Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia
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Embedded Machine Learning on ESP32 for Upper-Limb Exoskeletons Based on EMG
Stroke remains one of the primary causes of long-term disability worldwide and frequently results in persistent impairment of upper limb motor function. To support more effective and intensive rehabilitation, there is a need for wearable devices that can interpret muscle activity and autonomously assist limb movement without relying on an external computer. This study aims to design and implement an upper-limb rehabilitation exoskeleton that is driven by electromyography (EMG) signal classification using machine learning and by real-time elbow angle monitoring, with all models deployed directly on an ESP32 microcontroller. The proposed exoskeleton is built from lightweight, ergonomic 3D-printed components and operates in both unilateral and bilateral modes. Its main contributions include: (1) embedding real-time EMG classification models on the ESP32 so that the device can function independently, (2) integrating EMG-based motor control with elbow angle feedback from an MPU6050 inertial measurement unit, and (3) incorporating a load cell to estimate biceps force during training. EMG signals from the forearm flexor muscles are processed to extract statistical features such as variance (VAR), waveform length (WL), integrated EMG (IEMG), and root mean square (RMS). These features are used to train Random Forest, Decision Tree, Support Vector Machine (SVM), and XGBoost classifiers. The trained models are converted to C code using the micromlgen library for execution on the ESP32. System evaluation involved thirty male participants aged 20–25 years with body weights between 50–85 kg. All tested models achieved 100% accuracy in distinguishing relaxed versus grasping muscle contractions, while the correlation of elbow angles between unilateral and bilateral ESP32 systems reached 0.9469, indicating highly consistent motion detection. The Decision Tree model was selected for deployment due to its superior memory efficiency on the microcontroller. These results demonstrate that the developed ESP32-based exoskeleton provides a practical, efficient, and easily integrable solution for wearable stroke rehabilitation
Exoskeleton; Machine Learning; EMG; ESP32; Stroke Rehabilitation
Copyright (c) 2025 Triwiyanto Triwiyanto, Anita Miftahul Maghfiroh, Levana Forra Wakidi, Syevana Dita Musvika (Author) https://creativecommons.org/licenses/by-sa/4.0
Development of an Android-based Stroke Prevention Application
Stroke remains a significant public health problem in Indonesia, with a prevalence of 8.3 per 1,000 population and a significant contribution to disability and mortality. Limited community health literacy and underutilization of digital health media indicate the need for accessible technology-based stroke prevention interventions. This study aimed to develop and validate a community-oriented Android-based application for stroke prevention using an ADDIE-based Research and Development framework. This study contributes a validated mobile health intervention for community stroke prevention and a replicable development model adaptable to other non-communicable disease prevention programs. The development process included application design, feature and database construction, internal testing, expert validation, and small-group usability testing. experts. Media validation involved three instructional technology experts. A small-group usability test was conducted with 15 adult community members in Banjar Regency, selected through convenience sampling. Data were analyzed using descriptive statistics and feasibility classification. The application obtained a mean score of 4.7 from material experts and 4.9 from media experts, indicating a “Highly Feasible” classification. Usability testing showed an overall mean score of 16.8 out of 20, reflecting strong user acceptance. This study is limited by its small sample size and short-term evaluation without behavioral or clinical outcome assessment. Nevertheless, the application shows potential as a digital health education tool to improve stroke prevention literacy and support community-based prevention programs and national digital health strategies.
Copyright (c) 2025 Khairir Rizani, Norlaila Sofia, Ferry Fadli Fratama, M. Rizki Imanuddin (Author) https://creativecommons.org/licenses/by-sa/4.0
Health Information Technology Management Model to Improve User Performance and Satisfaction
The rapid development of digital technology has reshaped the way healthcare institutions manage information, deliver services, and support clinical decisions. Despite these advances, many hospitals still struggle with inefficiencies resulting from weak Health Information Technology (HIT) governance and limited user skills. Most existing approaches prioritize technical deployment while paying less attention to managerial, organizational, and behavioral factors that are essential for sustainable success. To overcome these limitations, this study introduces and empirically evaluates a comprehensive Health Information Technology Management (HITM) model that combines strategic IT governance, system quality, and user dimensions to improve satisfaction and performance among healthcare professionals. The research examines how governance mechanisms, system quality, and user capabilities affect satisfaction and performance. The specific objectives are to identify the key drivers of system quality, evaluate the relationship between system quality and user satisfaction, and examine how satisfaction impacts user performance. The study contributes theoretically by presenting a more integrated framework that unites concepts from IT governance, Information Systems Success Theory, and Technology Acceptance Theory. It also offers empirical evidence of the importance of managerial structures in driving successful digital transformation in healthcare settings. A survey involving healthcare personnel from three public hospitals in Indonesia was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results demonstrate strong model validity, accounting for 65% of the variance in user satisfaction and 59% of the variance in performance, with predictive relevance (Q²) values of 0.47 and 0.52, respectively. These outcomes demonstrate that mature governance, leadership support, cross-unit collaboration, and systematic user training enhance system quality, satisfaction, and ultimately performance. Future studies should expand testing in broader healthcare contexts with different resource conditions.
Health Information Technology Management; User Satisfaction; User Performance; System Quality;
Copyright (c) 2025 Nining yuniati (Author); Nugroho (Translator) https://creativecommons.org/licenses/by-sa/4.0
Development and Usability Evaluation of the "Si BINTANG" Audiovisual Web Application for Integrated Child Growth and Development Monitoring
Indonesia’s child growth monitoring system, essential for national stunting prevention, still relies on paper-based tools such as the Child Health Card (KMS), which often face challenges of low parental engagement, fragmented data management, and limited health literacy. Existing digital applications primarily function as data logbooks, lacking interactive audiovisual content that can effectively support parents with diverse literacy levels and learning needs. This gap highlights the urgency for innovative health communication strategies that bridge conventional and digital media to enhance participatory learning and improve community-based child monitoring practices. This study developed and evaluated Si BINTANG (Interactive Barcode-Based Growth and Development Information System). This hybrid audiovisual web platform connects a printed child monitoring book with digital content through QR code technology. The application was designed using a user-centered and health communication approach to enhance parental understanding, motivation, and engagement in monitoring their child's growth and development. A preliminary usability evaluation involving experts and mothers of children under five indicated high system quality, usability, and user acceptance, demonstrating positive responses across functionality, accessibility, and user satisfaction. These results suggest that hybrid digital–print integration can enhance health education by making it more interactive, inclusive, and accessible for families, particularly in low-literacy or resource-limited settings. While the findings show encouraging potential, this study acknowledges several limitations, including the small and localized sample size. Future research will focus on large-scale implementation and impact assessment on parental knowledge, behavioral change, and child health outcomes. The Si BINTANG platform represents a promising direction for strengthening family-based stunting prevention through hybrid digital innovation, contributing to Indonesia’s ongoing digital health transformation and community empowerment agenda.
