Kinerja Ergonomi Sensor ECG AD8232 Dan Pulse Oximeter Dalam Penilaian Beban Kerja Fisiologis Industri Manufaktur
DOI:
https://doi.org/10.55642/phasij.v5i02.1196Keywords:
Kinerja ergonomi, ECG AD8232, CVLAbstract
Penelitian ini bertujuan untuk membandingkan kinerja ergonomi (menggunakan sensor Electrocardiogram ECG- AD8232 berbasis Internet of Things (IoT)) dan (pulse oximeter) melalui pengukuran % CVL pada 21 pekerja di industry manuaktur, serta menguji apakah terdapat perbedaan signifikan secara statistik dalam pengukuran antara kedua alat tersebut. Pengujian dilakukan dengan merekam data detak jantung secara real-time, di mana sensor AD8232 dihubungkan ke mikrokontroler ESP32 dan platform Blynk, sedangkan oximeter menggunakan metode photoplethysmography (PPG) dengan tampilan langsung pada layar. Hasil penelitian menunjukkan bahwa sensor AD8232 unggul dalam kestabilan pembacaan, akurasi sinyal ECG, dan dukungan pemantauan jarak jauh, sedangkan oximeter lebih unggul dalam kemudahan penggunaan. Hasil dari pengujian berpasangan pada subjek yang sama untuk Uji distribusi normal (Shapiro-Wilk) pada data selisih CVL menunjukkan nilai p-value (0.003) lebih kecil dari tingkat signifikansi (0.05) sehingga data selisih tersebut tidak terdistribusi normal, selanjutnya hasil uji non-parametrik Uji Wilcoxon menunjukkan nilai p-value (0.146) lebih besar dari tingkat signifikansi (0.05) menunjukkan tidak ada perbedaan signifikan dalam % CVL diantara kedua Alat, sehingga kedua alat tersebut menunjukkan kinerja yang serupa dalam hal variabilitas pengukuran % CVL dan masih bisa diterima sebagai alat alternatif pemantauan denyut jantung dan perhitungan CVL.
References
Almaadawy, O., Uretsky, B. F., Krittanawong, C., & Birnbaum, Y. (2024). Target Heart Rate Formulas for Exercise Stress Testing: What Is the Evidence? In Journal of Clinical Medicine (Vol. 13, Issue 18). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/jcm13185562
Bhattarai, C., Yadav, S. K., & Koirala, S. (2022). IoT Based ECG Using AD8232 and ESP32. Nepal Journal of Science and Technology, 21(2), 115–121. https://doi.org/10.3126/njst.v21i2.62361
Charan, J., & Biswas, T. (2013). How to calculate sample size for different study designs in medical research? In Indian Journal of Psychological Medicine (Vol. 35, Issue 2, pp. 121–126). https://doi.org/10.4103/0253-7176.116232
Coste, A., Millour, G., & Hausswirth, C. (2025). A Comparative Study Between ECG- and PPG-Based Heart Rate Sensors for Heart Rate Variability Measurements: Influence of Body Position, Duration, Sex, and Age. Sensors, 25(18). https://doi.org/10.3390/s25185745
Dahiya, E. S., Kalra, A. M., Lowe, A., & Anand, G. (2024). Wearable Technology for Monitoring Electrocardiograms (ECGs) in Adults: A Scoping Review. In Sensors (Vol. 24, Issue 4). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/s24041318
Dias, M., Silva, L., Folgado, D., Nunes, M. L., Cepeda, C., Cheetham, M., & Gamboa, H. (2023). Cardiovascular load assessment in the workplace: A systematic review. In International Journal of Industrial Ergonomics (Vol. 96). Elsevier B.V. https://doi.org/10.1016/j.ergon.2023.103476
Ersha Mayori et al. (2025). Pengembangan Sistem Pemantauan Kesehatan dan Keselamatan Kerja Berbasis IoT di Kawasan Industri Pulogading. 8. https://journal.universitaspahlawan.ac.id/index.php/jutin/article/view/50921/31453
Etiwy, M., Akhrass, Z., Gillinov, L., Alashi, A., Wang, R., Blackburn, G., Gillinov, S. M., Phelan, D., Marc Gillinov, A., Houghtaling, P. L., Javadikasgari, H., & Desai, M. Y. (2019a). Accuracy of wearable heart rate monitors in cardiac rehabilitation. Cardiovascular Diagnosis and Therapy, 9(3), 262–271. https://doi.org/10.21037/cdt.2019.04.08
