Human Physiological Condition Monitoring System based on Microcontrollers
Article Main Content
With the rise in living standards, people are increasingly focusing on their health, and monitoring their physiological condition has become a popular trend. Sudden illnesses or hidden chronic conditions can cause abnormal fluctuations in temperature and heart rate, which can be difficult to detect without continuous monitoring. The main objective of this project is to develop a cost-effective and efficient system to monitor vital signs such as heart rate, body temperature, and steps taken, based on systematic experimental studies. The system utilizes a pulse sensor DS18B20, and ADXL345 to monitor the heart rate, body temperature, and motion status of the human body. The circuit and the HC-05 work together to transmit the detected data from the sensor to the MCU, which further transmits it to the LCD1602 or mobile phone interface for real-time display. The system provides a user-friendly interface and real-time monitoring, making it easier for individuals to keep track of their health status. This paper presents an innovative approach to human physiological condition monitoring using a microcontroller-based system, which has significant potential for improving healthcare by enabling early detection and prevention of medical conditions, ultimately leading to better quality of life.
References
-
Zhang Z, Wu H, Wang W, Wang B. A smartphone based respiratory biofeedback system. 3rd Int. Conf. on Biomedical Engineering and Informatics, (BMEI), 2010; 2: 717?720. Available: http://dx.doi.org/10.1109/BMEI.2010.5640072.
Google Scholar
1
-
Kavitha KC, Perumalraja R. Smart wireless healthcare monitoring for drivers community. International Conference on Communication and Signal Processing, (IEEE), 2014; 1105-1108.
Google Scholar
2
-
Juen J, Cheng Q, Schatz B. (2015). A natural walking monitor for pulmonary patients using mobile phones. IEEE Journal of biomedical and health informatics, 19(4), 1399-405.
Google Scholar
3
-
Kim J, Campbell AS, de ?vila BE, Wang J. (2019). Wearable biosensors for healthcare monitoring. Nature biotechnology, 37(4), 389-406.
Google Scholar
4
-
Reilly RB, Lee TC. (2010). Electrograms (ecg, eeg, emg, eog). Technology and Health Care, 18(6), 443-458.
Google Scholar
5
-
Li J, Igbe T, Liu Y, Nie Z, Qin W, Wang L, Hao Y. (2018). An approach for noninvasive blood glucose monitoring based on bioimpedance difference considering blood volume pulsation. IEEE Access, 6, 51119-51129.
Google Scholar
6
-
Jung HC, Moon JH, Baek DH, Lee JH, Choi YY, Hong JS, Lee SH. (2012). CNT/PDMS composite flexible dry electrodesfor long-term ECG monitoring. IEEE Transactions on Biomedical Engineering, 59(5), 1472-1479.
Google Scholar
7
-
Mukhopadhyay SC. (2015). Wearable sensors for human activity monitoring: A review. IEEE sensors journal, 15(3), 1321-1330.
Google Scholar
8
-
Dosinas A, Lukocius R, Vaitkunas M, Nedzinskaite G, Vaskys P, Gudzius S, Jonaitis A. (2017). Sensors and signal processing methods for a wearable physiological parameters monitoring system. Elektronika ir Elektrotechnika, 23(5), 74-81.
Google Scholar
9
-
Custodio V, Herrera FJ, L?pez G, Moreno JI. (2012). A review on architectures and communications technologies for wearable health-monitoring systems. Sensors, 12(10), 13907-13946.
Google Scholar
10
-
Din IU, Guizani M, Hassan S, Kim BS, Khan MK, Atiquzzaman M, Ahmed SH. The Internet of Things: A review of enabled technologies and future challenges, 7, 7606-7640.
Google Scholar
11
-
Liang X, Barua M, Chen L, Lu R, Shen X, Li X, Luo HY. (2012). Enabling pervasive healthcare through continuous remote health monitoring. IEEE Wireless Communications, 19(6), 10-18.
Google Scholar
12
-
Nawka N, Maguliri AK, Sharma D, Saluja P. SESGARH: A scalable extensible smart-phone based mobile gateway and application for remote health monitoring. IEEE 5th International Conference on Internet Multimedia Systems Architecture and Application, (IEEE), 2011; 1-6.
Google Scholar
13
-
Yu H, Liu L. Remote health monitoring system using zigbee network and gprs transmission technology. Fourth International Symposium on Computational Intelligence and Design, 2011; 1: 151-154.