Child growth monitoring; Digital health intervention; Stunting prevention; Hybrid health education; QR code technology
Copyright (c) 2025 Norlaila Sofia, Hapisah, Noor Adha Aprilea, Rusmilawaty, Yuniarti, Zakiah (Author) https://creativecommons.org/licenses/by-sa/4.0
Vision Transformer Enhanced by Contrastive Learning: A Self-Supervised Strategy for Pulmonary Tuberculosis Diagnosis
Tuberculosis (TB) diagnosis from Chest X-ray (CXR) images poses a significant challenge in radiology due to the inherent data imbalance and subtle lesion heterogeneity. These factors cause traditional deep learning models, like standard CNNs and conventional Vision Transformers (ViT), to exhibit poor generalization and inadequate sensitivity (recall) for the minority TB class. We address this critical research gap by introducing a novel methodology, an enhanced ViT architecture that leverages Self-Supervised Learning (SSL) via the SimCLR framework, subsequently optimized with an Adaptive Weighted Focal Loss. Our primary objective was to develop a generalizable model that minimizes false negatives without sacrificing overall precision, thereby establishing a new performance benchmark for automated TB detection. The methodology conceptually separates feature learning from SSL pre-training on unlabeled data to generate robust and domain-invariant features, distinct from classification optimization. Adaptive Weighted Focal Loss is employed during fine-tuning to counter majority class gradient dominance mechanistically. We validated this approach using K-Fold Cross-Validation. The final ViT SSL Weighted model achieved a peak internal accuracy of 0.9861 and an AUPRC of 0.9781. Crucially, it maintained generalization stability when externally tested on the TBX11K dataset, securing an AUPRC of 0.9795 and a high recall of 0.9527. This minimal variance strongly confirms the reproducibility and robustness of our features against institutional variation. The resulting high recall directly translates to enhanced diagnostic decision-making, significantly lowering the clinical risk associated with a missed TB diagnosis. This study establishes an effective, stable, and generalizable SSL-based ViT framework, offering a scalable solution for public health efforts in resource-constrained settings.
Copyright (c) 2025 Widia Marlina, Umar Zaky (Author) https://creativecommons.org/licenses/by-sa/4.0
The Effect Of Time Variation and Sodium Chloride (NaCl) Concentration In The Sedimentation Method On Soil-Transmitted Helmints (STH) Examination
Soil-transmitted helminths (STH) remain a significant public health concern, particularly in regions with inadequate sanitation. While the sedimentation method is routinely employed for STH diagnosis, the effects of procedural variables such as incubation time and sodium chloride (NaCl) concentration on recovery efficiency remain inadequately explored. This study aimed to evaluate the influence of variations in sedimentation time and NaCl concentration on the detection and morphological integrity of STH eggs in stool samples. This contributes to more reliable diagnostic results in laboratory settings, supports epidemiological surveillance, and enhances the accuracy of STH monitoring in endemic areas. A controlled experimental design was implemented, utilizing 48 treatment combinations that varied in NaCl concentration (2%, 4%, 6%, and 8%) and sedimentation duration (5, 10, 15, and 20 minutes). Stool samples naturally infected with Ascaris lumbricoides, Trichuris trichiura, and hookworm were processed and examined microscopically for egg count, morphology, and sedimentation quality. Data normality was assessed using the Shapiro–Wilk test, and differences among treatment groups were analyzed with the Kruskal–Wallis test followed by post-hoc pairwise comparisons. Results demonstrated that both NaCl concentration and sedimentation time significantly influenced egg recovery (p < 0.05), with 2% NaCl and 30 minutes yielding the highest recovery rate and optimal morphological preservation. Morphological assessment revealed that prolonged sedimentation (>40 minutes) resulted in noticeable egg deformation, potentially compromising identification accuracy. These findings highlight the critical importance of optimizing procedural parameters in routine STH diagnostics. Adjusting NaCl concentration and sedimentation time can enhance both quantitative recovery and qualitative morphological assessment, thereby improving diagnostic reliability in clinical and epidemiological settings. In conclusion, the study provides evidence-based recommendations for sedimentation protocols, bridging a methodological gap and offering practical guidance for parasitology laboratories aiming to enhance the accuracy of STH examinations.
Soil transmittedHelminths; Stool examination; Sedimentation method; Sodium chloride; Centrifugation time.
Copyright (c) 2025 Acivrida Mega Charisma, Arina Wahyuningrum (Author) https://creativecommons.org/licenses/by-sa/4.0
Analyzing the Sociodemographic and Psychological Factors Influencing the Intention to Consume Single-Use Plastics Among University Students: A Cross-Sectional Quantitative Study
The rising use of disposable plastics among Indonesian university students contributes to the growing problem of plastic waste, making it essential to understand the factors shaping their intentions to use single-use plastics. This research aims to determine the impact of sociodemographic factors (age, education level, and economic status) and psychological factors (subjective norms, emotional motivation, and beliefs) on the intention to use disposable plastic among university students. The study contributes by integrating the Theory of Planned Behaviour (TPB) and the Value-Belief-Norm (VBN) Theory to explain the intention to consume single-use plastics in the Indonesian context, identifying the belief variable as the most dominant factor influencing behavioral intention. The research employed a quantitative descriptive-analytical approach with a cross-sectional design, conducted from April to June 2024. A total of 125 respondents were selected using purposive sampling. Data were collected through questionnaires developed based on the TPB and VBN frameworks, then analyzed using descriptive statistical tests and multivariate logistic regression to identify significant predictors of behavioral intention. The results show that sociodemographic factors, age (p = 0.002), education level (p = 0.000), and economic status (p = 0.000), significantly influence the intention to consume disposable plastics. Likewise, psychological factors, subjective norms (p = 0.001), emotional motivation (p = 0.000), and beliefs (p = 0.000), also have a significant effect, with beliefs emerging as the most dominant factor (Exp(B) = 10.234). The study implies that efforts to reduce single-use plastic consumption among university students should focus on strengthening environmental education and transforming social norms to foster sustainable behaviors. Furthermore, future research with longitudinal designs and broader populations is recommended to enhance the generalizability of these findings.
