Real-time Simulation of Cardiac Excitation Using Hardwareimplemented Cardiac Excitation Modeling

In this paper a hardware-implemented cardiac excitation model of a cardiac cell based on Luo-Rudy phase I (LR1) for the action potential (AP) generation in a mammalian cardiac ventricle is proposed to speed up the computational time during the simulation of the cardiac AP conduction. The hardware-implemented cardiac excitation model is designed by using analog circuits and a dsPIC microcontroller that could reproduce timedependent and time-independent nonlinear current-voltage characteristics of six-type of ionic currents in LR1 model. Through the study, real-time simulations of reentrant excitation conduction of cardiac cells are realized by coupling 30 active circuits of the cell models based on a cable model. The real-time simulations of initiation have been performed by the model and they are comparable to those from the LR1 model. Thus, it is conceivable that the hardware-implemented cardiac excitation model may be useful as one of alternative tools toward further understanding of the reentrant mechanisms

In silico simulation of blood glucose-insulin dynamics using MATLAB-Simulink

Diabetes mellitus (DM) is a major public health concern in Malaysia and it continuously increases over years. Based on International Diabetes Federation, there are rising numbers of people having diabetes with 3.6 million people in Malaysia and 463 million people in the world [1]. The National Health and Morbidity Survey (NHMS) 2019 has shown that the diabetes in Malaysia has increased from 13.4% in 2015 to 18.3% in 2019 [2]. This can significantly increase the cost in diabetes treatment and management

RFID - based Interactive Log Bag for Poor Memory Prevention

People are sometimes forgotten about what they should do or what they need to bring. Poor memory problem that happened in people less than 40 years old is due to their attitudes that like to ignore things and carelessness. An Interactive Log Bag has been developed using Arduino Mega 2560 with Radio Frequency Identification (RFID) system to help people overcome the poor memory problem of bringing or keeping essential items in a bag before travelling or going to work. The bag will react to the user RFID-tagged objects for the items logging purpose. The logging items will be saved in the SD card and can be shown in Messenger Bag Android Application. An alert system by using strip RGB Light Emitting Diode (LED) will remind the users of the forgotten items. In addition, the list of items that are left behind or carried in the bag can be checked through an android application. This project will give an opportunity to the users to have a better life by overcoming one of the daily routine problems pertaining to the forgetfulness problem

Evaluation of Three-Axial Wireless-based Accelerometer for Fall Detection Analysis

Injuries from falling can be a serious problem for the elderly people and nowadays, a variety of research has been done on the topic of fall detection. Health professionals often refer to a person’s ability to perform Activities of Daily Life (ADL) as a measurement of their functional status. In this research, a wearable wireless-based three-axial accelerometer sensor from Shimmer has been evaluated using a falling detection algorithm from Lindemann et al. and expanded by Chia-Chi Wang et al. which is according to two parameters of sum-vector of all axes (Sa) and sum-vector of horizontal plane (Sh). These parameters are used to determine significant points of time in the falling process, and identify lying condition. For this purpose, a walking activity has been used to analyse between the fall and the ADL. According to the analysis of falls and walks through the ADL of walking activity on ten and three healthy subjects, respectively, the method is 100 percent capable to classify between the fall and the walk

Fuzzy Logic System for Menstrual Cycle Interpretation Based on BBT Data

Basal body temperature (BBT) data have been used for so long as a simple method in estimating the day of ovulation occurred and to understand menstrual cycle that is unique for every woman. The BBT is considered to be a reliable ovulatory index, since most women will have increased temperature in the luteal phase of the cycle. However, the problems faced are the studies of validating the efficacy using BBT and lack of research. Therefore, according to these problems, a fuzzy logic system for the predictions of ovulation occurrence, follicular and luteal phase length has been constructed to interpret the BBT data effectively and this system has been implemented on Arduino Mega 2560 microcontroller for portability purpose. As a result, according to six samples of open source BBT data obtained from the Fertility Friend website, the system enables to predict the ovulation occurrence and follicular and luteal phase length with 71.43 % of accuracy