Google Scholar
14
-
Chung WY, Yau CL, Shin KS, Myllyla R. A cell phone based health monitoring system with self analysis processor using wireless sensor network technology. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2017; 3705-3708.
Google Scholar
15
-
Anandh R, Indirani G. (2018). Real Time Health Monitoring System Using Arduino with Cloud Technology. Asian Journal of Computer Science and Technology, 7(S1), 29-32.
Google Scholar
16
-
Aminian M, Naji HR. (2013). A hospital healthcare monitoring system using wireless sensor networks. J. Health Med. Inform, 4(02), 121.
Google Scholar
17
-
Serhani MA, T. El Kassabi H, Ismail H, Nujum Navaz A. (2020). ECG monitoring systems: Review, architecture, processes, and key challenges. Sensors, 20(6), 1796.
Google Scholar
18
-
Thakor NV, Webster JG. (1980). Ground-free ECG recording with two electrodes. IEEE Transactions on Biomedical Engineering, BME-27 (12), 699-704.
Google Scholar
19
-
Javaid AQ, Ashouri H, Dorier A, Etemadi M, Heller JA, Roy S, Inan OT. (2016). Quantifying and reducing motion artifacts in wearable seismocardiogram measurements during walking to assess left ventricular health. IEEE Transactions on Biomedical Engineering, 64(6), 1277-1286.
Google Scholar
20
-
Sun F, Yi C, Li W, Li Y. (2017). A wearable H-shirt for exercise ECG monitoring and individual lactate threshold computing. Computers in industry, 92, 1-11.
Google Scholar
21
-
Sung M, Jeong K, Cho G. Suggestion for optimal location of textile-based ECG electrodes on an elastic shirts considering clothing pressure of the shirt. 12th IEEE International Symposium on Wearable Computers, 2008; 121-122.
Google Scholar
22
-
Retamosa JD, Araujo A, Wawrzyniak ZM. (2018). Low power wearable device for elderly people monitoring. Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments, 10808, 987-996.
Google Scholar
23
-
Liu J, Zhou Y. Design of a novel portable ECG monitor for heart health. Sixth International Symposium on Computational Intelligence and Design, 2013; 2: 257-260.
Google Scholar
24
-
Tosi J, Taffoni F, Santacatterina M, Sannino R, Formica D. (2017). Performance evaluation of bluetooth low energy: A systematic review. Sensors, 17(12), 2898.
Google Scholar
25
-
Song W, Yu H, Liang C, Wang Q, Shi Y.( 2012). Body monitoring system design based on android smartphone. World Congress on Information and Communication Technologies,1147-1151.
Google Scholar
26
-
Ai Z, Zheng L, Qi H, Cui W. Low-power wireless wearable ECG monitoring system based on BMD101. 37th Chinese control conference,(CCC), 2018; 7374-7379.
Google Scholar
27
-
Zhao S, Liu J, Gong Z, Lei Y, OuYang X, Chan CC, Ruan S. (2020).Wearable physiological monitoring system based on electrocardiography and electromyography for upper limb rehabilitation training. Sensors, 20(17), 4861.
Google Scholar
28
-
Sun F, Yi C, Li W, Li Y. (2017). A wearable H-shirt for exercise ECG monitoring and individual lactate threshold computing. Computers in industry, 92-93, 1-11.
Google Scholar
29
-
Zhao S, Liu R, Fei C, Guan D. (2019). Dynamic interface pressure monitoring system for the morphological pressure mapping of intermittent pneumatic compression therapy. Sensors, 19(13), 2881.
Google Scholar
30
-
Zhao S, Liu J, Gong Z, Lei Y, OuYang X, Chan CC, Ruan S. (2020).Wearable physiological monitoring system based on electrocardiography and electromyography for upper limb rehabilitation training. Sensors, 20(17), 4861.
Google Scholar
31
-
Guk K, Han G, Lim J, Jeong K, Kang T, Lim EK, Jung J. (2019). Evolution of wearable devices with real-time disease monitoring for personalized healthcare. Nanomaterials 9 (6), 813.
Google Scholar
32
-
Li W, Zhang H, Wan J, Li Y. A wearable exercise heart rate detection device based on single-arm ECG. International Conference on Biological Information and Biomedical Engineering, (BIBE), 2018; 1-4,VDE.
Google Scholar
33
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