Copyright (c) 2025 Alprida Harahap, Adi Antoni, Haslinah Ahmad , Anton J. Hadi, Nanda Masraini Daulay (Author) https://creativecommons.org/licenses/by-sa/4.0
Isolation, Quantification, and Plaque Morphology Analysis of Lytic Bacteriophages from River Water Targeting Clinical MDR Klebsiella pneumoniae Using the Double-Layer Agar Method
Antimicrobial resistance is a growing global health threat and is projected to cause up to 10 million deaths per year by 2050. Klebsiella pneumoniae is a priority pathogen due to its multidrug resistance (MDR) mechanisms, such as extended-spectrum β-lactamases and carbapenemases, which significantly limit therapeutic options and increase the need for antimicrobial alternatives. This study aimed to isolate and quantify active lytic bacteriophages capable of infecting clinical MDR K. pneumoniae from river water samples. Water samples were processed by centrifugation and membrane filtration to remove debris and bacterial cells, then incubated with MDR K. pneumoniae in Luria broth at 37°C to enhance phage adsorption and amplification. Phage detection and enumeration were performed using the double-layer agar method. Plaque morphology was observed to confirm lytic activity, while serial dilutions were used to determine phage titer. Several lytic bacteriophages were successfully isolated from river water samples. The plaques formed were clear, spherical, and well-defined, with some exhibiting halos indicative of possible depolymerase activity. Phage titers ranged from 1.28 × 10³ to 2.00 × 10⁶ PFU/mL, indicating efficient replication against MDR K. pneumoniae without repeated enrichment processes. River water is a potential source of lytic bacteriophages capable of infecting MDR K. pneumoniae. These findings emphasize the role of aquatic environments as natural reservoirs of phages with potential use in the development of future antimicrobial or biocontrol strategies and support the need for further studies on the host range, stability, and therapeutic applications of the isolated phages.
Multidrug-resistant (MDR) Klebsiella pneumoniae;
Copyright (c) 2025 Aminah Aminah, dr. Citra, Fitri Alina Sugianto, Gadis Amalia, M Atik Martiningsih, Zulfikar Husni Faruq (Author) https://creativecommons.org/licenses/by-sa/4.0
Quasi-experimental study on Aloe Vera Gel As A Phytotherapy to Accelerate Perineal Wound Regeneration In Postpartum Mothers At Bpm Pera
Perineal wounds are one of the most common complications in postpartum women, causing pain, increasing the risk of infection, and delaying recovery. The lack of effective, safe, affordable, and easily accessible therapies highlights a gap in perineal wound care practices, particularly in primary care. Aloe vera, which contains anti-inflammatory compounds and regenerative bioactives, has the potential to serve as an alternative phytotherapy, but clinical evidence of its effectiveness in perineal wounds remains limited. This study aimed to evaluate the effectiveness of aloe vera gel in accelerating perineal wound healing in postpartum women. The contribution of this research is to strengthen the practice of phytotherapy-based wound care that is safe, affordable, and applicable in primary health care facilities. The study used a quasi-experimental pre-post study design with a control group. Thirty postpartum women with grade I–II perineal wounds were divided into a treatment group (Aloe vera) and a control group (standard care). Healing was evaluated using the REEDA scale, and pain intensity was assessed using a Visual Analogue Scale (VAS) over seven days. Analysis was performed using an independent t-test with a significance level of 0.05. The results showed a significant difference between the two groups. The average healing time for the Aloe vera group was 4.20 days (SD 0.95), faster than the control group, which took an average of 7.00 days (SD 1.20). Statistical tests showed a p-value = 0.001, indicating significant effectiveness of Aloe vera application in accelerating tissue healing. In addition, REEDA and VAS scores on the seventh day were consistently lower in the treatment group, indicating a faster reduction in inflammation and pain. Implicitly, these findings provide a clinical contribution to strengthening safe and affordable phytotherapy-based wound care practices for postpartum mothers, particularly in primary healthcare facilities. This study concluded that aloe vera gel is an effective complementary therapy for accelerating perineal wound healing and improving maternal comfort.
Perineal Wounds, Phytotherapy, Postpartum Mothers, Aloe Vera, Regeneration.
Copyright (c) 2025 basaria, Retno Wahyuni, Hariati Eliana Purba, Isyos Sari Sembiring, Eva Ratna Dewi, Nopalina Suyanti Damanik, Titis Jernih Wati Gea (Author) https://creativecommons.org/licenses/by-sa/4.0
Smart Screening Technology for Diabetes Risk: FFQ and FINDRISC Integration in a Digital Platform
Diabetes mellitus (DM) is a growing metabolic and autoimmune-related disease whose early onset is increasingly observed among young adults, including the university students in Indonesia. The existing screening models are either costly, invasive, or fail to integrate lifestyle data, leaving a gap for practical yet scalable solutions in this population. This study introduces a smart screening technology that combines the Food Frequency Questionnaire (FFQ) and the Finnish Diabetes Risk Score (FINDRISC) within a digital platform to capture both dietary patterns and individual risk factors. A cross-sectional design was applied to 110 undergraduates, chosen to reflect young adults most vulnerable to lifestyle-related DM risks. Data were collected entirely online to ensure feasibility and low-cost scalability in campus and public health programs. Multiple linear regression revealed that both individual factors (age, gender, BMI, physical activity, family history) and dietary patterns were significant predictors of DM risk (β = 0.312; β = 0.389; p < 0.001), explaining 37.4% of the variance. Compared to prior studies that relied solely on clinical or genetic markers, this integration highlights the added predictive value of dietary data in digital risk screening. With 70.9% of respondents at moderate and 25.5% at high risk, the findings underscore the urgent need for early intervention among Indonesian students. The proposed model offers practical applications through university health centers, mobile apps for student lifestyle monitoring, and peer-based preventive education. Future work should extend to biomarker validation and adaptive algorithms to enhance predictive accuracy and applicability across diverse populations.
Copyright (c) 2025 Yuswanto Setyawan (Author) https://creativecommons.org/licenses/by-sa/4.0
SERAYA: A Mobile App for Mental Health with Personalized Self-Healing Recommendations Based on Psychological Assessment
Mental health disorders are a crucial public health issue in Indonesia, as reflected in the 2023 National Health Survey (SKI), which reported that 2.0% of the population aged ≥15 years old were diagnosed with mental health problems, and approximately 20% of the 250 million people experiencing mental health problems do not yet have access to adequate services. Although many previous studies have developed digital applications, such as “Serenity” and “CERDAS” in Indonesia for psychological assessment using instruments such as the DASS-21, these applications only provide general recommendations and do not provide personalized self-healing guidance. To address this gap, this study developed and tested “SERAYA”, a mobile application designed not only to assess mental health levels but also to provide self-healing recommendations. This application integrates two standard instruments, the DASS-21 and the PSS-10, to measure depression, anxiety, stress, and perceived stress. A rule-based expert system using forward chaining processes the assessment scores; for example, “IF DASS-21 depression score ≥ 28 THEN recommendation = ‘CBT Therapy’”. Based on this score, the system generates specific recommendations or direct referrals to mental health professionals for severe cases. SERAYA's functionality was verified through successful black-box testing. Initial usability assessments using the System Usability Scale (SUS) with 11 respondents yielded an average score of 80.68, indicating good usability and ease of learning for early users. While these initial results are encouraging, they are derived from a limited, non-clinical sample and cannot be generalized to the entire Indonesian population. Overall, this study demonstrates that “SERAYA” serves as a viable proof-of-concept for providing personalized early mental health support and illustrates the potential of rule-based systems in digital health applications. Future research should focus on larger-scale validation, clinical integration for professional referrals, and the application of machine learning techniques to enable dynamic and tailored personalization.
