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Heni Sumarti
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Journal of Holistic Medical Technologies
Published by Konsorsium Pengetahuan Innoscientia
ISSN : -     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Neuroscience
The Journal of Holistic Medical Technologies (JHMT) aims to advance the integration and application of diverse technological and scientific disciplines within the field of medical sciences. The journal aims to promote innovation and interdisciplinary research by publishing high-quality original research, reviews, and case studies that explore the intersection of medical physics, imaging technologies, electronics, herbal chemistry, and neuroscience. We aim to bridge the gap between theoretical and applied research, promoting holistic solutions to complex medical challenges. JHMT welcomes a broad range of submissions that contribute to these areas, aiming to integrate emerging technologies with traditional medical approaches to enhance patient care and expand scientific knowledge.
Arjuna Subject : Teknik (semua kategori) - Teknik Biomedis
Articles 5 Documents
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Search results for , issue "Vol. 1 No. 2 (2025): June" : 5 Documents clear
Electrical Capacitance Volume Tomography (ECVT) for real-time brain activity monitoring: a comparative frequency analysis study Hanin Aisya Fakihati; Seftina Diyah Miasary; Marlin Ramadhan Baidillah
Journal of Holistic Medical Technologies (JHMT) Vol. 1 No. 2 (2025): June
Publisher : Konsorsium Pengetahuan Innoscientia (KOPINNOS)

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Abstract

Current brain imaging modalities such as CT scan and MRI, while providing excellent anatomical detail, have limitations in real-time functional brain activity monitoring. Electrical Capacitance Volume Tomography (ECVT) emerges as a promising non-invasive, cost-effective alternative for dynamic brain activity assessment. This study aims to evaluate the sensitivity of ECVT technology in detecting brain motor activity variations across different frequencies and determine the optimal frequency for brain wave fluctuation measurement. A 16-electrode ECVT helmet system was employed to monitor brain activity in subjects performing motor stimulation tasks including hand gripping, imagined movement, and control conditions (water and empty space). Measurements were conducted at three frequency variations: 500 kHz, 1 MHz, and 5 MHz. Data acquisition involved multiple channel combinations (C14-16, C14-15, C14-13, C14-12, C16-15, C16-9, C16-8, C16-10) with voltage peak-to-peak (Vpp) measurements recorded via oscilloscope. The 500 kHz frequency demonstrated the highest sensitivity in detecting brain activity variations. Distinct Vpp patterns were observed across different motor tasks, with imagined movement producing the highest values, indicating increased neural activity. The ECVT system successfully differentiated between active motor tasks and resting states. ECVT at 500 kHz frequency shows superior sensitivity for brain activity monitoring, offering a portable, low-cost alternative to conventional neuroimaging modalities for real-time functional brain assessment.
Classification of diabetic retinopathy and normal fundus images based on texture features using Multilayer Perceptron (MLP) Ayu Wulandari; Heni Sumarti
Journal of Holistic Medical Technologies (JHMT) Vol. 1 No. 2 (2025): June
Publisher : Konsorsium Pengetahuan Innoscientia (KOPINNOS)

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Abstract

Diabetic retinopathy is a disease caused by uncontrolled blood sugar levels and occurs continuously. Funduscopic examination with an ophthalmoscope tool to determine diabetic retinopathy. This study aims to classify funduscopy images in distinguishing normal eyes and diabetic retinopathy based on texture characteristics using the multilayer perceptron (MLP) method. Texture feature extraction as a class recognition process that aims to produce characteristics based on the texture of each image. The texture features used are histogram and GLCM with 10 parameters. Research data is sourced from the Zenodo website and the National Library of Medicine. Based on the results of the study, it shows that the multilayer perceptron method with the help of Weka machine learning in classifying eye fundus images to distinguish normal eye cases and diabetic retinopathy produces an accuracy value of 83.75% at k-folds 20 cross validation with sensitivity and specificity values of 49.20% and 95.09%.
Analysis of urine pH measurement using Arduino UNO-based pH Sensor Achmad Safii; Muhammad Ghozali
Journal of Holistic Medical Technologies (JHMT) Vol. 1 No. 2 (2025): June
Publisher : Konsorsium Pengetahuan Innoscientia (KOPINNOS)

