Wireless ECG Monitoring System for Telemedicine Application

Aboalseoud, Ahmed; Youssry, Akram; El-Nozahi, Mohamed; El-Rafei, Ahmed; El-Bialy, Ahmed M.; Ragaai, Hani; Wahba, Ayman

doi:10.1109/icicis46948.2019.9014845

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…Excluding the effects of the skin-electrode model, and considering an ideal DUT, with infinite bandwidth and a gain which cancels the attenuation imposed by the differential attenuator (refer to figures 1 and 2), a cut-off frequency of 194 Hz is obtained for the complete system. This frequency lays above the 150 Hz LPF cut-off frequency recommended for diagnosis electrocardiography [31][32][33], and the 40 Hz frequency recommended for general purpose ECG acquisition [31]. The simulated frequency response of the system is presented in figure 10.…”

Section: System's Bandwidthmentioning

confidence: 93%

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ECG simulator with configurable skin-electrode impedance and artifacts emulation

Almeida¹,

Costa²,

Lourenço³

2021

Biomed. Phys. Eng. Express

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Electrocardiograms (ECG) recorded from everyday objects, such as wearables, fitness machines or smart steering wheels are becoming increasingly common. Applications are diverse and include health monitoring, athletic performance optimization, identification, authentication, and entertainment. In this study we report the design and implementation of an innovative ECG simulator, providing simulation of signal related artifacts and a dynamically adjustable skin-electrode interface model. The ECG simulator includes a unique combination of features: emulation of time dependent skinelectrode impedance, adjustable differential and common-mode interference, generation of lead-off events and analog front-end output digitalization. The skin-electrode capacitance range is 1 nF-255 nF and the resistance span is 4 kΩ-996 kΩ. System's functionality is demonstrated using a commercially available ECG front-end. The simulated SNR degradation introduced by the ECG simulator is under 0.1 dB. Results show that the skin-electrode interface can have a significant impact in the acquired waveforms. Impedance electrode imbalance, specifically of the resistive component, can generate artifacts which can be misinterpreted has arrhythmias. The proposed device can be useful for hardware and software ECG development and for training physicians and nurses to readily recognize skin-electrode impedance related artifacts.

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Section: System's Bandwidthmentioning

confidence: 93%

“…The minimum recommended cut-off frequency for ECG applications is 40 Hz for general use ECG devices [31] and 150 Hz for diagnostic ECG [31][32][33]. The DAC's sampling frequency, f S , was set to 1 kHz and the reconstruction filter to f S /4, to achieve greater attenuation above Nyquist frequency and to limit noise bandwidth.…”

Section: Signal Generation Modulementioning

confidence: 99%

ECG simulator with configurable skin-electrode impedance and artifacts emulation

Almeida¹,

Costa²,

Lourenço³

2021

Biomed. Phys. Eng. Express

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“…The QRS complex wave is the most important part of the cardiac system to determine. The ECG parameters normal values are shown in Table 1 [22], [23], [24].…”

Section: Fig 1 -The Classification Of Health Monitoring Systems [14]mentioning

confidence: 99%

“…ECG data collected from sensors is transmitted via a particular wireless protocol to the IoT cloud, such as Wi-Fi, Bluetooth, ZigBee, etc. [23]. These three protocols provide adequate data rates while consuming energy at an acceptable level.…”

Section: Data Transmissionmentioning

confidence: 99%

Smart Healthcare for ECG Telemonitoring System

Saeed¹,

Ameen

2021

JSCDM

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Cardiovascular disorders are one of the major causes of sad death among older and middle-aged people. Over the past two decades, health monitoring services have evolved quickly and had the ability to change the way health care is currently provided. However, the most challenging aspect of the mobile and wearable sensor-based human activity recognition pipeline is the extraction of the related features. Feature extraction decreases both computational complexity and time. Deep learning techniques are used for automatic feature learning in a variety of fields, including health, image classification, and, most recently, for the extraction and classification of complex and straightforward human activity recognition in smart health care. This paper reviews the recent state of the art in electrocardiogram (ECG) smart health monitoring systems based on the Internet of things with the machine and deep learning techniques. Moreover, the paper provided possible research and challenges that can help researchers advance state of art in future work.

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“…The internet of things (IoT) consists of small devices with a microprocessor and a battery, this device is used to collect data of its environment if the battery energy allows it. Latter the data is transmitted through a wireless link like GSM-GPRS [1], Wi-Fi [2], Bluetooth [3] or some sort of wireless communication that allows multiple connection between various devices [4]. Since IoT devices are designed to work alone the battery size and energy are restricted, therefore research efforts are aimed at saving energy consumption [5] [6].…”

Section: Introductionmentioning

confidence: 99%

Analysis on the Current Consumption of Applying the Huffman Codification for Data Transmission using the ESP-NOW Protocol

Luis¹,

Julio²,

Joel³

2023

IJETAE

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IoT devices have restrictions regarding their energy consumption. Their hardware allows them to consume less energy to work for long periods of time with a small battery. Research works that are aimed at decreasing energy consumption, focus on the device hardware components, while other research focus on transmission algorithms to reduce the number of transmissions. In this context compression algorithms play an important role in reducing the amount of data to transmit. The Huffman codification is very easy to understand and has many source codes available. Therefore, this research focuses on quantifying the amount of energy saved after applying the Huffman codification. The tests were performed using the ESP32 which has an integrated Wi-Fi radio; and has the ESP-NOW protocol to transmit data between two devices without too much hardware setup. The results show that as more data is compressed the device energy consumption tends to reduce by 2 mA after continuous transmissions. The final energy consumption value is similar to the device current consumption while processing data.

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Wireless ECG Monitoring System for Telemedicine Application

Cited by 9 publications

References 15 publications

ECG simulator with configurable skin-electrode impedance and artifacts emulation

ECG simulator with configurable skin-electrode impedance and artifacts emulation

Smart Healthcare for ECG Telemonitoring System

Analysis on the Current Consumption of Applying the Huffman Codification for Data Transmission using the ESP-NOW Protocol

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