Copyright (c) 2025 Enggi Wira Praja Putri Taufani (Author), Umar Zaky https://creativecommons.org/licenses/by-sa/4.0
Effectiveness of Using Analog Grid and Virtual Grid in Thoracic Radiography Examination
Chest radiography is essential for diagnosing thoracic abnormalities, but scattered radiation often reduces image contrast and diagnostic accuracy. Conventional analog grids mitigate scatter yet increase patient dose, while virtual grids offer digital correction with potentially lower radiation exposure. This study aimed to compare image quality and radiation efficiency between analog and virtual grids in thoracic radiography, contributing empirical evidence on the feasibility of adopting virtual grids as safer and more efficient alternatives. Three imaging protocols (Analog Grid, Virtual Grid 1, and Virtual Grid 2) were compared using identical exposure parameters on a phantom. Image quality was evaluated both objectively and subjectively. Results showed that Virtual Grid 2 achieved the highest score (4.47), slightly outperforming the Analog Grid (4.20) despite using lower radiation, while Virtual Grid 1 scored the lowest. ANOVA confirmed significant differences among the three methods, though the t-test between Analog Grid and Virtual Grid 2 showed no significant difference. A moderate negative correlation indicated that a reduced dose does not always compromise image quality when supported by advanced processing. In conclusion, Virtual Grid 2 demonstrates strong potential as a reliable alternative to analog grids, enabling excellent image quality with minimal radiation and supporting safer radiographic practices.
Copyright (c) 2025 Ayu Mahanani, Anshor Nugroho, Arnefia Mei Yusnida (Author) https://creativecommons.org/licenses/by-sa/4.0
Early Detection of Biliary Atresia through Quantitative Ultrasound Imaging: A Retrospective Analysis of Key Diagnostic Features
Biliary atresia (BA) is a progressive fibroinflammatory obstruction of the intra- and extrahepatic bile ducts, accounting for approximately 25–30% of neonatal cholestasis cases worldwide. Delayed diagnosis significantly increases the risk of liver failure and the need for transplantation. This study aimed to evaluate the diagnostic value of specific ultrasonographic parameters triangular cord sign, hepatic artery to portal vein (HAD/PV) ratio, and hepatic subcapsular flow (HSF) in the early detection of BA. A retrospective observational analytic study was conducted at Dr. Soetomo General Academic Hospital, involving 82 neonates with cholestasis between January 2019 and December 2023. Ultrasound images acquired using the GE LOGIQ Series E9 XDClear 2.0 were reviewed by blinded pediatric radiology consultants via the HOROS DICOM viewer. Statistical analysis revealed that both the triangular cord sign (p = 0.024; OR = 3.158) and hepatic subcapsular flow (p = 0.003; OR = 5.635) showed significant association with BA, while the HAD/PV ratio did not reach statistical significance (p = 0.087). Triangular cord sign and hepatic subcapsular flow are reliable sonographic markers that support early diagnosis of biliary atresia, whereas the HAD/PV ratio showed limited diagnostic relevance in this cohort. These findings reinforce the utility of non-invasive ultrasound imaging in differentiating BA from other causes of neonatal cholestasis. Incorporating these parameters into routine neonatal screening protocols may facilitate earlier surgical intervention and improve long-term outcomes
Copyright (c) 2025 Lenny Violetta, Dian Nurhayati, Ryan Elmanar (Author) https://creativecommons.org/licenses/by-sa/4.0
Comparative in Vitro Antibacterial Activity of Red Ginger (Zingiber Officinale Var. Rubrum) Extract and Conventional Antibiotics Against Pathogenic Escherichia Coli
The increasing incidence of antibiotic resistance in Escherichia coli poses a significant challenge to public health, as the effectiveness of conventional antibiotics such as ciprofloxacin continues to decline due to the emergence of resistant E. coli strains. This study aims to evaluate red ginger extract's in vitro antibacterial activity against Escherichia coli and determine the optimal concentration for bacterial inhibition. This research aims to determine the effectiveness of red ginger extract with concentrations of 60%, 80% and 100% on the growth of Escherichia coli. Research method using a laboratory-based experimental study was conducted using red ginger extract prepared via ethanol maceration at concentrations of 60%, 80%, and 100%. The extract's antibacterial activity against E. coli was evaluated using the disc diffusion method following CLSI guidelines, with ciprofloxacin (500 mg) as a positive control and 95% ethanol as a negative control. Each treatment was replicated five times. Inhibition zones were measured after 24 hours of incubation at 37°C. The results of the study show that red ginger extract demonstrated significant antibacterial activity against E. coli, with mean inhibition zones of 6.08 ± 0.98 mm, 6.48 ± 1.21 mm, and 5.20 ± 1.89 mm for 60%, 80%, and 100% concentrations, respectively. The 80% concentration showed optimal inhibition activity, while the higher concentration (100%) demonstrated reduced effectiveness. Statistical analysis confirmed significant treatment differences (p < .001, η² = 0.967). The positive control produced significantly larger inhibition zones (23.16 ± 1.67 mm, p < .05). This study concludes that red ginger extract exhibits moderate antibacterial activity against E. coli in vitro, with 80% concentration showing optimal efficacy. These findings suggest potential applications in developing natural antimicrobial agents, although further research is needed to elucidate mechanisms of action and evaluate clinical applications.
Copyright (c) 2025 Isramilda Isramilda, Andi Ipaljri, Kinanthi Amalia Putri (Author) https://creativecommons.org/licenses/by-sa/4.0
Monitoring the Occurrence of Alarms in Internet of Things-Based HFNC With Analysis of Signal Increases Before Blockages Error
HFNC must be closely monitored by nurses to increase the flow rate when the patient's condition worsens. The monitoring occurs every hour to assess the results of HFNC administration. If the patient's condition persists, the flow given to HFNC will be increased. Thus, careful monitoring is essential during oxygen therapy with HFNC to ensure the patient's oxygen dose remains consistent. Despite debates about aerosol side effects, HFNC has proven effective in increasing blood oxygen levels and improving lung performance. This study aims to analyze HFNC errors leading to decreased flow. The research employs a temperature setting of 34ºC and a flow setting of 30-60 LPM. Under a flow setting of 30 LPM, the average pressure value before the error is 0 in process 2, and after the error, it remains 0, indicating a Blockage error as notified by IoT. Similarly, under the same flow setting, the average pressure value before the error is 0 in process 1, and after the error, it remains 0, indicating a leaking error based on the IoT notification and tool condition. The study reveals an average error of 3.8 for Blockage and 1.5 for Leaking conditions. Future research could explore developments such as employing a more sensitive pressure sensor, like the MPX5010DP, and incorporating batteries to enhance the module's portability without the need for a voltage source.
