Phototherapy Radiometer with AS7262 Sensor

The phototherapy is a device used in hyperbilirubinemia therapy by using blue light radiation with ranges between 425nm-475nm. The effectiveness of hyperbilirubinemia therapy depends on the amount of energy emitted by light which expressed in μW/cm2. The purpose of this study is to develop a low-cost and high accuracy Phototherapy radiometer. Measurement of blue light irradiance using the AS7262 sensor which can measure the irradiance of visible light with a wavelength of 450nm, 500nm, 550nm, 570nm, 600nm, 650nm with relative responsiveness of 1 time at each wavelength. SD card memory is used to save measurement data of irradiance so that it can be processed later. Based on the blue light irradiance data collected the smallest error value is 0,40% at a distance of 10cm while the biggest error value is 9,01%  at a distance of 30cm. After testing the entire system, the device can be used according to its function and purpose

Apnea Monitor Based on Bluetooth with Android Interface

Apnea monitor is a device that is used to give a warning if there is stop breathing. Stop breathing while sleeping is one form of obstructive sleep apnea. This cessation of breath cannot be underestimated, this is related to the main risk factors for health implications and increased cardiovascular disease and sudden death. The purpose of this study is to design an apnea monitor with the Android interface. This device allows the users to get how many times sleep apnea happens while sleeping and got data to analysis before continuing with a more expensive and advanced sleep test. This device used a flex sensor to detect the respiration rate, the sensor placed on the abdomen or belly so it can measure expand and deflate while breathing. The microcontroller uses an Arduino chip called AT-Mega328. Bluetooth HC-05 used to send respiration data to Android, MIT app inventor used for the android programmer, and on the android, there are plotting of respiration value and when the device detected apnea so the android also gives a warning to the user. Based on the results of testing and measurement then compare with another device, the results of the average% error were 3.61%. This apnea monitor design is portable but there are needs some improvement by using another sensor for detected respiration and using a module other than Bluetooth

Modified Background Subtraction Statistic Models for Improvement Detection and Counting of Active Spermatozoa Motility

An important early stage in the research of sperm analysis is the phase of sperm detection or separating sperm objects from images/video obtained from observations on semen. The success rate in separating sperm objects from semen fluids has an important role for further analysis of sperm objects. Algorithm or Background subtraction method is a process that can be used to separate moving objects (foreground) and background on sperm video data that tend to uni-modal. In this research, some of the subproject model statistics of substrata model are Gaussian single, Gaussian Mixture Model (GMM), Kernel Density Estimation and compared with some basic subtraction model background algorithm in detecting and counting the number of active spermatozoa. From the results of the tests, the Grimson GMM method has an f-measure value of 0.8265 and succeeded in extracting the sperm form near its original form compared to other method

Kesehatan Sebagai Suatu Investasi

Makalah ini akan meninjau kesehatan sebagai salah satu komponen mutu modal manusia dalam pembangunan. Kesehatan merupakan kebutuhan yang penting bagi manusia. Status kesehatan yang lebih baik secara relatif diinginkan oleh setiap individu manusia yang hidup di muka bumi ini. Setiap individu akan berusaha mencapai status kesehatan tersebut dengan melakukan investasi dan atau mengkonsumsi sejumlah barang dan jasa kesehatan.Dari sudut pandang ekonomi, pentingnya faktor kesehatan bagi manusia akan sangat terkait sekali dengan kualitas sumber daya manusia (quality of human resources). Tinggi rendahnya kualitas sumber daya manusia (SDM) akan ditentukan oleh status kesehatan, pendidikan, dan tingkat pendapatan per kapita (Ananta dan Hatmajdi, 1985). Dalam kegiatan perekonomian, ketiga faktor tersebut akan menentukan produktivitas SDM sebagai salah satu indikator quality of human resources

Development of A Low-Cost and Effisient ECG Devices with IIR Digital Filter Design

