Hardware-software implementation of a local Wi-Fi network for the transmission of biomedical signals

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.309387

Keywords:

biomedical signal, Holter monitoring, computer simulation, MATLAB system, Wi-Fi transmission, algorithm, ESP32 module

Abstract

The object of this study is a wireless local Wi-Fi network for broadcasting biomedical signals, its structure, and principles of construction. The task of minimizing the power consumption of a Wi-Fi transmitter has been addressed, which provides the possibility of building a wireless system for long-term monitoring of biomedical signals. As a result, a functional diagram of a wireless Holter monitoring system based on an ESP32 microcontroller was constructed, which includes a subsystem for setting up and diagnosing system units using MATLAB software packages, an ECG signal generator, and a multifunctional PCIe board from National Instruments. Evaluation criteria and methods for minimizing power consumption by an autonomous Wi-Fi transmitter have been proposed. Methods for synchronizing the working cycles of the transmitter and receiver of the Holter monitoring system were determined. A procedure for determining the optimal biosignal measurement frequency is presented, at which the distortion of ECG signals would be minimal, which means that the signal could be transmitted without losses. The concept of constructing an algorithm for implementing a program for a Wi-Fi transmitter has been developed, ensuring parallel execution of ECG signal measurement operations and their transmission over a local network. The data from semi-naturalistic tests with an experimental Holter monitoring system with a pre-setup subsystem and using external measuring devices, a computer, and the MATLAB software environment are presented. A comparative analysis of the experimental data with primary ECG signals and ECG signals at the receiver output showed a fairly stable correspondence between the input and output ECG signals. The proposed algorithms make it possible to reduce the average current consumption of the ESP32 microcontroller to 50.5 mA. The results of the study demonstrate the possibility of constructing an energy-efficient wireless system for long-term monitoring of biomedical signals based on the Wi-Fi interface

