7 research outputs found
Image enhancement for red blood cell segmentation
A number of issues in blood cell image features such as illuminations, weak edge boundaries and color similarities especially between white blood cell (WBC) cytoplasm and red blood cell (RBC) which affect the accuracy of the segmentation of red blood cell image. This research aims to overcome the issue by applying image enhancement technique. Average filter, image contrast and median filter being proposed in this research. Each of the techniques help to eliminate fairly spread noises, display clear images and diminish single pixel noises. As the result, the quality image is increased and ready for the segmentation process
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Electrocardiograph (ECG) circuit design and software-based processing using LabVIEW
YesThe efficiency and acquisition of a clean (diagnosable) ECG signal dependent upon the proper selection of electronic components and the techniques used for noise elimination. Given that the human body and the lead cables act as antennas, hence picking up noises from the surroundings, thus a major part in the design of an ECG device is to apply various techniques for noise reduction at the early stage of the transmission and processing of the signal. This paper, therefore, covers the design and development of a Single Chanel 3-Lead Electrocardiograph and a Software-based processing environment. Main design characteristics include reduction of common mode voltages, good protection for the patient, use of the ECG device for both monitoring and automatic extraction (measurements) of the ECG components by the software. The hardware consisted of a lead selection stage for the user to select the bipolar lead for recording, a pre-amplification stage for amplifying the differential potentials while rejecting common mode voltages, an electrical isolation stage from three filtering stages with different bandwidths for noise attenuation, a power line interference reduction stage and a final amplification stage. A program in LabVIEW was developed to further improve the quality of the ECG signal, extract all its features and automatically calculate the main ECG output waveforms. The program had two main sections: The filtering section for removing power line interference, wideband noises and baseline wandering, and the analysis section for automatically extracting and measuring all the features of the ECG in real time. A Front Panel Environment was, therefore, developed for the user interface. The present system produced ECG tracings without the influence of noise/artefacts and provided accurate detection and measurement of all the components of the ECG signal
Electrocardiograph (ECG) circuit design and software-based processing using LabVIEW
The efficiency and acquisition of a clean (diagnosable) ECG signal dependent upon the proper selection of electronic components and the techniques used for noise elimination. Given that the human body and the lead cables act as antennas, hence picking up noises from the surroundings, thus a major part in the design of an ECG device is to apply various techniques for noise reduction at the early stage of the transmission and processing of the signal. This paper, therefore, covers the design and development of a Single Chanel 3-Lead Electrocardiograph and a Software-based processing environment. Main design characteristics include reduction of common mode voltages, good protection for the patient, use of the ECG device for both monitoring and automatic extraction (measurements) of the ECG components by the software. The hardware consisted of a lead selection stage for the user to select the bipolar lead for recording, a pre-amplification stage for amplifying the differential potentials while rejecting common mode voltages, an electrical isolation stage from three filtering stages with different bandwidths for noise attenuation, a power line interference reduction stage and a final amplification stage. A program in LabVIEW was developed to further improve the quality of the ECG signal, extract all its features and automatically calculate the main ECG output waveforms. The program had two main sections: The filtering section for removing power line interference, wideband noises and baseline wandering, and the analysis section for automatically extracting and measuring all the features of the ECG in real time. A Front Panel Environment was, therefore, developed for the user interface. The present system produced ECG tracings without the influence of noise/artefacts and provided accurate detection and measurement of all the components of the ECG signal
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A novel algorithm for human fall detection using height, velocity and position of the subject from depth maps
YesHuman fall detection systems play an important role in our daily life, because falls are the main obstacle for elderly people to live independently and it is also a major health concern due to aging population. Different approaches are used to develop human fall detection systems for elderly and people with special needs. The three basic approaches include some sort of wearable devices, ambient based devices or non-invasive vision-based devices using live cameras. Most of such systems are either based on wearable or ambient sensor which is very often rejected by users due to the high false alarm and difficulties in carrying them during their daily life activities. This paper proposes a fall detection system based on the height, velocity and position of the subject using depth information from Microsoft Kinect sensor. Classification of human fall from other activities of daily life is accomplished using height and velocity of the subject extracted from the depth information. Finally position of the subject is identified for fall confirmation. From the experimental results, the proposed system was able to achieve an average accuracy of 94.81% with sensitivity of 100% and specificity of 93.33%.Partly sponsored by Center for Graduate Studies. This work is funded under the project titled “Biomechanics computational modeling using depth maps for improvement on gait analysis”. Universiti Tun Hussein Onn Malaysia for provided lab components and GPPS (Project Vot No. U462) sponsor
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The effect of WIN55, 212-2 on protein S100, matrix metalloproteinase-2 and nitric oxide expression of chondrocyte monolayer
YesStudies have been conducted to highlight the anti-inflammatory and immunosuppressive properties of
synthetic cannabinoids as well as their potential for cartilage repair. Various wound healing techniques can be
used to investigate the mechanisms of chondrocyte repair in monolayers or three dimensional tissues constructs.
In this work the effect of WIN55, 212-2 (WIN-2) on nitric oxide (NO) and matrix metalloproteinase-2 (MMP-2)
expressed by wounded chondrocyte monolayers was investigated. Moreover, expression of collagen type-I and
type-II, fibronectin and S100 proteins were detected using immunofluorescence and quantitatively verified using
ELISA based techniques following treatment with 1 μM and 2 μM of WIN-2. Treating chondrocytes with 1 μM
of WIN-2 significantly increased expression of collagen type-II, fibronectin and S100, and significantly reduced
collagen type-I expressions as compared to the control groups. On the other hand, both concentrations of WIN-2
significantly reduced the expression of the inflammation markers NO and MMP-2 in a dose dependent manner.
These findings highlight the potential use of the synthetic cannabinoids for improving cartilage healing properties
as well as acting as an anti-inflammatory agent which could be used to enhance tissue engineering protocols
aimed at cartilage repair
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The Novel Coronavirus Causes Impairment of Blood Vessels and Respiratory System with Head-to-Toe Symptoms and Vaccine Development: An Overview
YesBlood clotting was reported in April 2020 [1] as another serious symptom due to COVID-19, but also came other reports such as young adults dying due to strokes and heart attacks [2]. The currently known head-to-toe symptoms of COVID-19, seem to indicate vascular as well as respiratory diseases and that 40% of related death are due to cardiovascular complications [2]. In a recently published journal paper in Lancet [3], the authors found that SARS-CoV-2 virus can infect the endothelial cells that line the inside of blood vessels noting that endothelial cells protect the cardiovascular system and release proteins that influence everything from blood clotting to the immune response. In the same paper, the authors showed damage to endothelial cells in the lungs, heart, kidneys, liver, and intestines in patients with Covid-19. Therefore, the emerging belief is that the novel coronavirus is a respiratory illness to begin with, but as it spreads further into blood vessels it becomes a vascular illness that is capable of killing patients via vascular system