Copyright (c) 2023 Dwi Widyaningtyas, Muhammad Ridha Mak’ruf, Andjar Pudji https://creativecommons.org/licenses/by-sa/4.0
Enhancing Accuracy in Mycobacterium Tuberculosis Counting on Acid-Fast Bacteria Sputum through Microscope Camera and Image Processing with Thresholding Method
Tuberculosis (TB) is a chronic infectious illness. Pulmonary TB is still a global threat and concern. Currently, TB is among the top 10 causes of death in the world in 2015 and it is estimated that there are around 10.4 million new cases of TB in the world. 6 countries account for around 60% of new cases in the world: India, Indonesia, China, Nigeria, Pakistan, and South Africa. Globally, the TB death rate was around 22% of total world deaths from 2000 to 2015. This study introduces an innovative tool, the "Microscope Camera for Enhanced Mycobacterium Tuberculosis Counting in Acid-Fast Bacteria Sputum through Image Processing with Thresholding Method," designed to revolutionize the examination of tuberculosis (TB) samples. In response to the global threat of Pulmonary Tuberculosis, the tool employs a state-of-the-art CMOS-HD (Complementary metal-oxide semiconductor High Definition) camera module and leverages the Python application for efficient image processing. The primary objective is to address the limitations faced by conventional diagnostic methods, particularly the challenges associated with the Rapid Molecular Test Method due to its dependence on expensive equipment, thereby making it less feasible for implementation in resource-constrained public health centers. The study underscores the persistent threat of TB as a global health concern, emphasizing its prevalence, with approximately 10.4 million new cases worldwide. Focusing on Ziehl-Neelsen stain sputum samples, the research seeks to elevate the accuracy of TB diagnosis by proposing a streamlined approach. This involves integrating a digital microscope system with a CMOS-HD camera module and utilizing advanced image processing techniques, specifically the Python Thresholding method. In the methodology, the research outlines a comprehensive data collection and analysis process. Mechanical and block diagrams illustrate the design of the module, while the system flow diagram elucidates the sequence of steps involved in TB sample analysis. The data analysis section employs metrics such as average, percentage error, and success percentage, providing a quantitative assessment of the system's performance. The results reveal an encouraging average system accuracy of 85.30%, demonstrating the potential of the developed tool to enhance the diagnostic process. However, the study transparently acknowledges areas for improvement, particularly in addressing discrepancies between manual and system calculations. The conclusion emphasizes the tool's promising role in assisting healthcare workers in detecting and counting TB bacteria in sputum, underscoring the need for ongoing refinements to achieve a definitive 100% accuracy and eliminate the possibility of misdiagnoses.
Tuberculosis, Python, Acid-Fast Bacteria
Copyright (c) 2024 Achmad Agus Sholichuddin, and M. Prastawa Assalim T.P https://creativecommons.org/licenses/by-sa/4.0
Exploring Digital Filters for Cardiac Monitoring: A Focus on Carotid Pulse and Phonocardiogram Signals
Heart defect early detection and correct diagnosis have become important healthcare priorities. Tools for monitoring cardiac problems are constantly being developed, with the PCG (Phonocardiogram) and Cardiac Monitor via Carotid Pulse essential for heart evaluation. Although condenser microphones embedded in electric stethoscopes have been used in past research as PCG sensors, more advancements are still required to reduce received noise. This study investigates how well a Chebyshev type-II digital filter works to reduce noise on the cardiac monitor using PCG and carotid pulse. The PCG sensor is the GY-MAX 9814 module, which is interfaced with an Arduino Uno microcontroller. Matlab, Visual Studio (used as a graph viewer), and Doppler Simulator (used as a phantom cardiac signal) are used. SNR (Signal to Noise Ratio) is used in the analysis to assess the effectiveness of two digital filter orders. The average SNR value for the Doppler Simulator is 0.001404 dB at order 2, however, it climbs dramatically to 18.60023 dB at level 4 according to the results of the SNR analysis. The average SNR value in human signals is 11.50718 dB before the filter, 0.001404 dB after the post-order 2 filter, and 12.0009 dB after the post-order 4 filter. According to the results, the digital filter of order 4 is more effective in reducing noise. This study highlights the possibility of an order 4 digital filter to improve the Cardiac Monitor through PCG and Carotid Pulse. Through enhanced signal quality, the creation of this gadget holds the potential for streamlining the identification of cardiac problems. Future developments in this technology could lead to more precise and trustworthy cardiac exams, which would help with early diagnosis and treatment of cardiovascular health.
GY-MAX 9814, Chebyshev Type II, Signal to Noise Ratio, Phonocardiogram
Copyright (c) 2024 Bahrurrizki Ramadhan, Endro Yulianto, Sari Luthfiyah and Wahyu Caesarendra https://creativecommons.org/licenses/by-sa/4.0
Improvement of Non-invasive Blood Sugar and Cholesterol Meter with IoT Technology
In checking blood sugar levels, patients often feel uncomfortable because invasive blood sampling must be done and if done to patients who have a history of high glucose, it can cause wounds that are difficult to heal and can be operated on. This study aims to non-invasively monitor cholesterol levels, reducing discomfort and pain for patients by eliminating the need for invasive procedures. The method used in this research is the MAX30102 sensor will detect blood sugar through the patient's finger, the data will be processed in ESP8266 as monitoring will connect to the OLED LCD as a viewer and IoT as data storage with WiFi connected. In this study, the greatest accuracy value was obtained 99.03% with the largest error value of 10.52% and the smallest accuracy value was 89.48% with the smallest error value of 0.97%. From all measurement results, the average accuracy value is 93.974% and the average error is 6.026%. It can be concluded that the development of a non-invasive method for monitoring blood sugar levels by utilizing the MAX30102 sensor with this accuracy value shows that this non-invasive method is reliable for monitoring blood sugar levels. In future studies, researchers are expected to use more accurate sensors and take more data to get a better average value.
Copyright (c) 2024 Ahmad Faisal Islamudin, Triana Rahmawati, Triwiyanto and Vugar Abudlayev https://creativecommons.org/licenses/by-sa/4.0
Non-Contact Respiration Monitoring Using Bio-Radar Sensor Based on Linear Regression Classifier
Tuberculosis (TB) is an infectious disease that mainly attacks the lungs, caused by the bacterium Mycobacterium tuberculosis. To reduce its spread, hospitals use special rooms for TB patients and health workers follow strict Standard Operating Procedures (SOP). Recent advances in medical technology have led to the development of contactless respiratory monitoring techniques, such as bio-radar sensors that utilize the Doppler principle to detect lung movement. This research aims to explore the application of bio-radar sensors for contactless respiratory rate monitoring and then combine it with machine learning methods, specifically using linear regression algorithms, to translate bio-radar output into measurable respiratory rate values. By training a regression model using a processed raw data set to identify inspiration and expiration, where 1 is inspiration and 0 is expiration. To test the performance of the contactless breathing module, it was compared to a patient monitor. The module and comparison tool were run simultaneously with 10 measurement distance points for 10 patients or respondents with each distance point taken three times. The data that has been obtained from the results of comparisons between modules and comparison tools is entered into machine learning data analysis techniques, namely accuracy, precision and recall. The accuracy results were 74.9%, precision 71.4% and recall 83.3%. This research has proven that bio radar can be used to detect lung movement.
