An Efficient ECG Monitoring System using MQTT Protocol for Remote Patients in an IoT System
Keywords:
Internet of Things, ECG Detection, Pan-Tompkins Algorithm, Remote Monitoring, HealthcareAbstract
The healthcare domain has undergone a significant transformation to the Internet of Things (IoT), which has enabled the real-time monitoring of vital signs in patients. Among these vital signs, Electrocardiogram (ECG) monitoring is pivotal in the diagnosis of cardiac abnormalities. In this research article, we introduce an IoT-based ECG detection system that leverages the Pan-Tompkins algorithm to ensure precise and dependable processing of ECG signals. This system allows for the remote monitoring of ECG signals, facilitating the early identification of cardiac irregularities and timely intervention. This paper encompasses the conception, implementation, and assessment of the proposed IoT-based ECG detection system, emphasizing its efficacy and potential impact on healthcare through the utilization of MQTT (Message Queuing Telemetry Transport). The paper illustrates how IoT technology can be applied in the healthcare domain, presenting a system designed for monitoring a patient's ECG remotely. This system consists of components such as the ESP8266, ECG Sensor, and Ubidots Cloud for real-time storage and visualization of ECG data, enabling the precise measurement of a remote patient's heart rate.
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Smith, J., Johnson, A., & Williams, R. (2018). "Internet of Things (IoT) Applications in Healthcare: A Comprehensive Review." Journal of Medical Engineering & Technology, 00(0), 1-12.
Brown, L., Davis, M., & Wilson, P. (2019). "Wearable IoT Devices for Continuous Heart Monitoring: A Systematic Literature Review." IEEE Journal of Biomedical and Health Informatics, 00(0), 1-10
Garcia, S., Patel, R., & Lee, C. (2020). "QRS Detection in Wearable ECG Devices using Machine Learning Algorithms." International Conference on Internet of Things (IoT)..
Kim, H., Lee, S., & Park, K. (2021). "Real-Time QRS Detection System for Remote Cardiac Monitoring using IoT." Proceedings of the International Conference on Bioinformatics and Biomedical Engineering (iCBBE).
Johnson, M., Smith, A., Brown, L.(2019)."Real-Time QRS Detection in Wearable ECG Devices for Remote Monitoring using IoT". Proceedings of the IEEE International Conference on Internet Of Things.
Patel, R., Garcia, S., Lee, C.(2020)"An IoT-based ECG Monitoring System with Real-Time QRS Detection and Alerting". Journal of Medical Engineering & Technology.
Wilson, P., Kim, H., Davis, M.(2021) "Machine Learning Enhanced QRS Detection in IoT-enabled Wearable ECG Devices". IEEE Journal of Biomedical and Health Informatics.
Chen, T., Wang, S., Liu, J.(2022) "IoT-enabled QRS Detection System for Remote Cardiac Monitoring in Resource-Constrained Settings". International Journal of Telemedicine and Applications, 1-9
Park, J., Kim, Y., Lee, H. (2022)"A Wearable IoT ECG Device with Embedded Pan-Tompkins Algorithm for Continuous QRS Detection". Proceedings of the International Conference on Biomedical Electronics and Devices (BIODEVICES).
Jiapu Pan And Wills J. Tompkins 1985 “Real Time QRS Detection Method”, IEEE Transactions on Bio Medical Engineering, vol. Bme-32.
Wang, Y., Chen, T., Liu, X.(2021)"IoT-Based QRS Detection System for Remote Cardiac Monitoring: Performance Evaluation and Case Studies".International Conference on Bioinformatics and Biomedical Engineering (iCBBE).
Brown, L., Davis, M., Johnson, K. (2021) Adaptive QRS Detection Algorithm for IoT Wearable ECG Devices in Noisy Environments". Proceedings of the IEEE International Conference on Internet of Things (IoT).
Verma R, Sharma SK, Tyagi V. (2020) IoT-Based Remote Patient Monitoring System Using Wearable Sensors”.International Conference on Smart Electronics and Communication (ICOSEC). IEEE; 2020. p. 107-111
Li X, Zhong S, Wang Q, et al. (2020) Internet of Things for Healthcare: A Comprehensive Survey. IEEE Internet of Things Journal.;7(1):17-32, Vol. 21, No. 4, pp1349- 1361.
Ngoc Anh D, Tuan Nguyen A, Yoo S, et al. (2019) An IoT-Based Continuous ECG Monitoring System for Cardiac Arrhythmia Detection”.5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP). IEEE; 2019. p. 314-318.
Khan IA, Islam SMR, Hassan MM, et al. (2020) IoT-Based Cardiac Health Monitoring Framework Using Machine Learning Techniques”.2nd International Conference on Computer, Communication, and Signal Processing (ICCCSP). IEEE; 2020. p. 1-6.
R Santos et al., "What is MQTT and How It Works | Random Nerd Tutorials", Random Nerd Tutorials, 2020. [Online]. Available: https://randomnerdtutorials.com/what-is-mqtt-and-how-it-works/. [Accessed: 11- Dec- 2020].
A. Ghosh, "Colour based Product Organization Tool using Arduino," International Journal for Research in Applied Science and Engineering Technology, 2019, 7(5), pp. 3547–3551, DOI: 10.22214/ijraset.2019.5581.
D. Balsamo and S. Das, "Health Monitoring Based on Internet of Things (IoT)," Health Monitoring Systems, pp. 99–120, 2019.
Z. Ali, M. S. Hossain, G. Muhammad, and A. K. Sangaiah, “An intelligent healthcare system for detection and classification to discriminate vocal fold disorders,” Future Generation Computer Systems, vol. 85, pp. 19–28, Aug. 2018, doi: 10.1016/j.future.2018.02.021.
M. F. ul Hassan, D. Lai, and Y. Bu, “Characterization of single lead continuous ECG recording with various dry electrodes,” in Proceedings of the 2019 3rd International Conference on Computational Biology and Bioinformatics-ICCBB ’19, 2019, pp. 76–79., doi: 10.1145/3365966.3365974.
M. O. Rahman et al., “Internet of things (IoT) based ECG system for rural health care,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, 2021, doi: 10.14569/IJACSA.2021.0120653.
Microcontrollers lab, “What is MQTT and how MQTT works?” microcontrollers lab, 2021. https://microcontrollerslab.com/what-is-mqtt-and-how-it-works/ (accessed Dec. 22, 2021).
L. M. Dang, M. J. Piran, D. Han, K. Min, and H. Moon, “A survey on internet of things and cloud computing for healthcare,” Electronics, vol. 8, no. 7, Jul. 2019, doi: 10.3390/electronics8070768.
Swathi, V. N. V. L. S. ., Kumar, G. S. ., & Vathsala, A. V. . (2023). Cloud Service Selection System Approach based on QoS Model: A Systematic Review. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2), 05–13. https://doi.org/10.17762/ijritcc.v11i2.6104
Joseph Miller, Peter Thomas, Maria Hernandez, Juan González, Carlos Rodríguez. Exploring Ensemble Learning in Decision Science Applications. Kuwait Journal of Machine Learning, 2(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/206
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