Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
권호 표지

Development of Continuous ECG Monitor for Early Diagnosis of Arrhythmia Signals

부정맥 신호의 조기진단을 위한 연속 심전도 모니터링 기기 개발

  • Choi, Junghyeon (AIRLab) ;
  • Kang, Minho (AIRLab) ;
  • Park, Junho (AIRLab) ;
  • Kwon, Keekoo (Daegu-Gyeongbuk Research Center, Electronics and Telecommunications Research Institute) ;
  • Bae, Taewuk (Daegu-Gyeongbuk Research Center, Electronics and Telecommunications Research Institute) ;
  • Park, Jun-Mo (School of Electronics and Biomedical Engineering, Tongmyong University)
  • Received : 2021.02.09
  • Accepted : 2021.06.25
  • Published : 2021.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

With the recent development of IT technology, research and interest in various bio-signal measuring devices are increasing. But studies related to ECG(electrocardiogram), which is one of the most representative bio-signals, particularly arrhythmic signal detection, are incomplete. Since arrhythmia has various causes and has a poor prognosis after onset, preventive treatment through early diagnosis is best. However, the 24-hour Holter electrocardiogram, a tool for diagnosing arrhythmia, has disadvantages in the limitation of use time, difficulty in analyzing motion artifact due to daily life, and the user's real-time alarm function in danger. In this study, an ECG and pulse monitoring device capable of continuous measurement for a long time, a real-time monitoring app, and software for analysis were developed, and the trend of the measured values was confirmed. In future studies, research on derivation of quantitative results of ECG signal measurement analysis is required, and further research on the development of an arrhythmic signal detection algorithm based on this is required.

최근 IT기술이 발달함에 따라 다양한 생체신호 측정 기기에 대한 연구 및 관심이 높아지고 있으나, 가장 대표적인 생체 신호 중 하나인 심전도, 특히 부정맥 신호 검출과 관련한 연구는 미비한 현실이다. 부정맥은 그 발병원인이 다양하며 발병이후 예후가 좋지 않으므로 조기진단을 통한 예방치료가 최선이다. 하지만 부정맥을 진단하기 위한 도구인 24시간 홀터 심전계는 사용지속시간의 제약, 일상생활로 인한 동잡음 분석의 어려움, 위험상황에서 사용자의 실시간 알람 기능에 단점을 보인다. 본 연구에서는 장시간 연속 측정이 가능한 심전도 및 맥박 모니터링 기기와 실시간 모니터링 앱, 분석용 소프트웨어를 개발하였으며, 측정한 값의 경향성을 확인하였다. 향후 연구에서는 심전도 신호 측정 분석의 정량적 결과 도출에 관한 연구가 필요하며, 이를 바탕으로 하는 부정맥 신호 검출 알고리즘 개발과 관련한 추가 연구를 진행해야 한다.

Keywords

Acknowledgement

본 연구는 한국전자통신연구원 김해시보조금사업의 일환으로 수행되었음 [20AD1900, 김해지역 AI 제조혁신기술 공동개발 및 지원사업]

References

  1. Seunghwan Kim, "유비쿼터스 헬스케어를 위한 생체신호 모니터링 기술", IT SoC Magizine, No. 25, pp.40-47, 2008.
  2. Joohyun Hong, Eunjong Cha, Taesoo Lee, "Evaluation of CDMA Network Based Wireless 3 Channel ECG Monitoring System", Journal of Biomedical Engineering Research, vol.29, no.4, pp.295-301, 2008.
  3. Jeonggwan Cho, "Recent Advancement in the Management of the Cardia Arrythmia", Journal of Korean Medical Association, vol. 53, no. 3, pp.190-195, 2010. https://doi.org/10.5124/jkma.2010.53.3.190
  4. J.H.Hong et al.m "A PDA-Based Wireless ECG Monitoring System for u-Healthcare", Journal of Medical Informatics, vol.12, no.2, 99.153-159, 2006. 재인용
  5. R. Fensli, E. Gunnarson and O. Hejlesen, "A wireless ECG system for continous event recording and communication to a clinical alarm station", Proceeding of the 26th Annul International Conference of the IEEE EMBS, San Francisco, USA, Sept. 2004, pp2208-2211 재인용
  6. A. I. Hernandez, F. Mora, G. Villegas, G. Passariello and G. Carrault, "Real-Time ECG Transmission Via Internet for Nonclinical Applications", IEEE Transactions on Biomedical Engineering, vol.5, no.3, pp.253-257, 2001. 재인용
  7. J. Andreasson, M. Ekstorm, A. Fard, J.G. Castano and T. Johnson, "Remote System for Patient Monitoring Using Bluetooth", Proceedings of IEEE, pp.304-307, 2002. 재인용
  8. L.W. Keijsers, M. Horstink and S. Gielen, "Automatic Assessment of Levodopa-Induced Dyskinesias in Daily Life by Neural Networks", Movement Disorders, vol.18, no.6, pp.711-723, 2003. 재인용
  9. B. Jajafi, K. Aminian, F. Loew and C.J. Bula, "Ambulaory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly", IEEE Transactions on Biomedical Engineering, vol.50, no.6, pp.711-723, 2003. 재인용 https://doi.org/10.1109/tbme.2003.812189
  10. M. Mohebbi, H. Ghassemian, "Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal". Journal of Computer Methods and Programs in Biomedicine, vol.105, no.1, pp.40-49, 2012. https://doi.org/10.1016/j.cmpb.2010.07.011
  11. O. Kwon, et al., "Electrocardiogram Sampling Frequency Range Acceptable for Heart Rate Variability Analysis", Journal of Healthcare Informatics Research, vol.24, no.3, pp.198-206, 2018. https://doi.org/10.4258/hir.2018.24.3.198
  12. J. Pan, W. J. Tompkins, "A Real-Time QRS Detection Algorithm", IEEE Transactions on Biomedical Engineering, vol.BME-32, iss.3, pp. 230-236, 1985. https://doi.org/10.1109/TBME.1985.325532