Etiwy, M., Akhrass, Z., Gillinov, L., Alashi, A., Wang, R., Blackburn, G., Gillinov, S. M., Phelan, D., Marc Gillinov, A., Houghtaling, P. L., Javadikasgari, H., & Desai, M. Y. (2019b). Accuracy of wearable heart rate monitors in cardiac rehabilitation. Cardiovascular Diagnosis and Therapy, 9(3), 262–271. https://doi.org/10.21037/cdt.2019.04.08
Firescu, V., & Filip, D. (2025). Human Factors and Ergonomics in Sustainable Manufacturing Systems: A Pathway to Enhanced Performance and Wellbeing. Machines, 13(7). https://doi.org/10.3390/machines13070595
Fiyanto Roy Oktaf et al. (2024). Design and Development of a Heart Rate and Blood Oxygen Saturation Monitoring Device in Humans During Sleep Condition Based on the Internet of Things. Volume 7 Issue 1. DOI: https://doi.org/10.21009/JEVET.0071.05
Kraft, A. M., Velasco Garrido, M., Herold, R., Harth, V., & Preisser, A. M. (2023). Physical workload and cardiopulmonary parameters in relation to individual capacity of bulk waste workers – a cross-sectional field-study. Journal of Occupational Medicine and Toxicology, 18(1). https://doi.org/10.1186/s12995-023-00389-z
Lwanga, S. K., & Lemeshow, S. (1991). Sample size determination in health studies a practical manual. https://archive.org/details/isbn_9780471925170
Okuda, M., Kawamoto, Y., Tado, H., & Fujita, Y. (2025). Heart Rate Monitoring for Physiological Workload in Forestry Work: A Scoping Review. In Forests (Vol. 16, Issue 3). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/f16030520
Rehman, R. Z. U., Chatterjee, M., Manyakov, N. V., Daans, M., Jackson, A., O’Brisky, A., Telesky, T., Smets, S., Berghmans, P. J., Yang, D., Reynoso, E., Lucas, M. V., Huo, Y., Thirugnanam, V. T., Mansi, T., & Morris, M. (2024). Assessment of Physiological Signals from Photoplethysmography Sensors Compared to an Electrocardiogram Sensor: A Validation Study in Daily Life. Sensors, 24(21). https://doi.org/10.3390/s24216826
Salsabila Dany, H. A. T. I. A. I. (2022). Sistem Monitoring Denyut Jantung Berbasis IoT menggunakan protokol XMPP. 2. https://jitel.polban.ac.id/jitel/article/view/109/45
Septianto, A., & Wahyu, S. T. (2021). Analisa Perbaikan Postur Kerja Pekerja Dalam Ilmu Ergonomi Menggunakan Metode Workplace Ergonomics Risk Assessment (WERA) dan Standard Nordic Questionnaire (Vol. 6, Issue 1).
Setiarini Asih et al. (2021). Sistem Monitoring Frekuensi Denyut Nadi pada Pelari Menggunakan Metode Photoplethysmographic. Vol 8, No. 6. https://jtiik.ub.ac.id/index.php/jtiik/article/view/3729/pdf
Shcherbina, A., Mikael Mattsson, C., Waggott, D., Salisbury, H., Christle, J. W., Hastie, T., Wheeler, M. T., & Ashley, E. A. (2017). Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort. Journal of Personalized Medicine, 7(2). https://doi.org/10.3390/jpm7020003
Siswiyanti dan Sugiono Cipto. (2025). Perubahan Postur Duduk (Statis) Menjadi Postur Duduk-Berdiri (Dinamis) Meningkatkan Produktivitas Batik Tulis. Public Health and Safety International Journal, Vol. 5 No.1(1), 2715–5854. https://doi.org/10.55642
Sugunakar, M. B. S., Maruthy, K. N., Srinivas, C. H., & Johnson, P. (2021). INDIAN JOURNAL OF SCIENCE AND TECHNOLOGY A comparative study between single lead AD8232 heart rate monitor and standard electrocardiograh to acquire electrocardiographic data for cardiac autonomic function testing. / Indian Journal of Science and Technology, 14(6), 534–540. https://doi.org/10.17485/IJST/v14i6.1822
Widiatmoko Ari dan Prasetyowati Arttini Dwi. (2025). View of Accuracy Analysis of Oxygen Saturation Measurements of TKDN Oximeters Using the Uncertainty Method. Vol 6, No. 2. https://journal.polbitrada.ac.id/index.php/Jtemp/article/view/156/90