Author Biographies

Yuliya Gerasimova, M. Kozybayev North Kazakhstan University

Candidate of Engineering Sciences

Department of Energetic and Radioelectronics

Victor Ivel, M. Kozybayev North Kazakhstan University

Doctor of Sciences in Engineering

Department of Energetic and Radioelectronics

Sayat Moldakhmetov, M. Kozybayev North Kazakhstan University

PhD

Department of Power Engineering and Radio Electronics

Pavel Petrov, M. Kozybayev North Kazakhstan University

PhD

Department of Power Engineering and Radio Electronics

References

  1. Patel, S., Park, H., Bonato, P., Chan, L., Rodgers, M. (2012). A review of wearable sensors and systems with application in rehabilitation. Journal of NeuroEngineering and Rehabilitation, 9 (1). https://doi.org/10.1186/1743-0003-9-21
  2. Bekbay, A., Alimbayeva, Z., Alimbayev, C., Bayanbay, N., Ozhikenov, K., Mukazhanov, Y. (2022). Development of an atrioventricular block prediction of method for portable heart monitoring system. Eastern-European Journal of Enterprise Technologies, 3 (5 (117)), 15–27. https://doi.org/10.15587/1729-4061.2022.258791
  3. Subramaniam, S., Akay, M., Anastasio, M. A., Bailey, V., Boas, D., Bonato, P. et al. (2024). Grand Challenges at the Interface of Engineering and Medicine. IEEE Open Journal of Engineering in Medicine and Biology, 5, 1–13. https://doi.org/10.1109/ojemb.2024.3351717
  4. Garudadri, H., Chi, Y., Baker, S., Majumdar, S., Baheti, P. K., Ballard, D. (2011). Diagnostic grade wireless ECG monitoring. 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. https://doi.org/10.1109/iembs.2011.6090194
  5. Pinho, F., Correia, J. H., Sousa, N. J., Cerqueira, J. J., Dias, N. S. (2014). Wireless and wearable eeg acquisition platform for ambulatory monitoring. 2014 IEEE 3nd International Conference on Serious Games and Applications for Health (SeGAH). https://doi.org/10.1109/segah.2014.7067078
  6. Barrett, P. M., Komatireddy, R., Haaser, S., Topol, S., Sheard, J., Encinas, J. et al. (2014). Comparison of 24-hour Holter Monitoring with 14-day Novel Adhesive Patch Electrocardiographic Monitoring. The American Journal of Medicine, 127 (1), 95.e11-95.e17. https://doi.org/10.1016/j.amjmed.2013.10.003
  7. Ivel, V. P., Gerasimova, Y. V., Moldakhmetov, S. S., Petrov, P. A., Gerasimov, I. A., Zainchkovskaya, K. V. (2019). Wireless three-channel Holter monitoring system. IOP Conference Series: Materials Science and Engineering, 537 (3), 032090. https://doi.org/10.1088/1757-899x/537/3/032090
  8. Oresko, J. J., Duschl, H., Cheng, A. C. (2010). A Wearable Smartphone-Based Platform for Real-Time Cardiovascular Disease Detection Via Electrocardiogram Processing. IEEE Transactions on Information Technology in Biomedicine, 14 (3), 734–740. https://doi.org/10.1109/titb.2010.2047865
  9. Frederix, I., Caiani, E. G., Dendale, P., Anker, S., Bax, J., Böhm, A. et al. (2019). ESC e-Cardiology Working Group Position Paper: Overcoming challenges in digital health implementation in cardiovascular medicine. European Journal of Preventive Cardiology, 26 (11), 1166–1177. https://doi.org/10.1177/2047487319832394
  10. Mukhopadhyay, S. C. (2015). Wearable Sensors for Human Activity Monitoring: A Review. IEEE Sensors Journal, 15 (3), 1321–1330. https://doi.org/10.1109/jsen.2014.2370945
  11. Saad, C., Mostafa, B., Ahmadi, E., Abderrahmane, H. (2014). Comparative Performance Analysis of Wireless Communication Protocols for Intelligent Sensors and Their Applications. International Journal of Advanced Computer Science and Applications, 5 (4). https://doi.org/10.14569/ijacsa.2014.050413
  12. Franceschinis, M., Pastrone, C., Spirito, M. A., Borean, C. (2013). On the performance of ZigBee Pro and ZigBee IP in IEEE 802.15.4 networks. 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). https://doi.org/10.1109/wimob.2013.6673344
  13. Al Hadidi, M., Al-Azzeh, J. S., Tkalich, O., Odarchenko, R., Gnatyuk, S., Khokhlachova, Y. (2017). ZigBee, Bluetooth and Wi-Fi Complex Wireless Networks Performance Increasing. International Journal on Communications Antenna and Propagation (IRECAP), 7 (1), 48. https://doi.org/10.15866/irecap.v7i1.10911