Respiration, Bio-Radar, Artificial Intelligence, Linear Regression
Copyright (c) 2024 Muhamad Fahruidn Y., Syaifudin, Bambang Guruh Irianto, and Phuoc-Hai Huynh https://creativecommons.org/licenses/by-sa/4.0
Fuzzy Logic Method to Control Evenly Distributed and Stable Waterbath Temperature with Four Heaters
Water baths are commonly used in scientific fields to incubate samples at specific temperatures. The temperature of the water bath must be controlled precisely, because even the slightest temperature variation can affect the results of the experiment. It can handle imprecise, uncertain and incomplete information, making it suitable for temperature control in water baths. This research aims to determine the distribution and stability of fuzzy logic control to control the temperature of a water bath with four heaters. Even heat distribution from the four heaters will ensure consistent water bath temperature throughout the bath. This research uses an Arduino microcontroller to process the temperature sensor output from the DS18B20, then the processed temperature value will be displayed on the TFT LCD. The independent variable in this research is the temperature value, while the dependent variable is the DS18B20 temperature sensor. The largest error value from the module measurements is at a temperature setting of 30 ºC on the 2nd temperature sensor with an error value of 1.43%. Meanwhile, the smallest error value is found at a temperature setting of 35 ºC on the 1st and 4th temperature sensors with an error value of 0.01%. Data collection used a digital thermometer comparison tool with 10 repetitions as a temperature sensor reference tool. The results obtained using this sensor are more stable and have a high accuracy value. The results of the research show that the temperature difference between points 1 to 4 when viewed from the error percentage is very small, or it can be said that the temperature distribution is even. The conclusion from these results is that the module has a stable temperature value and the error value is low and is still within the tolerance limit. permitted is ±5%.
Waterbath, Fuzzy Logic, Temperature, DS18B20
Copyright (c) 2024 Rifqi Kurniawan, Syaifudin, Lamidi, and Shubhrojit Misra https://creativecommons.org/licenses/by-sa/4.0
Monitoring Oxygen Concentration and Humidity Parameters of Bubble CPAP Based on IoT
Existing Bubble Continuous Positive Airway Pressure (CPAP) devices used in neonatal care. Specifically, the lack of digital result display and monitoring capabilities for oxygen concentration and humidity parameters is identified as a major issue. This study aims to address the shortcomings of existing Bubble Continuous Positive Airway Pressure (CPAP) devices used in neonatal care by designing a monitoring system for oxygen concentration and humidity parameters. The lack of digital result display and monitoring capabilities for oxygen rate, concentration, temperature, and humidity necessitates an improved solution. The proposed system utilizes Internet of Things (IoT) technology, allowing remote monitoring by healthcare professionals. Oxygen concentration is detected using the OCS-3f sensor, and humidity is measured with the DHT22 sensor. Data from these sensors are processed by the ESP32 microcontroller and transmitted to the https://thinger.io site via built-in Wi-Fi. The monitoring tool ensures accurate measurements between 21% to 95% oxygen concentration, with a maximum error of 4.6% and a minimum error of 0.04%. This high accuracy enhances the reliability of the CPAP bubble device for oxygen therapy. The study's significance lies in its contribution to neonatal care, offering a real-time monitoring system that facilitates prompt diagnosis and treatment. By integrating IoT and telegram notifications, healthcare professionals can remotely monitor and respond to the baby's condition, improving overall care quality. This innovative tool holds promise in enhancing neonatal care, ensuring optimal oxygen therapy, and supporting the well-being of infants receiving CPAP bubble therapy. Implications of this study are promising in terms of improving neonatal care, enhancing the reliability of CPAP devices, and leveraging technology to facilitate better healthcare practices for the most vulnerable population: premature and critically ill infants.
Bubble CPAP, Oxygen Concentration, Humidity, OCS-3f, DHT 22
Copyright (c) 2023 Ratna Ika Puspitasari, Dyah Titisari, Lusiana dan Lamidi https://creativecommons.org/licenses/by-sa/4.0
PID Temperature Control of Baby Incubator Transport Battery Efficiency
Transport baby incubators are used to keep babies warm and safe while in transport using battery voltage sources or DC electricity, which are portable and can be used without getting a supply of electrical energy. The problem that often occurs with this tool is the limited battery power system. causes a risk to the infant in the event of power failure or battery exhaustion. We aim to evaluate the battery efficiency of Baby Incubator Transport using a PID temperature controller. The evaluation is done by comparing and analyzing the battery voltage of the device to the standard device, as well as considering the setting temperature and duration of use of the device so that it can provide convenience in evacuating babies in an emergency. The tool uses the PID method to control temperature and maximize battery power. In this design, researchers only look at the efficiency of the PID method on temperature control and the battery to be used. This module will have a display that will display the battery voltage value, battery voltage percentage, skin temperature, chamber temperature, humidity, and temperature control that has been selected in the form of a graph. Compared with the digital multimeter measuring instrument. From the results of data collection, it can be concluded that the PID method has a faster rise time to reach the setting temperature, while the fuzzy method has a longer rise time to reach the setting temperature. However, the PID method requires more battery power than the Fuzzy method. The measurement results between the display and the measuring device have a difference of 3.1% at 34°C, at 35°C it is 3.9%, and at 36°C it is 4.7%. The biggest error is at a temperature of 36ºC, the smallest is at a temperature of 34ºC. Based on the results of the observation analysis of battery power consumption, it is found that the smaller the battery energy, the smaller the current issued, as well as the voltage issued. But if the load is large, the current is inversely proportional to the center, the battery voltage decreases while the current increases.
