UV light has become an integral part of human life especially in performing wide range of disinfection. Most of the research on UVLEDs is limited to UVC region because of comparison with mercury based UV lamps which work typically at 254 nm. Limited research is found on the use of UVA-LEDs for inactivation of microorganisms in healthcare. In this study a standard 3 mm LED has been compared with 385 nm UVA-LED for inactivation of Escherichia coli. E. coli strains were swabbed on control, LED and UVA-LED petri dishes using cotton bud. The LED and UVA-LED samples were exposed to standard LED light and UVA light respectively for 1 h. The analysis of bacteria by determining Colony forming units (CFU) and log inactivation were carried out to calculate the number of colonies present in each sample. Result showed negligible to none disinfection properties in standard LED light. LED samples had CFU/ml colonies compared to control which is CFU/ml. UVA-LED samples achieved maximum inactivation and only had CFU/ml. Log inactivation results showed that LED samples observed 0.1-log inactivation whereas the UVA-LED had significant inactivation of 3.8-log inactivation corresponding to approximately 99.99 % E. coli reduction. The results demonstrate that UVA-LED at 385 nm is capable of efficiently providing inactivation of bacteria E. coli.
Osteoarthritis is the most commonly seen arthritis, where there are 30.8 million adults affected in 2015. Magnetic resonance imaging (MRI) plays a key role to provide direct visualization and quantitative measurement on knee cartilage to monitor the osteoarthritis progression. However, the visual quality of MRI data can be influenced by poor background luminance, complex human knee anatomy, and indistinctive tissue contrast. Typical histogram equalisation methods are proven to be irrelevant in processing the biomedical images due to their steep cumulative density function (CDF) mapping curve which could result in severe washout and distortion on subject details. In this paper, the prominent region of interest contrast enhancement method (PROICE) is proposed to separate the original histogram of a 16-bit biomedical image into two Gaussians that cover dark pixels region and bright pixels region respectively. After obtaining the mean of the brighter region, where our ROI – knee cartilage falls, the mean becomes a break point to process two Bezier transform curves separately. The Bezier curves are then combined to replace the typical CDF curve to equalize the original histogram. The enhanced image preserves knee feature as well as region of interest (ROI) mean brightness. The image enhancement performance tests show that PROICE has achieved the highest peak signal-to-noise ratio (PSNR=24.747±1.315dB), lowest absolute mean brightness error (AMBE=0.020±0.007) and notably structural similarity index (SSIM=0.935±0.019). In other words, PROICE has considerably outperformed the other approaches in terms of its noise reduction, perceived image quality, its precision and has shown great potential to visually assist physicians in their diagnosis and decision-making process.
The rapid use of ultraviolet light emitting diodes (UV-LEDs) in various disinfection applications is growing tremendously due to their advantages unachievable using UV lamps. In this study, a comparison of standard LED at 460 nm wavelength and UVA LED at 385 nm was conducted to determine their effectiveness in disinfection of frequently isolated pathogens in hospitals (Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli). Determination of disinfection efficiency was carried out by measuring inhibition zone. Effects of varied exposure time on the inactivation of pathogenic microorganisms was studied. The results demonstrated that LED does not have germicidal activities. The highest inactivation for UVA LED was achieved for Pseudomonas aeruginosa. Linear relationship was found between exposure time and log reduction. This study showed that UVA LEDs can effectively inactivate significantly higher number of microorganisms hence can be used in disinfection of various applications.
This work presents the use of Arduino-based embedded system interfaced to MATLAB software packages as an alternative cost-effective solution for the control of the microbioreactor operation. In the presented work, a microbioreactor platform with a working volume of approximately 1.5 mL have been fabricated using a low-cost poly (methylmethacrylate) (PMMA) and poly(dimethylsiloxane) (PDMS) polymers. The reactor have been integrated with stirring control, fuzzy logic temperature control, and aeration feature via a miniature air compressor. Control program of the microbioreactor system was established using Simulink, MATLAB software were executed by interfacing the program with Arduino Mega 2560 microcontroller for input and output of signals. Numbers of experimentation were performed to validate and demonstrate the potential of the proposed method. Satisfactorily degree of control and supervision was achieved (+ 1-3% of the set-point values). The entire microbioreactor system can be operated stably for a least 48 hours. The work demonstrated the usefulness of MATLAB software in establishing a microbioreactor operating interface that consisted merely few Simulink program block sets and executed on a low-cost Arduino board.
Magnetic resonance imaging is an important modality in the diagnosis and pathology detection. Edge detection is used for image segmentation and feature extraction as part of the medical image analysis. There is no ideal and universal algorithm which performs perfectly under all conditions. Conventional Canny edge detector is not suitable to be used in Magnetic resonance images that contaminated by Rician noise. In this paper, we propose the use of customized non-local means into the Canny edge detector instead of Gaussian smoothing in the conventional Canny edge detector to effectively remove Rician noise while preserving edges in Magnetic resonance image of an internal organ. The result shows that our method can yield better edge detection than conventional method, with minimal false edge detection. The proposed method undergoes several attempts of parameter adjustment to detect true edges successfully using optimal parameter setting.
Currently, contactless power transfer system is being implemented to power up the medical devices. Those medical devices can either power by transcutaneous cable or batteries. However, the power driven for medical devices via transcutaneous cable might lead to infection due to breach on the skin. The battery replacement surgery for cardiovascular patients also can lead to infection. Therefore, a contactless power transfer system is effectively solving the problem by transmitting power in a safe and non-invasive manner and has mitigate effect to patient health, yet efficient in the power transmission process. Magnetic coupled resonant is being designed since magnetic field cannot be shielded by biological tissues. Resonant power transfer technique can minimize the power scattering on the non-resonant objects such as human body. Impedance matching technique is utilized to improve the overall power transmission efficiency. The system consists a pair of transmitter and receiver coil, transmitter and receiver circuit, and a pair of transformer as impedance matching purpose. The system is capable to achieved a transfer efficiency of over 60%. Contactless power transfer technology does offer the advantages of safety, non-invasive and no significant effect on patient health. Eventually, bacterial infection on the skin breach is prevented.
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