  14. Weyer, S., Menden, T., Leicht, L., Leonhardt, S., Wartzek, T. (2015). Development of a wearable multi-frequency impedance cardiography device. Journal of Medical Engineering & Technology, 39 (2), 131–137. https://doi.org/10.3109/03091902.2014.990161
  15. Iqbal, S. M. A., Mahgoub, I., Du, E., Leavitt, M. A., Asghar, W. (2022). Development of a wearable belt with integrated sensors for measuring multiple physiological parameters related to heart failure. Scientific Reports, 12 (1). https://doi.org/10.1038/s41598-022-23680-1
  16. Barylo, H. I., Kuchmii, H. L., Kremer, I. P. (2013). ZigBee wireless communication system for telemedicine. Eastern-European Journal of Enterprise Technologies, 6 (12 (66)), 79–82. https://doi.org/10.15587/1729-4061.2013.19741
  17. Danbatta, S. J., Varol, A. (2019). Comparison of Zigbee, Z-Wave, Wi-Fi, and Bluetooth Wireless Technologies Used in Home Automation. 2019 7th International Symposium on Digital Forensics and Security (ISDFS). https://doi.org/10.1109/isdfs.2019.8757472
  18. Filho, P., Schulz, F. (2013). Zigbee Network for Biomedical Signal Monitoring: Preliminary Results. International journal of Engineering Research and Application, 3 (5), 531–534.
  19. Fernández-López, H., Afonso, J. A., Correia, J. H., Simoes, R. (2012). Towards the design of efficient nonbeacon-enabled ZigBee networks. Computer Networks, 56 (11), 2714–2725. https://doi.org/10.1016/j.comnet.2012.04.013
  20. Yang, Z., Zhou, Q., Lei, L., Zheng, K., Xiang, W. (2016). An IoT-cloud Based Wearable ECG Monitoring System for Smart Healthcare. Journal of Medical Systems, 40 (12). https://doi.org/10.1007/s10916-016-0644-9
  21. Kaliaskarov, N., Ivel, V., Gerasimova, Y., Yugay, V., Moldakhmetov, S. (2020). Development of a distributed wireless Wi-Fi system for monitoring the technical condition of remote objects. Eastern-European Journal of Enterprise Technologies, 5 (9 (107)), 36–48. https://doi.org/10.15587/1729-4061.2020.212301
  22. Martínez-Suárez, F., García-Limón, J. A., Baños-Bautista, J. E., Alvarado-Serrano, C., Casas, O. (2023). Low-Power Long-Term Ambulatory Electrocardiography Monitor of Three Leads with Beat-to-Beat Heart Rate Measurement in Real Time. Sensors, 23 (19), 8303. https://doi.org/10.3390/s23198303
  23. Li, D., Liu, P., Sun, T., Li, L., Xue, Y. (2024). Real-Time PVC Recognition System Design Based on Multi-Parameter SE-ResNet. IEEE Access, 12, 70345–70356. https://doi.org/10.1109/access.2024.3402359
  24. Ivel, V. P., Gerasimova, Y. V., Moldakhmetov, S. S., Petrov, P. A., Gerasimov, I. A. (2020). Wireless Holter monitoring system with a dual-core processor. IOP Conference Series: Materials Science and Engineering, 919 (2), 022040. https://doi.org/10.1088/1757-899x/919/2/022040
  25. Data Sheet. AD8232. Available at: https://www.micro-semiconductor.com/datasheet/29-AD8232ACPZ-R7.pdf
  26. Sigit, R. (2014). Mini Wireless ECG for Monitoring Athletes’ ECG Signal Based on Smartphone. IOSR Journal of Engineering, 4 (6), 13–18. https://doi.org/10.9790/3021-04611318
  27. Syahmi Md Dzahir, M. A., Seng Chia, K. (2023). Evaluating the Energy Consumption of ESP32 Microcontroller for Real-Time MQTT IoT-Based Monitoring System. 2023 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT). https://doi.org/10.1109/3ict60104.2023.10391358
  28. Jung, J., Shin, S., Kang, M., Kang, K. H., Kim, Y. T. (2021). Development of Wearable Wireless Electrocardiogram Detection System using Bluetooth Low Energy. Electronics, 10 (5), 608. https://doi.org/10.3390/electronics10050608
  29. Koshekov, K., Kobenko, V., Koshekov, A., Moldakhmetov, S. (2020). Hand-written character structure recognition technology on the basis of identification measurements. ARPN Journal of Engineering and Applied Sciences, 15 (21), 2555–2562. Available at: https://www.arpnjournals.org/jeas/research_papers/rp_2020/jeas_1120_8390.pdf
Hardware-software implementation of a local Wi-Fi network for the transmission of biomedical signals

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Published

2024-08-30

How to Cite

Gerasimova, Y., Ivel, V., Moldakhmetov, S., & Petrov, P. (2024). Hardware-software implementation of a local Wi-Fi network for the transmission of biomedical signals. Eastern-European Journal of Enterprise Technologies, 4(9 (130), 34–43. https://doi.org/10.15587/1729-4061.2024.309387

Issue

Section

Information and controlling system