Real-Time IoT-Based Wireless Interaction System for Patients with Disabilities

Authors

DOI:

https://doi.org/10.61841/y3dgzz18

Keywords:

Internet of Things (IoT), NodeMcu ESP8266, Heart Rate Sensor, Oximeter, Monitoring System

Abstract

The increasing population of disabled patients in hospitals highlights the critical need for solutions that address their unique and timely healthcare requirements. Traditional methods, such as employing full-time caregivers or implementing round-the-clock monitoring systems, are often costly and require substantial resources. This study presents a cost-efficient and real-time solution designed to enhance communication between nurses and multiple patients using a motion-based wireless interaction system. The system incorporates a mechanism for monitoring blood oxygen levels and heart rate alongside a motion-based messaging component. It utilizes the MAX30100 sensor module (Pulse Oximeter and Heart Rate sensor), MPU6050 sensor (Accelerometer and Gyroscope), and ESP8266 NodeMCU. These devices are mounted on a movable part of the patient’s body to enable efficient communication. Wireless messages are sent to a central receiver located at the nurse’s station, displayed on a screen, and supported by auditory alerts to ensure timely responses. Repeaters are employed to maintain seamless communication for wards located over 40 meters away, ensuring broader coverage. This system significantly lowers manpower demands and operational expenses while improving patient satisfaction and healthcare quality through automated caretaking and consistent monitoring. The design and architecture underwent comprehensive testing at different stages, culminating in a fully functional prototype. This innovative system addresses the challenges of continuous patient monitoring, providing a scalable and effective solution to advance healthcare services for disabled patients.

Author Biography

  • Mahfujur Rahman, Jahangirnagar University, Department of Institute of Information Technology, Savar, 1342, Dhaka, Bangladesh

    Mahfujur Rahman completed his Master’s degree in Information Technology from Jahangirnagar University in 2024 and earned a Bachelor’s degree in Electronics and Communication Engineering from the Institute of Science, Trade & Technology (Affiliated by National University, Bangladesh)  in 2018. His current research interests include Internet of Things, Data Analytics, Machine Learning, Wireless Network & Signal processing, Big data and Cyber Security, Renewable Energy.

References

Aishwarya Desai, Nishigandha Pawar, Kshitija Desai, Noopur Behrani “motion based message conveyor for paralytic/disabled”. International Journal of Innovative Research in Computer and Communication Engineering Volume 4, Issue 3, March 2016.

Rohini Bhilare, Shraddha Swami, Priyanka Deshmukh, Mr. Prasad R. Patil “motion based message conveyor for patient using arduino system and zigbee”. International Journal of Advanced Research In Engineering Technology & Sciences March-2015 Volume 2, Issue-3.

Prpit Verma, Nitish Kapila, Narsingh Rathore, Aakash Prajapati md. suhaib abbasi “motion based message conveyer for paralytic/disabled people”. International Journal for Research in Applied Science & Engineering Technology (IJRASET) April-2017 Volume 5, Issue-4.

S. Bradley, F. Kamwendo, E. Chipeta, W. Chimwaza, H. Pinho, and E. Mcauliffe, “Too few staff, too many patients: A qualitative study of the impact on obstetric care providers and on quality of care in Malawi”, BMC Pregnancy and Childbirth, vol. 15, no. 1, pp. 65, 2015. DOI: 10.1186/s12884-015-0492-5.

S. Gangopadhyay, S. Mukherjee, and S. Chatterjee, “Intelligent gesture controlled wireless wheelchair for the physically handicapped”, International Journal of Electrical, Electronics and Data Communication, vol. 1, no. 7, Sep. 2013. ISSN: 2320-2084.

A. Desai, N. Pawar, K. Desai, and N. Behrani, “Motion Based Message Conveyor for Paralytic/Disabled”, International Journal of Innovative Research in Computer and Communication Engineering, vol. 4, no. 3, Mar. 2016.

https://components101.com/development-boards/nodemcu-esp8266-pinout-features-and-datasheet.

https://components101.com/sensors/max30100-heart-rate-oxygen-pulse-sensor-pinout-features-datasheet.

https://components101.com/sensors/mpu6050-module.

2020. [Online]. Available: https://www.arduino.cc/en/software. [Accessed: 14- Dec- 2020].

H. Park, P. Bonato, L. Chan, and M. Rodgers, “A review of wearable sensors and systems with application inrehabilitation,” J. Neuroeng. Rehabil., vol. 9, no. 1, p. 21,2012.

3. N. B. Krishnan, S. S. S. Sai, and S. B. Mohanthy, “Real Time Internet Application with distributed flow environment for medical IoT,” Proc. 2015 Int. Conf. Green.

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Published

2025-02-07

How to Cite

Rahman, M. (2025). Real-Time IoT-Based Wireless Interaction System for Patients with Disabilities. Journal of Advance Research in Computer Science & Engineering (ISSN 2456-3552), 10(1), 8-16. https://doi.org/10.61841/y3dgzz18