Baby Incubator Transport, Battery Efficiency, PID Control
Copyright (c) 2024 Angga Vidaryanto, I.D.G Hari Wisana, Abd Kholiq, and Riqqah Dewiningrum https://creativecommons.org/licenses/by-sa/4.0
IoT-Based Human Vital Sign Monitoring Tool Using Telegram Notifications
Vital signs play a crucial role in monitoring the progress of adult or pediatric patients during hospitalization, as they enable prompt detection of delayed recovery or adverse events. Vital signs are measured to obtain fundamental indicators of the patient's health status. The measurement of vital signs, including blood pressure, temperature, pulse, and respiratory rate, is the most common intervention in hospital medicine. Advanced monitoring systems combine clinical and technological aspects to deliver innovative healthcare outcomes. Remote patient monitoring systems are increasingly becoming the cornerstone of healthcare delivery, replacing traditional manual recording with computer and smartphone based electronic recording as a versatile and innovative health monitoring system. This study aims to design a Vital Sign Monitoring Parameter BPM and RR tool with Notifications via the IoT-Based Telegram application. The tool enables the monitoring of vital signs, particularly BPM and RR, regardless of the patient's location and at any given time. This allows doctors, health workers, and patients to stay informed about their health condition. Real-time display of vital sign data is available through the TFT LCD screen, and the data from the screen can be accessed via Telegram. The Telegram application will send notifications in the event of abnormal patient conditions. MAX30100, a digital sensor for detecting breathing rate and heart rate, is utilized in this research. Furthermore, the data obtained shows errors that are within the allowable limits for each parameter. The difference between the heart rate readings and the respiratory rate values on the device and the patient monitor is 1.14% for heart rate and 0.84% for respiratory rate. This study indicates that it is time to monitor vital signs that can be seen remotely and have a system that is an inexpensive and easy-to-operate device for health workers without interfering with activities of daily living.
Smartband, Multiplexer, SEN0203, MLX90614, BPM, Temperature
Copyright (c) 2023 Rizky Dwi K, M. Prastawa Assalim Tetra Putra, Abdul Kholiq, Bedjo Utomo, Sumber, Triwiyanto and Yagnik Rathod https://creativecommons.org/licenses/by-sa/4.0
Development IoT-based Infant Monitoring System for Preventing Sudden Infant Death Syndrome (SIDS) with Abnormal Condition Notifications and Lost Data Analysis
Sudden infant death syndrome or SIDS is the sudden death of a healthy baby under 1 year of age that occurs without any symptoms. It can be triggered by various factors, ranging from the baby's sleeping position to the baby's physical condition that has not reached a certain stage of development. Checking the baby's body temperature and heart rate is a very important element to monitor the baby's condition. In addition, checking body temperature and heart rate can also prevent febrile seizures that can cause epilepsy. Therefore, a tool is needed that can monitor the body temperature and heart rate of babies in real time and with an efficient mechanism. The purpose of this research is to conduct real-time monitoring with vital parameters of Respiration Rate using Piezo Electric sensor and heart rate monitoring using MAX30100 sensor. This research method is the design of a respiration and heart rate monitoring tool using piezoelectric sensors and ESP 32. The measurement results show that the largest difference value with the comparison tool is 28.74% and the smallest is 0.00%. suggestions and recommendations in this study on the right sensor placement so that effective results are obtained and the output results can be accessed via the website by doctors and other health workers and the existence of telegram notifications if conditions are abnormal so as to prevent SIDS..
Copyright (c) 2023 Erick Dwi Ananta, Syaifuddin LiliekSoetjiatie, and Bedjo Utomo https://creativecommons.org/licenses/by-sa/4.0
Design of Ambulatory Blood Pressure Monitoring for IOT-Based Hypertension Patients
Ambulatory blood pressure monitoring or ABPM is a non-invasive method to determine the average blood pressure for at least 24 hours, not only when medical checkup. ABPM is often found in cardiac examinations and monitoring of catlab preoperative patients. This study aims to analyze the performance of the ABPM tool that can measure blood pressure continuously with a specified time interval connected to IoT so that can make it easier to get test results. The contribution of this research is a 24 hour monitoring system with delivery via IoT. The experiment was conducted 10 times with Prosim comparison at each point to assess the level of reading accuracy and effectiveness of IoT viewers. At 120/80 mmHg systole accuracy 98.42%, diastole 97.25%. While at 150/100 mmHg systole accuracy is 99.67%, Diastole is 98.1%. At 200/160 mmHg point Systole accuracy 98.35%, Diastole 98.25%. The SPSS test states that the reading data collection is acceptable and has an average commensurate with the test. The difference in viewer time on the TFT and IoT layers is 3.8 seconds and the test data value is 0% loss. The results from making this module, concluding by utilizing the sensor MPX5050 obtained sufficient accuracy, the use of ESP32 as a microcontroller processes the sensor readings which will be converted into systole-diastole values and displays on IoT so that it can slightly help analyze the patient's condition, and this module can read the simulator tool well at pressures of 120/80 mmHg, 150/100 mmHg, and 200/160 mmHg. The device showed good accuracy and reliability in measuring blood pressure at different levels compared to a vital signs simulator. The device can be used for 24-hour monitoring of hypertension patients and provide useful information for diagnosis and treatment.
ABPM, Hypertension, Blood Pressure, IoT, MPX5050
Copyright (c) 2024 Alvy Noorlatifa Sari, Priyambada C. N., Muhammad Ridha Mak’ruf, Her Gumiwang Ariswati, Moch. Prastawa Assalim T.P., and Anita Miftahul Maghfiroh https://creativecommons.org/licenses/by-sa/4.0
A Pioneering Study on the Design and Implementation of Bioradar Sensors for Luxurious Portable Non-Contact Respiration Monitoring
Respiratory disorders are a critical health problem. Respiration is a vital activity for the proper functioning of the body. Pandemic SARS-CoV-2 virus is a highly contagious disease and causes rapid spread of droplets. This study aims to determine the effectiveness of the bioradar sensor used in non-contact respiration monitoring by exploring the distance to find out the optimal distance for sensor readings in monitoring respiration rate per minute. The results of this study for the 3 treatments given to respondents did not affect the results of measuring respiration rate. At distances of 10 cm and 25 cm they produce 40-43 times/minute, distances of 50 cm and 75 cm produce 33-36 times/minute, distances of 100 cm produce 20-22 times/minute and distances of 125 cm and 150 cm are not detected. The highest error value is -100.00% at a distance of 125cm and 150cm and the lowest error value is 3.39% at a distance of 100 cm. based on the results of the analysis of the effectiveness of sensor readings on distance, which is quite effective at a distance of ±100 cm. It is hoped that this research can reduce the level of disease transmission during the Covid-19 pandemic. The results of the study showed that the three treatments given to respondents did not affect the results of respiratory rate measurements. At a distance of 10 cm and 25 cm, it produced 40-43 times/minute, at a distance of 50 cm and 75 cm it produced 33-36 times/minute, at a distance of 100 cm it produced 20-22 times/minute, and at a distance of 125 cm and 150 cm it was not detected. The highest error value is -100.00% at a distance of 125 cm and 150 cm, and the lowest error value is 3.39% at a distance of 100 cm. Based on the analysis of the effectiveness of the sensor reading at a distance, it was found to be quite effective at a distance of ±100 cm. The implication of this study is that this bioradar sensor is effective in monitoring breathing rate at a distance of about 100 cm. The results of this study are expected to reduce the level of disease transmission during the Cov-19 pandemic, as non-contact monitoring can help in avoiding droplet spread, which is one of the ways the virus is transmitted. This study provides important information on the use of bioradar sensors in non-contact monitoring of breathing that can be used to improve the safety and quality of healthcare, especially in the context of a pandemic.
