Mohd Firdaus Abdullah

Development of a low cost self-sensing Piezoresistive Microcantilever biosensor and read-out circuitry for measuring salivary-amylase activity

This paper deals with the development of a low cost self-sensing Piezeoresistive Microcantilever Biosensor to detect human stress using salivary alpha amylase activity. The salivary alpha amylase enzyme will immobilize on to the Piezeoresistive Microcantilever biosensor to detect activity during the enzyme responses. When the Microcantilever beam deflects it caused the stress change within the microcantilever beam and applied strain to the piezoresistor material thereby causing the resistance change and the Piezoresistive Microcantilever biosensor integrated with transducer components coverts the biochemical signal into measurable signal. The enzyme concentration signal is converted to a voltage by the transducer. A novel Piezeoresistive Microcantilever biosensing method and its application is described. The device was designed specifically that it enables the small resistivity change due to the enzymatic reaction to be measured.

Development of a transduction circuit for piezoresistive MEMS sensor for biosensing

This paper concerns the development of a potentiometric transduction circuit for a piezoresistive MEMS sensor to detect human stress. The biosensor is comprised of a bioreceptor and a transducer. The sensing principle is based on immobilization of the bioreceptor to produce a biochemical reaction. The novel piezoresistive microcantilever sensor integrated with a transduction circuit converts this biochemical event into a measurable electrical signal. From previous work, it has been found that the level of alpha amylase activity corresponds to human stress. The piezoresistive MEMS sensing and transduction method are described, with enzyme concentration as the input and voltage as the output. The transduction circuit designed enables the small change in resistivity due to the enzymatic reaction to be detected. The circuit has been designed and tested through theoretical, simulation and experimental studies. It has been found that for a sensor input range of 1.2 to 1.3 kilo ohms, an output range of −100 to +100 millivolts is obtained. A discrepancy within 3.69% is found between simulation and experimental results, on the average. The null bridge condition is designed at 1.2 kilo ohms while the offset rate is found to be 10 millivolts per ohm.

New image enhancement technique for WMH segmentation of MRI FLAIR image

This paper proposes a new image enhancement technique known as Average Intensity Replacement based on Adaptive Histogram Equalization (AIR-AHE) for FLAIR image based on intensities and contrast mapping techniques. The proposed algorithm consists of partial contrast stretching, contrast limiting enhancement, window sliding neighborhood operation and new pixel centroid replacement. The fluid attenuated inversion recovery (FLAIR) sequences of MRI images which are used for segmentation have low contrast. Therefore, contrast stretching is used to improve the quality of the image. After improving the quality of image, the regions of high intensity are determined to represent potential WMH areas. The result shows that the image has a moderate enhancement on the WMH region which is significant to the image contrast enhancement. With complete brightness preservation, the proposed method gives a relatively natural brightness improvement on the WMH of the periventricular region.

Initial quantitative comparison of 940nm and 950nm infrared sensor performance for measuring glucose non-invasively

This project uses a non-invasive method for measuring the blood glucose concentration levels. By implementing two infrared light with different wavelength; 940nm and 950nm based on the use of light emitting diodes and measure transmittance through solution of distilled water and d-glucose of concentration from 0mg/dL to 200mg/dL by using a 1000nm photodiode. It is observed that the output voltage from the photodiode increased proportionally to the increased of concentration levels. The relation observed was linear. Nine subjects with the same age but different body weight have been used to observe the glucose level during fasting and non-fasting. During fasting the voltage is about 0.13096V to 0.236V and during non-fasting the voltage range is about 0.12V to 0.256V. This method of measuring blood glucose level may become a preferably choice for diabetics because of the non-invasive and may extend to the general public. For having a large majority people able to monitor their blood glucose levels, it may prevent hypoglycemia, hyperglycemia and perhaps the onset of diabetes.

Particles contaminations detection during plasma etching process by using k-nearest neighbors and Fuzzy k-nearest neighbors

This paper present the particle contamination detection during plasma etching process by using k-nearest neighbor (kNN) and Fuzzy k-nearest neighbor (FkNN). In the process of manufacturing semiconductor devices, detecting particle contamination in process tool is a vital factor for determining for product yield. In situ particle is an accurate and cost effective method of contamination control in a production environment which possible to measure particles under actual conditions in real time. Data were collected from two sources Statistical Process Control (SPC) database and Advance Process Control (APC) database. There are four features which are Standard Deviation of voltage bias, Range between minimum and maximum of voltage bias, average of voltage bias and Radio frequency (RF) per Hour. These data are analyzed to identify important features that able to correlate with the particle contamination count during plasma etching process. In this research there are two part of analysis, individual parameter analysis and combination several parameter analysis by using kNN and FkNN. This analysis, used to classify into two levels of contamination, that are low and high particles contamination. By analysis results, kNN method is highest accuracy 83.33% by using standard deviation of voltage bias and FkNN show highest accuracy on combination parameters analysis 80.56% from combination between RF hour and standard deviation of voltage bias.

