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Human activity can serve as an identifier of subject health, behavioral patterns, and personal preferences. With the sudden splurge in mobile and wearable devices, activity data has become more readily available to design useful applications that enhance the users' everyday lives without any obtrusive intervention. This paper focuses on the use of a system identification approach to characterize human...
In the caza of “Byblos”, Lebanon, a new road has been constructed near the natural reserve of “Bentael”, threatening the fauna and the flora of the reserve. Among the 360 floral species, “Urginea maritima” has been declared rare by the United Nations Environment Program (UNEP)[1]. Concerns on the extinction of some species are getting serious. In order to elucidate the seriousness of these worries,...
As any technology, medical equipment provides benefits to patients, but they also present significant risks that can affect and threaten patient safety. In healthcare organizations, clinical engineering departments play a big role in maintaining the safety and reliability of medical equipment. In order to mitigate failures of such equipment and control risks, a proper Medical Equipment Management...
The human activity recognition is widely used for human behavior prediction especially for dependent people. This is achieved to provide safety, health monitoring, and well being of this population at home. In this paper, the problem of human activity recognition is reformulated as joint segmentation of multidimensional time series. The hidden Markov model regression (HMMR) is used to perform unsupervised...
The aim of this investigation is to design and construct a demonstrative prototype of a low cost foot planter-pressure scanner that can assess health care providers in diagnosing and monitoring patients who are suffering from foot disorders. The prototype will be designed from a matrix of force sensitive sensors that measure the spread of forces on the plantar surface of the foot. Suitable Graphical...
The Kalman Filter (KF) is a powerful state estimation technique developed for linear time-varying systems and has recently extended for estimating nonlinear time varying dynamical systems. However, a major challenge for this technique is the choice of the tuning filter parameters that often necessitates a long and tedious process, particularly for large nonlinear systems. In the present work, we propose...
Locked-in syndrome is known to be a condition in which a patient loses the ability to control nearly all voluntary muscles in the body except for the eye. In today's world, healthcare facilities have the means and equipment necessary to help such patients and take care of their needs, which includes medical care and patient comfort. However, such dedicated professional services are not commonly provided...
Network modularity is a key feature for efficient information processing in the human brain. This information processing is however dynamic and networks can reconfigure at very short time period (few hundreds of millisecond). This requires neuroimaging techniques with sufficient time resolution. Here the dense electroencephalography (EEG) source connectivity methods were used to identify cortical...
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...
the use of packaging material in biomedical sensors is a required criterion to achieve certain properties; the most important one is biocompatibility. Response time of biomedical sensors is highly dependent on the sensor's specifications in addition to the type of packaging materials. Compensation of the time delay in the sensor's response due to the packaging material requires detailed mathematical...
Pattern recognition control applied on surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for the control of powered prosthetics for transradial amputees. The use of limb prostheses is essential for maintaining personal independence and a more effective inclusion in society. However, due to their poor control, imposed by the reduced accuracy of hand movement classification,...
Low capacity, bulky size and wiring limitations of the conventional wireless multi-channel electroencephalography (EEG) system restrict its use as brain neuromonitoring system. To reduce such restriction, this paper proposes an EEG system based on multi-input multi-output (MIMO) technique and polar coded data. In the proposed system, all the channels are sent and received simultaneously, while the...
Cerebrovascular Accidents can be caused by cerebral emboli blocking brain blood vessels. Analysis of transcranial Doppler signals practically aids the detection of emboli. Signal processing methods have been proposed for emboli detection. In this study, we introduce a new micro-embolic energy detector composed of N detectors associated to N Doppler frequency sub-bands. To test our detectors, we propose...
The EHG signals are recorded using a multichannel system positioned on the woman's abdomen for the simultaneous recording of 16 channels of EHG. Several studies calculated the features related to EHG propagation by studying the coupling between all possible channels (bivariate analysis). Using all the possible features extracted to characterize propagation, from all possible combinations of channels,...
the noisy and complex nature of many biological signals such as the electroencephalogram (EEG) has long constituted a major challenge in terms of analysis and prediction for single and multivariate problems. Nonlinear signal modeling, despite its widespread applicability, often shows limited success whenever the signal is contaminated with noise or is time varying in nature. We herein introduce a...
Determination of seizure origin is often challenging due to the rapid speed at which electrical activity propagates throughout the brain. The Directed Transfer Function (DTF) has been proposed and validated as a quantitative approach to determine the flow of seizure activity. In this work, outflow and inflow features are extracted from the DTF matrix and used as inputs to a Kmeans unsupervised clustering...
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