Application of Voice Recognition Technology for Early Detection of Respiratory Disorders in Premature Babies
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Early Detection, Respiratory Disorders, Premature Babies
Abstract
Bayi prematur memiliki risiko tinggi mengalami gangguan pernafasan yang berpotensi mengancam nyawa yang dapat berujung pada komplikasi atau permasalahan yang serius atau bahkan kematian jika tidak dideteksi secara tepat waktu. Untuk itu diterapkanlah sebuah teknologi pengenalan suara dagar dapat mengidentifikasi gangguan pernapsan yang terjadi pada bayi premature. Tujuan dari penelitian ini adalah untuk mengembangkan sistem yang dapat mengenali pola suara khas yang terkait dengan gangguan pernafasan pada bayi prematur. Dengan memanfaatkan teknologi ini, diharapkan dapat meningkatkan kemampuan deteksi dini gangguan pernafasan pada bayi prematur, sehingga memungkinkan intervensi medis yang lebih cepat dan tepat. Metode penelitian melibatkan pengumpulan data suara respirasi dari bayi prematur menggunakan mikrofon yang dipasang di sekitar inkubator mereka, diikuti oleh analisis menggunakan teknik pengolahan sinyal digital dan algoritma pembelajaran mesin. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu mengidentifikasi pola suara yang menunjukkan tanda-tanda gangguan pernafasan dengan tingkat akurasi yang tinggi yang di alami oleh bayi permatur. Hal ini didukung oleh data validasi yang menunjukkan bahwa sistem berhasil mendeteksi sebagian besar kasus gangguan pernafasan pada bayi permatur.Kesimpulan dari penelitian ini adalah bahwa teknologi pengenalan suara memiliki potensi besar sebagai alat deteksi dini gangguan pernafasan pada bayi prematur, yang dapat membantu tenaga medis dalam memberikan perawatan yang tepat waktu dan mengurangi risiko komplikasi serius. Dengan demikian, penerapan teknologi ini di lingkungan klinis dapat meningkatkan prognosis dan kelangsungan hidup bayi prematur yang rentan.
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References
Abdel-Latif, M. E., Davis, P. G., Wheeler, K. I., De Paoli, A. G., & Dargaville, P. A. (2021). Surfactant therapy via thin catheter in preterm infants with or at risk of respiratory distress syndrome. Cochrane Database of Systematic Reviews, 2021(5). https://doi.org/10.1002/14651858.CD011672.pub2
Ahmad, M., Amin, M. B., Hussain, S., Kang, B. H., Cheong, T., & Lee, S. (2016). Health Fog: A novel framework for health and wellness applications. The Journal of Supercomputing, 72(10), 3677–3695. https://doi.org/10.1007/s11227-016-1634-x
Aldana-Aguirre, J. C., Pinto, M., Featherstone, R. M., & Kumar, M. (2017). Less invasive surfactant administration versus intubation for surfactant delivery in preterm infants with respiratory distress syndrome: A systematic review and meta-analysis. Archives of Disease in Childhood - Fetal and Neonatal Edition, 102(1), F17–F23. https://doi.org/10.1136/archdischild-2015-310299
Chung, A. E., Griffin, A. C., Selezneva, D., & Gotz, D. (2018). Health and Fitness Apps for Hands-Free Voice-Activated Assistants: Content Analysis. JMIR mHealth and uHealth, 6(9), e174. https://doi.org/10.2196/mhealth.9705
Colorafi, K. J., & Evans, B. (2016). Qualitative Descriptive Methods in Health Science Research. HERD: Health Environments Research & Design Journal, 9(4), 16–25. https://doi.org/10.1177/1937586715614171
Creasy, R. K. (1993). Preterm birth prevention: Where are we? American Journal of Obstetrics and Gynecology, 168(4), 1223–1230. https://doi.org/10.1016/0002-9378(93)90373-Q
Dargaville, P. A., Aiyappan, A., Cornelius, A., Williams, C., & De Paoli, A. G. (2011). Preliminary evaluation of a new technique of minimally invasive surfactant therapy. Archives of Disease in Childhood - Fetal and Neonatal Edition, 96(4), F243–F248. https://doi.org/10.1136/adc.2010.192518