SARS-CoV-2, bioradar, respiration, transmitter, receiver
Copyright (c) 2023 Waode Erimelga N , Her Gumiwang A , Sari Luthfiyah , and Kartinah Zen https://creativecommons.org/licenses/by-sa/4.0
Design and Implementation of a Web-Based Application for Media and Laboratory Reagents Management with QR Code Feature
Planning needs, purchasing, determining the availability of practical materials, and keeping an eye on the state of the actual or real amount are the first steps in practical material management operations. This task is completed to ensure the accuracy of the bookkeeping records in order to reduce variations in inventory levels. The goal of the study is to manage media practice materials and QR Code-based laboratory reagents as efficiently as possible. In this study using the Waterfall method which is included in the SDLC (Software Development Life Cycle) model. The laboratory equipment inventory application is made using a sublime text editor and uses PHP, HTML, CSS programming languages and bootstrap frameworks to make the application look more attractive. The system's use demonstrates the efficiency and precision with which data on laboratory equipment is recorded in order for the leadership to make decisions regarding the proper quantity of teaching and learning aids to be purchased. The unique feature of this system is the direct smartphone connection of the notification, which makes it simpler for users to keep track of inventory flow. The inventory service notification system through WhatsApp is expected to contribute to improving the quality of academic services and meeting the needs of its users. From the results of this study states that the application design used can be a solution in overcoming previous problems so as to achieve effective and efficient data collection activities.
aplication, media reagent, notification, stok opname, QR Code.
Copyright (c) 2023 Fira Kuswandari, Rahmi Susanti, Michael Alfian Grey, and Dewi Inderiati https://creativecommons.org/licenses/by-sa/4.0
Digital Filter Design to Reduce Motion Artifacts in Electrocardiogram Signals Based on IIR Filter
Developed a new method to overcome motion artifacts in Electrocardiogram (ECG) signals, which often interfere with accurate clinical analysis. Motion artifacts, such as body movements, can cause significant distortions in the ECG signal, resulting in incorrect interpretation and affecting medical diagnosis. The main objective of this research is to design and implement an infinite impulse response (IIR) filter with a predetermined sequence, namely orders 2, 4, 6, and 8 to reduce motion artifacts in the ECG signal. We aim to improve ECG signal quality by preserving important ECG signal information and reducing noise caused by motion artifacts. This research contributes to developing more precise and reliable ECG signal processing techniques. The proposed method provides an effective approach to handling motion artifacts, enabling more accurate and reliable ECG interpretation by medical professionals. We used an ECG simulator that provides body movement simulation as a basis for experiments. The detected ECG signal is processed with a predetermined order IIR filter. We compare the filtered signal to the original signal to measure the effectiveness of reducing motion artifacts. Experimental results show that the applied IIR filter efficiently reduces motion artifacts in the ECG signal. The SNR assessment showed a significant improvement, proving the success of this method in maintaining ECG signal quality. The result is that in the 2nd order, the SNR value is 22.25 dB, in the 4th order the SNR value is 22.75 dB, in the 6th order the SNR value is 22.99 dB, in the 6th order the SNR value is 22.99 dB. 8 obtained an SNR value of 23dB. This study successfully demonstrated that using IIR filters in a specified order effectively reduces motion artifacts in the ECG signal, increases SNR, and maintains the integrity of clinical information in the ECG signal. The implications of this research extend to medical technology development and clinical applications, providing a strong foundation for continued research in more efficient and reliable ECG signal processing.
Copyright (c) 2023 Anita Miftahul Maghfiroh, Singgih Yudha Setiawan, Muhammad Umer Farooq Mujahid https://creativecommons.org/licenses/by-sa/4.0
Bedside Monitor Based on Personal Computer Using STM32F7 Microcontroller
A vital sign examination is one of the important indications used to establish the diagnosis of a disease and is useful for determining the medical treatment plan needed for the patient. An electrocardiograph (ECG) is a parameter in medical equipment used in the process of measuring the electrical activity of the heart muscle by measuring biopotential differences from the body surface. In 2016, cardiovascular disease was the number-one cause of death in the world. This happens because the detection of cardiovascular disease is often late, so a monitoring tool is needed that can monitor the patient's condition quickly and efficiently. The purpose of this research is to create a tool that is used to facilitate the monitoring of patient conditions. The implication of this research is that in the many cases where the signal produced is not perfect and there is still a lot of noise, this can be overcome by using the STM32F7 microcontroller, which has a 16-bit resolution, so that the resulting signal will be better, smoother, and have less noise. produced is very small. The method used in this study was to use a phantom ECG as a comparison and to use five respondents whose BPM values were to be compared with another comparison using a pulse oximeter. The design of this tool uses an ECG analog circuit that is placed on the patient's lead II leads to detect the patient's electrocardiograph signal. Data processing will be done using the STM32F7 microcontroller, and the results of the data processing will be sent to the PC using Visual Basic. The results showed that the BPM error value using a phantom ECG was 2.5%. While the smallest error value is 0,83%. In BPM measurements using 5 respondents, the largest error value was 0.9% and the smallest error value was 0%. The results of these tests indicate that this module can be used to monitor the value of each parameter in accordance with the plan.
ECG Lead II, BPM , STM32F7 Nucleo, Visual Basic NET
Copyright (c) 2023 Ingga Ariestya Riswandhani, Priyambada Cahya Nugraha, and Syaifudin https://creativecommons.org/licenses/by-sa/4.0
NutriTalk: Nutrition Intervention by Experts to Reduce the Impact of Stunting Through Mobile Based Applications Using Agile Method
The prevalence of childhood stunting, a pervasive global health concern primarily attributed to persistent malnutrition, underscores an urgent need for intervention. In Indonesia, where stunting rates are alarmingly high, with approximately 27.6% of children under five affected, innovative solutions are imperative. This study introduces "Nutri Talk," a mobile application developed using Agile Methodology to revolutionize nutritional consulting services. The application facilitates seamless communication with nutrition specialists, offering evidence-based information and personalized consultations to empower parents in making informed dietary decisions for their children. The application demonstrates robust functionality and user satisfaction through rigorous testing, including Boundary Value Analysis (BVA) and User Acceptance Testing (UAT). "Nutri Talk" stands poised to mitigate the long-term impacts of stunting, leveraging technology to enhance nutritional outcomes. This research advocates for a comprehensive approach to combat stunting, combining mobile technology advancements with targeted interventions, ultimately contributing to improved childhood nutrition and development.
childhood stunting, Agile Methodology, nutrition consulting, Boundary Value Analysis (BVA), User Acceptance Testing (UAT)
Copyright (c) 2023 Arvita Agus Kurniasari, Zora Olivia, Arinda Lironika Suryana, Agatha Widiyawati, and Nita Maria Rosiana https://creativecommons.org/licenses/by-sa/4.0