Mini Review of Glucose Detection Using Plasmonic Sensor

Glucose is a crucial compound in human life. Glucose has important roles in energy source production and overall brain health. In addition, it can be converted into other compounds essential for the growth, repair, and maintaining tissues throughout the body. Also, glucose becomes an indicator of diabetes, i.e., ill when the body can not produce insulin hormone properly. The poor management of diabetes can affect long-term complications that can significantly impact a person's quality of life and may lead to disability or even premature death if not properly addressed. Thus, it is important to do glucose detection to stay within a healthy range. The common methods patients use are glucose meters and urine testing on the laboratory scale. This method has several areas for improvement, such as being invasive, needing experts, and requiring a long-time detection. Thus, researchers come into various alternative glucose detection such as chromatography, mass spectrometry, electrochemical, and plasmonic sensor. Chromatography for glucose detection is rarely used in recent years because of its complexity. Then, for mass spectrometry, it is also complicated for the result and maintenance. As for electrochemical methods, the disadvantage is that other electroactive components on the sample can be interfered with. Plasmonic sensors that utilize the Localized Surface Plasmon Resonance (LSPR) phenomenon are considered due to their advantage, i.e., non-invasive, real-time monitoring, and highly sensitive to surrounding medium change. Plasmonic sensors usually use components of light absorption, luminescence, fluorescence, Raman scattering, reflectance, and refractive index based on the nanoparticles used as sensing materials. Still, transmission and reflection are popular and widely applied. Furthermore, plasmonic sensors generally consist of instruments such as a light source, fiber optic, chamber to place substrate/analyte, spectrometer/detector, and computer. Besides, plasmonic sensors can produce different analytical characteristics suitable for different cases and tuned for the need because of the various sensing materials used. Hence, plasmonic sensors become a promising alternative method for glucose detection

Modified lambert beer for bilirubin concentration and blood oxygen saturation prediction

Noninvasive measurement of health parameters such as blood oxygen saturation and bilirubin concentration predicted via an appropriate light reflectance model based on the measured optical signals is of eminent interest in biomedical research. This is to replace the use of conventional invasive blood sampling approach. This study aims to investigate the feasibility of using Modified Lambert Beer model (MLB) in the prediction of one’s bilirubin concentration and blood oxygen saturation value, SO2. This quantification technique is based on a priori knowledge of extinction coefficients of bilirubin and hemoglobin derivatives in the wavelength range of 440 – 500 nm. The validity of the prediction was evaluated using light reflectance data from TracePro raytracing software for a single-layered skin model with varying bilirubin concentration. The results revealed some promising trends in the estimated bilirubin concentration with mean ± standard deviation (SD) error of 0.255 ± 0.025 g/l. Meanwhile, a remarkable low mean ± SD error of 9.11 ± 2.48 % was found for the predicted SO2 value. It was concluded that these errors are likely due to the insufficiency of the MLB at describing changes in the light attenuation with the underlying light absorption processes. In addition, this study also suggested the use of a linear regression model deduced from this work for an improved prediction of the required health parameter values

Development of Auto Roll Prayer Mat for Musolla

During Friday or ‘Hari Raya’ festival, mosques will be flooded with Muslims who wish to perform prayers. Normally, mosques or ‘musolla’ require a large prayer space and certainly committees of the mosques would like to provide a comfortable space to perform prayer. However, the problem comes when the area provided is small and therefore the mosque’s person in charge which is known as ‘tok siak’ needs to prepare additional prayer mat for them. In this study, Auto Roll Prayer Mat (ARPM) is a new innovation idea system that was designed to ease the burden and at the same time to make the task more efficient. ARPM can perform in two conditions, which are it can stretched out prayer mat automatically and the other is that the prayer mat also can roll back to its actual condition. The overall system was supported with a main component of the system which was a power window motor accompanied with pulse width modulation (PWM) motor controller circuit. Moreover, ARPM was also equipped with secondary function of an automatic cleaning process where the ARPM system was able to clean the prayer mat by using a servo motor and Arduino UNO microcontroller, while simultaneously stretching out the prayer mat