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Abstract

Naturally, humans possess excretory organs that function to eliminate metabolic waste products. Urine is one of the fluids resulting from metabolic waste in the body. Urine can serve as an indicator of actual body condition. Urine pH measurement is one of the easily accessible methods for determining the body's acid-base balance. The pH meter system for urine pH detection was constructed using a pH V1.1 sensor as hardware with Arduino Uno assistance as both hardware and software for program processing. This research focuses on designing a device to determine urine pH levels using the Research and Development (R&D) pH meter method. Device calibration using buffer solutions with pH values of 4.01, 6.86, and 9.18 yielded a device error value of 0.11% and standard deviation (S) = 0.0091. Testing was also conducted using 30 human urine samples from subjects aged 16 to 40 years. The tested urine samples were 100 ml each, with results showing pH values ranging from 4.86 to 6.97. The standard deviation (S) for urine sample testing was 0.081. The difference in standard deviation values between calibration and urine samples was attributed to probe cleanliness on the pH meter, emphasizing the importance of probe cleanliness when switching between samples.
Identification of istihadhah blood color using TCS3200 color sensor with Multilayer Perceptron (MLP) method Syukrotus Sa’diati; Heni Sumarti
Journal of Holistic Medical Technologies (JHMT) Vol. 1 No. 2 (2025): June
Publisher : Konsorsium Pengetahuan Innoscientia (KOPINNOS)

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Abstract

One of the natures of women, including menstruation, namely the discharge of blood from the vagina periodically and has a certain cycle. However, this cycle can experience disturbances, in Islam it is referred to as istihadloh. Women who are experiencing istihadloh are called mustahadloh. One of the mustahadloh categories is Mu'tadah Ghoiru Mumayyizah, namely women who have recently bled but cannot distinguish between strong and weak blood. This study aims to distinguish between menstrual blood and istihadloh based on its color. The research method was carried out by designing and manufacturing the TCS3200 color sensor tool based on Arduino Uno with RGB value output results. The average RGB value of istihadloh blood is R 71.6, G 83.7 and B 55.2. While the average RGB values for menstrual blood color are R 143.3, G 176.6 and B 79.3. The results of the classification accuracy using the MLP method in differentiating menstrual blood and istihadloh based on color using the TCS3200 color sensor are 96.7%.
Dose Analysis of Boron Neutron Capture Therapy (BNCT) in Brain Cancer Based on Cyclotron Using PHITS Application Simulation Muhammad Ghozali; Heni Sumarti
Journal of Holistic Medical Technologies (JHMT) Vol. 1 No. 2 (2025): June
Publisher : Konsorsium Pengetahuan Innoscientia (KOPINNOS)

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Abstract

One of the cancers is brain cancer, the most dangerous of which is Glioblastoma Multiforme (GBM). The research conducted aims to determine the effect of boron concentration on the boron dose rate, irradiation time and absorbed dose. Current cancer treatment still provides deterministic effects (tissue reactions) of radiation to patients and long therapy times. Therefore, researchers conducted research on Boron Neutron Capture Therapy (BNCT) in the treatment of cancer patients that is more selective in destroying cancer cells and is safe because it does not damage healthy tissues around it and the therapy requires a short time. The type of research conducted is quantitative experimental research. The research method with simulation uses the Particle and Heavy Ions Transport code System (PHITS) application on therapy process of Boron Neutron Capture Therapy (BNCT) for brain cancer patients type of Glioma grade 4 called Glioblastoma Multiforme. Patient modeling is based on the Oak Ridge National Laboratory-Medical Internal Radiation Dose (ORNL-MIRD) phantom in adult men who have a brain cancer diameter of 4 cm at a depth of 7 cm with a neutron source from a 30 MeV Cyclotron. The boron concentration used has 3 variations, as follows 20 μg/g, 40 μg/g and 60 μg/g of cancer tissue. Based on the results of the study at a boron concentration of 60 μg/g in the Gross Total Volume (GTV) organ or the center of cancer cells with a dose rate value of 11,160 x 10-2 Gy/s, thus accelerating the irradiation time within a period of 4 minutes 48 seconds and the absorbed dose increases by 30 Gy. Thus, it can be concluded that the higher the boron concentration, the faster the boron dose rate value, the greater the absorbed dose and the faster the irradiation time when carrying out brain cancer therapy.

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