Measurement of biosignals such as electrocardiograph has the interpretation of noise from other signals. The noise can interfere with the measurement of the heart signal and make the measurement inaccurate, so the purpose of this study is to make a 6-Lead Electrocardiogram module with an Arduino-Based Digital Filter. By using a digital filter. The contribution of this research is the use of digital filters to eliminate noise in electrocardiograph signals. This research uses Infinite Impulse Filter digital filters such as Butterworth, Chebyshev I, Chebyshev II, and Elliptic in order 2, 4, 6, 8, and 10. The study was conducted by providing input from the Function Generator on Arduino which has been applied digital filters with Frequency with 0.5Hz – 100Hz cut-off. The instrument is compared with a factory electrocardiograph. Filter measurements using 460 input data. Butterworth filter with the greatest emphasis on order 8 frequency 0.5Hz produces an emphasis of -5.74298158 dB and a frequency of 100Hz produces an emphasis of -5.93529424 dB. The Chebyshev I filter has the greatest emphasis on order 6 frequency 0.5Hz producing an emphasis of -3.27104076 dB and on order 8 frequency 100Hz producing an emphasis of -5.08730424 dB. Chebyshev II filter the biggest emphasis on the order of frequency 0.5Hz produces a suppression of -44,66011104 dB and 80Hz frequency produces a suppression of -37,3653957 dB. Elliptic filters the greatest emphasis on order 6 frequency 0.5Hz produces an emphasis on -1.55429354 dB and 100Hz frequency on order 8 produces an emphasis on -2.2849115 dB. The results showed that what was appropriate with the cut-off frequency was the Butterworth order 8 filter which was suitable for the application of the Electrocardiograph signal filter because it had bandwidth that suppressed the signal outside the cut-off frequency. The results of this study can be implemented on a 6-Lead ECG module to eliminate noise or interference when tapping ECG signals

Automatic Dehydration Level Detection Devices

Dehydration is a condition that occurs when the loss of body fluids exceeds the amount entered in the body so that it can disrupt the balance of minerals in body fluids. Most people do not feel thirsty until finally, they experience a period of severe dehydration, which can cause physical, cognitive, fatigue; if not corrected immediately can cause death. The purpose of this study is to design a dehydration and urine pH detection devices automatically. The contribution of this study is that this device is equipped with urine pH measurement and automatic body fluid calculation. This device is able to detect urine color levels, read urine pH values ​​, and provide information on body fluids needed to treat the patient's condition when detected. The sensors used in this device are color sensor TCS34725, pH meter sensor module SKU-016 and DS18B20 temperature sensor, the calculation of the amount of fluid that must be entered automatically from the patient's body weight input. The programming uses Arduino Nano as the main controller with a 128x64 graphic LCD. From the testing that has been done, it is known that the percentage error in the module is 3.5%, which means that it is still in the tolerance value because the tolerance limit is 5%, for the sensitivity test results get a value of 60% and specificity of 70%. Thus, it shows that the device is feasible and can be implemented as a dehydration detection device that is carried out independently at home

Measuring Respiration Rate Via Android

-Respiratory rate is the total number of breath or breathing cycle, which occurs every minute. Abnormal respiratory rate is a sensitive indicator for danger patients requiring medical treatment immediately. The objective of the study is to design respiration rate monitor via Anroid mobile phone. In this study, we used flex sensors to detect the respiration rate. The flex sensors was placed in the human stomach diaphragm which detects the changes in the human stomach diaphragm during breathing. The measurement results are displayed on the liquid crystal display (LCD) 2 x 16. The data  will be sent via a Bluetooth connection to the android to display the values ​​and graphs. The comparison between the design and standart showed that the maximum erros is 4.69% while the minimum error is 1.52%. The average error for all measurement is 2.83%. It can be concluded that the tool wear is eligible because it is still below the minimum threshold of 10% error

Design A Monitoring Device for Heart-Attack Early Detection Based on Respiration Rate and Body Temperature Parameters

Acute myocardial infarction, commonly referred to as a heart attack, is the most common cause of sudden death where a monitoring tool is needed that is equipped with a system that can notify doctors to take immediate action. The purpose of this study was to design a heart attack detection device through indicators of vital human signs. The contribution of this research is that the system works in real-time, has more parameters, uses wireless, and is equipped with a system to detect indications of a heart attack. In order for wireless monitoring to be carried out in real-time and supported by a detection system, this design uses a radio frequency module as data transmission and uses a warning system that is used for detection. Respiration rate was measured using the piezoelectric sensor, and body temperature was measured using the DS18B20 temperature sensor. Processing of sensor data is done with ESP32, which is displayed wirelessly by the HC-12 module on the PC. If an indication of a heart attack is detected in the parameter value, the tool will activate a notification on the PC. In every indication of a heart attack, it was found that this design can provide notification properly. The results showed that the largest respiratory error value was 4%, and the largest body temperature error value was 0.55%. The results of this study can be implemented in patients who have been diagnosed with heart attack disease so that it can facilitate monitoring the patient's condition