileptic seizure and non- seizure events. Singular...
In this paper we consider the use of a well-known statistical method, namely Maximum-Likelihood Detection (MLD), to early diagnose, through a wire-free low-cost video processing-based approach, the presence of neonatal clonic seizures. Since clonic seizures are characterized by periodic movements of parts of the body (e.g., hands, legs), by evaluating the periodicity of the extracted signals it is...
Amplitude integrated electroencephalogram (aEEG), a cerebral function monitoring method, is widely used in response to the clinical needs for continuous EEG monitoring. The focus work of this paper is presenting a novel combined feature set of aEEG and applying random forest (RF) method to identify the normal and abnormal aEEG tracing. To that end, a complete experimental evaluation was conducted...
In this paper, we consider a novel low-complexity image processing-based approach to the detection of neonatal clonic seizures. Our approach is based on the extraction, from a video recording of a newborn, of an average luminosity signal representative of the body movements. Since clonic seizures are characterized by periodic movements of parts of the body (e.g., the limbs), by evaluating the periodicity...
Routine electroencephalogram (EEG) is an important test in aiding the diagnosis of patients with suspected epilepsy. These recordings typically last 20-40 minutes, during which signs of abnormal activity (spikes, sharp waves) are looked for in the EEG trace. It is essential that events of short duration are detected during the routine EEG test. The work presented in this paper examines the effect...
Hypothyroidism occurs in infants with insufficient production of hormones by the thyroid gland. The cry signals of babies with hypothyroidism have distinct patterns which can be recognized with pattern classifiers such as Multilayer Perceptron (MLP) artificial neural network. This study investigates the performance of the MLP in discriminating between healthy infants and infants suffering from hypothyroidism...
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