Dargaville, P. A., Aiyappan, A., De Paoli, A. G., Kuschel, C. A., Kamlin, C. O. F., Carlin, J. B., & Davis, P. G. (2013). Minimally-invasive surfactant therapy in preterm infants on continuous positive airway pressure. Archives of Disease in Childhood - Fetal and Neonatal Edition, 98(2), F122–F126. https://doi.org/10.1136/archdischild-2011-301314
Dargaville, P. A., Kamlin, C. O. F., Orsini, F., Wang, X., De Paoli, A. G., Kanmaz Kutman, H. G., Cetinkaya, M., Kornhauser-Cerar, L., Derrick, M., Özkan, H., Hulzebos, C. V., Schmölzer, G. M., Aiyappan, A., Lemyre, B., Kuo, S., Rajadurai, V. S., O’Shea, J., Biniwale, M., Ramanathan, R., … Collins, S. L. (2021). Effect of Minimally Invasive Surfactant Therapy vs Sham Treatment on Death or Bronchopulmonary Dysplasia in Preterm Infants With Respiratory Distress Syndrome: The OPTIMIST-A Randomized Clinical Trial. JAMA, 326(24), 2478. https://doi.org/10.1001/jama.2021.21892
Downing, G. J., & Kilbride, H. W. (1995). Evaluation of Airway Complications in High-Risk Preterm Infants: Application of Flexible Fiberoptic Airway Endoscopy. Pediatrics, 95(4), 567–572. https://doi.org/10.1542/peds.95.4.567
Fagherazzi, G., Fischer, A., Ismael, M., & Despotovic, V. (2021). Voice for Health: The Use of Vocal Biomarkers from Research to Clinical Practice. Digital Biomarkers, 5(1), 78–88. https://doi.org/10.1159/000515346
Göpel, W., Kribs, A., Ziegler, A., Laux, R., Hoehn, T., Wieg, C., Siegel, J., Avenarius, S., Von Der Wense, A., Vochem, M., Groneck, P., Weller, U., Möller, J., Härtel, C., Haller, S., Roth, B., & Herting, E. (2011). Avoidance of mechanical ventilation by surfactant treatment of spontaneously breathing preterm infants (AMV): An open-label, randomised, controlled trial. The Lancet, 378(9803), 1627–1634. https://doi.org/10.1016/S0140-6736(11)60986-0
Hailman, M., Merritt, T. A., Schneider, H., Epstein, B. L., Mannino, F., Edwards, D. K., & Gluck, L. (1983). Isolation of Human Surfactant from Amniotic Fluid and a Pilot Study of Its Efficacy in Respiratory Distress Syndrome. Pediatrics, 71(4), 473–482. https://doi.org/10.1542/peds.71.4.473
Halliday, H. L., Ehrenkranz, R. A., & Doyle, L. W. (2009). Late (>7 days) postnatal corticosteroids for chronic lung disease in preterm infants. In The Cochrane Collaboration (Ed.), Cochrane Database of Systematic Reviews (p. CD001145.pub2). John Wiley & Sons, Ltd. https://doi.org/10.1002/14651858.CD001145.pub2
Hawdon, J. M., Beauregard, N., Slattery, J., & Kennedy, G. (2000). Identification of neonates at risk of developing feeding problems in infancy. Developmental Medicine & Child Neurology, 42(4), 235–239. https://doi.org/10.1017/S0012162200000402
Khalilzad, Z., Hasasneh, A., & Tadj, C. (2022). Newborn Cry-Based Diagnostic System to Distinguish between Sepsis and Respiratory Distress Syndrome Using Combined Acoustic Features. Diagnostics, 12(11), 2802. https://doi.org/10.3390/diagnostics12112802
Kumah-Crystal, Y., Pirtle, C., Whyte, H., Goode, E., Anders, S., & Lehmann, C. (2018). Electronic Health Record Interactions through Voice: A Review. Applied Clinical Informatics, 09(03), 541–552. https://doi.org/10.1055/s-0038-1666844
Levy, M. L., Fletcher, M., Price, D. B., Hausend, T., Halbert, R. J., & Yawn, B. P. (2006). International Primary Care Respiratory Group (IPCRG) Guidelines: Diagnosis of respiratory diseases in primary care. Primary Care Respiratory Journal, 15(1), 20–34. https://doi.org/10.1016/j.pcrj.2005.10.004
Loewy, J., Stewart, K., Dassler, A.-M., Telsey, A., & Homel, P. (2013). The Effects of Music Therapy on Vital Signs, Feeding, and Sleep in Premature Infants. Pediatrics, 131(5), 902–918. https://doi.org/10.1542/peds.2012-1367
Manfredi, C., Bocchi, L., Orlandi, S., Spaccaterra, L., & Donzelli, G. P. (2009). High-resolution cry analysis in preterm newborn infants. Medical Engineering & Physics, 31(5), 528–532. https://doi.org/10.1016/j.medengphy.2008.10.003
Marukami, T., Tani, S., Matsuda, A., Takemoto, K., Shindo, A., & Inada, H. (2012). A Basic Study on Application of Voice Recognition Input to an Electronic Nursing Record System -Evaluation of the Function as an Input Interface-. Journal of Medical Systems, 36(3), 1053–1058. https://doi.org/10.1007/s10916-010-9567-z
