Remote Patient Healthcare surveillance system based real-time vital signs

  • Qunoot N. Alsahi Department of Computer Science/ University of Basrah /Iraq
  • Ali F. Marhoon Department of Information and Communication Engineering / Alkhwarizmi College of Engineering / University of Baghdad
  • Ali H. Hamad Department of Electrical Engineering/ University of Basrah /Iraq

Abstract

Today many people suffering from health problems like dysfunction in lungs and cardiac. These problems often require surveillance and follow up to save a patient's health, besides control diseases before progression. For that, this work has been proposed to design and developed a remote patient surveillance system, which deals with 4 medical signs (temperature, SPO2, heart rate, and Electrocardiogram ECG. An adaptive filter has been used to remove any noise from the signal, also, a simple and fast search algorithm has been designed to find the features of  ECG signal such as Q,R,S, and T waves.  The system performs analysis for medical signs that are used to detected abnormal values. Besides, it sends data to the Base-Station with a data block (ECG signals) that contains the problem.  In addition, it generates an alarm to the physicians via ringing up mobile and SMS to overcome the internet disconnected. Also, the system has been designed to achieve precision, low cost, and low energy consumption. Three types of sensors has been used in this work, ECG, SPo2, and temperature sensors. Also, a sim800L GSM module has been used for communications,  the main controller in this work is ESP32 unit.

Downloads

Download data is not yet available.

References

M. M. Baig, H. GholamHosseini, and M. J. Connolly, “Mobile healthcare applications: system design review, critical issues and challenges,” Australas. Phys. Eng. Sci. Med., vol. 38, no. 1, pp. 23–38, 2015.

K. Y.-C. Hsieh and A.-C. Tung, “Taiwan’s National Pension Program: A remedy for rapid population aging?,” J. Econ. Ageing, vol. 8, pp. 52–66, 2016.

F. Leu, C. Ko, I. You, K. K. R. Choo, and C. L. Ho, “A smartphone-based wearable sensors for monitoring real-time physiological data,” Comput. Electr. Eng., vol. 65, pp. 376–392, 2018.

M. Pereira and K. K. Nagapriya, “A novel IoT based health monitoring system using LPC2129,” RTEICT 2017 - 2nd IEEE Int. Conf. Recent Trends Electron. Inf. Commun. Technol. Proc., vol. 2018-Janua, pp. 564–568, 2017.

H. R. Hossein and S. S. Shaikh, “SPHPMS: Smart personnel m-healthcare patient monitoring system,” Int. Conf. Electr. Electron. Optim. Tech. ICEEOT 2016, pp. 1750–1753, 2016.

S. Kale, S. Mane, and P. Patil, “IOT based wearable biomedical monitoring system,” Proc. - Int. Conf. Trends Electron. Informatics, ICEI 2017, pp. 971–976, 2017.

A. Kaur and A. Jasuja, “Health monitoring based on IoT using Raspberry PI,” in 2017 International Conference on Computing, Communication and Automation (ICCCA), pp. 1335–1340, 2017.

J. V. Alamelu and A. Mythili, “Design of IoT based generic health care system,” 2017 Int. Conf. Microelectron. Devices, Circuits Syst. ICMDCS 2017, vol. 2017-Janua, pp. 1–4, 2017.

M. Taştan, “IoT Based Wearable Smart Health Monitoring System,” Celal Bayar Üniversitesi Fen Bilim. Derg., vol. 14, no. 3, pp. 343–350, 2018.

T. Shaown, I. Hasan, M. M. R. Mim, and M. S. Hossain, “IoT-based Portable ECG Monitoring System for Smart Healthcare,” 1st Int. Conf. Adv. Sci. Eng. Robot. Technol. 2019, ICASERT 2019, vol. 2019, no. Icasert, pp. 1–5, 2019.

T. Tamura, “Connected healthcare system to monitor the blood pressure of clients with an unobtrusive device,” Med. Meas. Appl. MeMeA 2019 - Symp. Proc., pp. 1–6, 2019.

A. D. Acharya and S. N. Patil, “IoT based Health Care Monitoring Kit,” Proc. 4th Int. Conf. Comput. Methodol. Commun. ICCMC 2020, no. Iccmc, pp. 363–368, 2020.

A. F. Marhoon and A. H. Hamad, “A new real-time resource-efficient algorithm for ECG denoising, feature extraction and classification-based wearable sensor network,” Int. J. Biomed. Eng. Technol., vol. 18, no. 2, pp. 103–114, 2015.

S. Ramakrishnan, “Design and Analysis of Feature Extraction Algorithm for ECG signals using Adaptive Threshold Method,” 2017 Trends Ind. Meas. Autom., pp. 1–8, 2017.

Q. N. and A. F., “Design Health care system using Raspberry Pi and ESP32,” Int. J. Comput. Appl., vol. 177, no. 36, pp. 33–38, 2020.

M. A. Mahmoud, M. A. M. El-bendary, and M. Eltokhy, “Transfer Some of the Vital Signs of the Body by using Wireless Sensor Network,” pp. 1665–1679, 2020.

A. W. Brand, “Raspberry Pi for Dummies.” John Wiley and Sons, New Jersey, 2013.

M. Babiuch, P. Foltynek, and P. Smutny, “Using the ESP32 microcontroller for data processing,” Proc. 2019 20th Int. Carpathian Control Conf. ICCC 2019, pp. 1–6, 2019.

Shanghai SIMCom Wireless Solutions Ltd. "SIM800L Hardware Design V1.00", Shanghai, 2013.

Published
2020-12-01
How to Cite
Alsahi, Q., Marhoon, A., & Hamad, A. (2020). Remote Patient Healthcare surveillance system based real-time vital signs. Al-Khwarizmi Engineering Journal, 16(4), 41-51. https://doi.org/10.22153/kej.2020.10.003