Preliminary study of recognizing alphabet letter via hand gesture

Communication is one of human basic necessity. People with disabilities usually use sign language to communicate with others. The study identifies the alphabet letters from the finger spelling based on American Sign Language (ASL) standard. The bending sensors were attached to three fingers of spelling glove where the bending movement of each finger contributes different resistance value of the bending sensors. The combinations of resistance value from each finger were detected from microcontrollers library and alphabet letters will be displayed. This study assists normal person who are new to sign language to understand the spelling letters when communicate with the disabilities.

Development of low pass filtering and linearization for piezoresistive microcantilever biosensing

This paper concerns the development and design of filtering and linearization stage of potentiometric transducer to measure human stress level based on salivary amylase activity. The design of this new way approached is implemented using Cadence OrCAD Capture CIS 15.7 software and hardware construction and troubleshooting. From the previous research, it has been found that for a sensor input range of 1.1 to 1.3 kilo ohms, an output range of −100 to +100 millivolts is obtained. The design for filtering stage used the first order passive low pass filter to accommodate the stress signal frequency for 0.4Hz. Besides the design also focus to boost up the low voltage input of 108.6mV–(−100mV) to 0V–5V output voltage. Its involved low pass filter, voltage follower and linearization stages. The result indicates discrepancy within 4.5% and 3.7% were found between the simulation and experimental results for voltage follower after filtering and linearization circuit respectively, on the average. This development allowed stress measurement with relatively high precision and accuracy.

A study on electrode for amperometric measurement of human stress with flow injection analysis biosensing system

This paper presents a study on electrode for the amperometric detection of human stress based on salivary alpha amylase, emulated with different concentration of glucose, with the flow injection analysis biosensing system. Amperometric detection is an electrochemical voltammetric measurement approach, where the current intensity in a detection cell is regarded as a function of the concentration of the analyte. Flow injection analysis is a chemical analysis method that injects a test sample into a flowing carrier stream. The screen printed electrode is used to detect the amount of glucose concentration, which is proportional to the amount of output current. The objective of the study is to conduct a comparative study between the gold and carbon electrode, as a choice for amperometric detection of human stress with flow injection analysis biosensing system. It has been found that, the [initial, steady state current output at first injection of glucose, current output at second injection of glucose] for carbon and gold printed electrode are [0–80, 0–20, 0–20] μA and [0–35, 0–10, 0–5] μA respectively. This shows measurement resolution of the carbon screen printed electrode is better, which results in higher measurement sensitivity. However, it is found that the gold printed electrode exhibits higher rate of reaction with the steeper gradients and the current reaches its steady state values faster. Yet, in view of the cost, the gold printed electrode is about three times more than the carbon printed electrode and also the ease in handling the zero baseline, the latter is thus made as the choice electrode.

Assessing intensity of white matter hyperintensity and normal appearing white matter in healthy adults

There have been interest on white matter hyperintensity (WMH) and normal white matter (WM) changes reported but have not yet been fully characterized. Different image sequences of magnetic resonance imaging (MRI) scans may shows different gray scale intensity. However, it is difficult to differentiate the intensity of normal WM and WMH as their intensities are visually not much different. In this study, normal WM and WMH changes were investigated based on their intensity to determine the correlation of WMH types and severity in brain of healthy subjects. The assessment was performed by using fully automatic WMH detection and computing algorithms. The main brain regions were segregated into gray matter (GM), normal WM, cerebrospinal fluid (CSF) and non-brain tissue. From the results, it shows that there was significant difference seen between normal appearing WM and hyperintense WM in terms of their intensity levels. The study shows that the development of WMH is prevalent to the occasion of normal WM changes. This is shows that WMH intensity reflects the level of WMH classes and severity; however, further investigations are needed to improve their efficiency.

A low cost automatic control system for conductivity of small scale wastewater treatment

This paper presents a design for a low cost 2-electrodes conductivity control system for small scale wastewater treatment system, such as that from etching process of printed circuit board. It involves the design of a conductivity sensing probe, its associated control circuitry and an actuation mechanism. The conductivity sensor applies a direct current to two electrodes and measures the potential voltage. The control circuitry computes the switching action of the actuation mechanism which acts in response to a specific level of conductivity. This control system determines whether the wastewater from the wastewater treatment system is clean enough to be discharged based on the water conductivity. Experimental result covered by this low cost conductivity control system ranges from 0.08 µS to 0.632 S and shows a switching voltage of 2.23 volts which corresponds to 20 µS, a requirement for treated water from small scale wastewater treatment system for etching process of printed circuit board. The wastewater is recycled when the water conductivity reaches above 20 µS while the wastewater is discharged otherwise.