More, K., Sakhuja, P., & Shah, P. S. (2014). Minimally Invasive Surfactant Administration in Preterm Infants: A Meta-narrative Review. JAMA Pediatrics, 168(10), 901. https://doi.org/10.1001/jamapediatrics.2014.1148
Moretti, C., Gizzi, C., Papoff, P., Lampariello, S., Capoferri, M., Calcagnini, G., & Bucci, G. (1999). Comparing the effects of nasal synchronized intermittent positive pressure ventilation (nSIPPV) and nasal continuous positive airway pressure (nCPAP) after extubation in very low birth weight infants. Early Human Development, 56(2–3), 167–177. https://doi.org/10.1016/S0378-3782(99)00046-8
Namba, H. (2021). Physical Activity Evaluation Using a Voice Recognition App: Development and Validation Study. JMIR Biomedical Engineering, 6(1), e19088. https://doi.org/10.2196/19088
Orlandi, S., Reyes Garcia, C. A., Bandini, A., Donzelli, G., & Manfredi, C. (2016). Application of Pattern Recognition Techniques to the Classification of Full-Term and Preterm Infant Cry. Journal of Voice, 30(6), 656–663. https://doi.org/10.1016/j.jvoice.2015.08.007
Reuter, S., Moser, C., & Baack, M. (2014). Respiratory Distress in the Newborn. Pediatrics In Review, 35(10), 417–429. https://doi.org/10.1542/pir.35.10.417
Rohlfing, M. L., Buckley, D. P., Piraquive, J., Stepp, C. E., & Tracy, L. F. (2021). Hey Siri: How Effective are Common Voice Recognition Systems at Recognizing Dysphonic Voices? The Laryngoscope, 131(7), 1599–1607. https://doi.org/10.1002/lary.29082
Saggio, G., & Costantini, G. (2022). Worldwide Healthy Adult Voice Baseline Parameters: A Comprehensive Review. Journal of Voice, 36(5), 637–649. https://doi.org/10.1016/j.jvoice.2020.08.028
Salehian Matikolaie, F., & Tadj, C. (2020). On the use of long-term features in a newborn cry diagnostic system. Biomedical Signal Processing and Control, 59, 101889. https://doi.org/10.1016/j.bspc.2020.101889
Sardesai, S., Biniwale, M., Wertheimer, F., Garingo, A., & Ramanathan, R. (2017). Evolution of surfactant therapy for respiratory distress syndrome: Past, present, and future. Pediatric Research, 81(1–2), 240–248. https://doi.org/10.1038/pr.2016.203
Sezgin, E., Militello, L. K., Huang, Y., & Lin, S. (2020). A scoping review of patient-facing, behavioral health interventions with voice assistant technology targeting self-management and healthy lifestyle behaviors. Translational Behavioral Medicine, 10(3), 606–628. https://doi.org/10.1093/tbm/ibz141
Shah, S., Slaney, E., VerHage, E., Chen, J., Dias, R., Abdelmalik, B., Weaver, A., & Neu, J. (2023). Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature. Neonatology, 120(5), 558–565. https://doi.org/10.1159/000531441
Short, E. J., Kirchner, H. L., Asaad, G. R., Fulton, S. E., Lewis, B. A., Klein, N., Eisengart, S., Baley, J., Kercsmar, C., Min, M. O., & Singer, L. T. (2007). Developmental Sequelae in Preterm Infants Having a Diagnosis of Bronchopulmonary Dysplasia: Analysis Using a Severity-Based Classification System. Archives of Pediatrics & Adolescent Medicine, 161(11), 1082. https://doi.org/10.1001/archpedi.161.11.1082
Vogel, M., Kaisers, W., Wassmuth, R., & Mayatepek, E. (2015). Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial. Journal of Medical Internet Research, 17(11), e247. https://doi.org/10.2196/jmir.5072
Wheeler, S., & Cassimus, G. C. (1999). Selecting and implementing a voice recognition system. Radiology Management, 21(4), 37–42.
Widiastuti, W., Fatimah, D. D. S., Damiri, D. J., & Sekolah Tinggi Teknologi Garut. (2012). Aplikasi Sistem Pakar Deteksi Dini Pada Penyakit Tuberkulosis. Jurnal Algoritma, 9(1), 57–66. https://doi.org/10.33364/algoritma/v.9-1.57
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Copyright (c) 2024 Dhiana Setyorini, Benny Novico Zani, Dina Rasmita, Khrisna Agung Cendekiawan, Arnes Yuli Vandika
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