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. 2024 Jun 30:13:102834.
doi: 10.1016/j.mex.2024.102834. eCollection 2024 Dec.

IoT-based emergency cardiac death risk rescue alert system

Shafiq Ul Rehman  1 , Ibrahim Sadek  2 , Binhua Huang  3 , Selvakumar Manickam  3 , Lamees N Mahmoud  2
Affiliations

IoT-based emergency cardiac death risk rescue alert system

Shafiq Ul Rehman et al. MethodsX. .

Abstract

The use of technology in healthcare is one of the most critical application areas today. With the development of medical applications, people's quality of life has improved. However, it is impractical and unnecessary for medium-risk people to receive specialized daily hospital monitoring. Due to their health status, they will be exposed to a high risk of severe health damage or even life-threatening conditions without monitoring. Therefore, remote, real-time, low-cost, wearable, and effective monitoring is ideal for this problem. Many researchers mentioned that their studies could use electrocardiogram (ECG) detection to discover emergencies. However, how to respond to discovered emergencies in household life is still a research gap in this field.•This paper proposes a real-time monitoring of ECG signals and sending them to the cloud for Sudden Cardiac Death (SCD) prediction.•Unlike previous studies, the proposed system has an additional emergency response mechanism to alert nearby community healthcare workers when SCD is predicted to occur.

Keywords: ECG-Based Alert System for Cardiac Death Risk Rescue; Edge computing; Electrocardiogram; Healthcare; Wearables.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image, graphical abstract
Graphical abstract
Fig 1
Fig. 1
The wearable device can detect ECG signals without special electrodes attached to the chest and upload signals to edge-computing services and mobile phones.
Fig 2
Fig. 2
The whole architecture of the emergency aid system. The extended module is proposed but not implemented. The system consists of wearable ECG detectors with Bluetooth modules for patients, edge services, and software for information users (doctors).
Fig 3
Fig. 3
Circuit diagram. There are three modules: the ECG module using a BMD101 System on Chip (SoC), the power adapter module, and the Bluetooth module.
Fig 4
Fig. 4
The hardware includes an ECG, a Bluetooth module, gloves made of silver fiber, and electrodes. The electrodes are a snap that can easily snap together.
Fig 5
Fig. 5
Cloud computing logic flow.
Fig 6
Fig. 6
Subscriber software logic flow.
Fig 7
Fig. 7
The experiment of upload performance. (a) The connection diagram of the speed test of ECG data uploaded by Bluetooth at various distances. (b) The link test diagram of a community doctor's device connecting to an edge computing service. (c) Combine (a) and (b) for test.
Fig 8
Fig. 8
Simulates connections of scenarios: (a) Case A experiments that a room obstacle the signal between transmitter and receiver. (b) Case B shows that a solid wall obstructs the transmitter and receiver signal. (c) Case C experiments with a right-angle wall obstacle to the signal between the transmitter and receiver.
Fig 9
Fig. 9
Upload performance data.
Fig 10
Fig. 10
Scenario simulation results from the transmission speed through a right-angled and solid wall.
Fig 11
Fig. 11
ECG signal displayed on a mobile phone (subscriber).
See this image and copyright information in PMC

References

    1. Lucena J.S. Sudden cardiac death. Forensic Sci. Res. 2019;4:199–201. doi: 10.1080/20961790.2019.1622062. - DOI - PMC - PubMed
    1. Velázquez-González J.R., Peregrina-Barreto H., Rangel-Magdaleno J.J., Ramirez-Cortes J.M., Amezquita-Sanchez J.P. ECG-based identification of sudden cardiac death through sparse representations. Sensors. 2021;21:7666. doi: 10.3390/s21227666. - DOI - PMC - PubMed
    1. Shanin F., Aiswarya Das H.A., Arya Krishnan G., Neha L.S., Thaha N., Aneesh R.P., Embrandiri S., Jayakrishan S. 2018 International CET Conference on Control, Communication, and Computing (IC4) IEEE; 2018. Portable and centralised e-health record system for patient monitoring using internet of things(IoT; pp. 165–170. - DOI
    1. Amezquita-Sanchez J.P., Valtierra-Rodriguez M., Adeli H., Perez-Ramirez C.A. A novel wavelet transform-homogeneity model for sudden cardiac death prediction using ECG signals. J. Med. Syst. 2018;42:176. doi: 10.1007/s10916-018-1031-5. - DOI - PubMed
    1. Xu G. IoT-assisted ECG monitoring framework with secure data transmission for health care applications. IEEe Access. 2020;8:74586–74594. doi: 10.1109/ACCESS.2020.2988059. - DOI

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