Design of a low power ECG signal processor for wearable health system-review and implementation issues

2017 ◽  
Author(s):  
K. Raja ◽  
S. Saravanan ◽  
R. Anitha ◽  
S. Suganthi Priya ◽  
R. Subhashini
Keyword(s):  
Low Power ◽  
Health System ◽  
Ecg Signal ◽  
System Review ◽  
Signal Processor

An Ultra-Low Power Holter and Low Complexity Design Using Mixed Signal Processor

2013 ◽  
Vol 284-287 ◽  
pp. 1627-1632
Author(s):  
Hsieh Chang Huang ◽  
Ching Tang Hsieh ◽  
Guang Lin Hsieh
Keyword(s):  
Low Power ◽  
Analog Circuits ◽  
Finite Impulse Response ◽  
Low Complexity ◽  
Fir Filter ◽  
Ecg Signal ◽  
Ultra Low Power ◽  
Mixed Signal ◽  
Sd Card ◽  
Signal Processor

An ultra-low power, portable, and easily implemented Holter recorder is necessary for patients or researchers of electrocardiogram (ECG). Such a Holter recorder with off-the-shelf components is realized with mixed signal processor (MSP) in this paper. To decrease the complexity of analog circuits and the interference of 60 Hz noise from power line, we use the MSP to implement a finite impulse response (FIR) filter which is equiripple design. We also integrate the ring buffer for the input samples and the symmetrical characteristic of the FIR filter for efficiently computing convolution. The experimental results show that the ECG output signal with the PQRST feature is easy to be distinguished. This ECG signal is recorded for 24 hours using a SD card. Furthermore, the ECG signal is transmitted with a smartphone via Bluetooth to decrease the burden of the Holter recorder. As a result, this paper uses the Lomb method for the spectral analysis of Heart Rate Variability (HRV) better than Fast Fourier Transform (FFT).

A low power ECG signal processor for ambulatory arrhythmia monitoring system

2010 ◽  
Author(s):  
Hyejung Kim ◽  
Refet Firat Yazicioglu ◽  
Tom Torfs ◽  
Patrick Merken ◽  
Hoi-Jun Yoo ◽  
...  
Keyword(s):  
Low Power ◽  
Monitoring System ◽  
Ecg Signal ◽  
Signal Processor

WBAN Based Long Term ECG Monitoring

2013 ◽  
Vol 1 (3) ◽  
pp. 20-37 ◽  
Author(s):  
Marius Rosu ◽  
Sever Pasca
Keyword(s):  
Low Power ◽  
Sensor Nodes ◽  
Ecg Signal ◽  
Area Network ◽  
Wireless Sensor Nodes ◽  
Medication Process ◽  
Remote Healthcare ◽  
Electrocardiogram Ecg ◽  
Supply Information

Healthcare solutions using anytime, and anywhere remote healthcare surveillance devices, have become a major challenge. The patients with chronic diseases who need only therapeutic supervision are not advised to occupy a hospital bed. Using Wearable Wireless Body/Personal Area Network (WWBAN), intelligent monitoring of heart can supply information about medical conditions. Electrocardiogram (ECG) is the core reference in the diagnosis and medication process. An approach on healthcare solution WBAN based, for real-time ECG signal monitoring and long-term recording will be presented. Low-power wireless sensor nodes with local processing and encoding capabilities in order to achieve maximum mobility and flexibility are our main goal. ZigBee wireless technology will be used for transmission. Sensor device will be programmed to process locally the ECG signal and to raise an alert. Low-power and miniaturization are essential physical requirements.

A fetal ECG signal monitoring system using digital signal processor

2003 ◽  
Author(s):  
Y.C. Park ◽  
B.M. Cho ◽  
N.H. Kim ◽  
W.K. Kim ◽  
S.H. Park ◽  
...  
Keyword(s):  
Monitoring System ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Ecg Signal ◽  
Fetal Ecg ◽  
Signal Monitoring ◽  
Signal Processor

Implementation of a real-time ECG signal processor

2014 ◽  
Author(s):  
Shih-Yu Chang Chien ◽  
Cheng-Han Hsieh ◽  
Mark Po-Hung Lin ◽  
Qiang Fang ◽  
Shuenn-Yuh Lee
Keyword(s):  
Real Time ◽  
Ecg Signal ◽  
Signal Processor

scholarly journals A Low-Power High-Data-Transmission Multi-Lead ECG Acquisition Sensor System

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4996 ◽  
Author(s):  
Liang-Hung Wang ◽  
Wei Zhang ◽  
Ming-Hui Guan ◽  
Su-Ya Jiang ◽  
Ming-Hui Fan ◽  
...  
Keyword(s):  
Low Power ◽  
Clinical Diagnosis ◽  
Medical Staff ◽  
Supply Voltage ◽  
Sampling Rate ◽  
Low Power Design ◽  
Sensor System ◽  
Acquisition System ◽  
Ecg Signal ◽  
Acquisition Device

This study presents a low-power multi-lead wearable electrocardiogram (ECG) signal sensor system design that can simultaneously acquire the electrocardiograms from three leads, I, II, and V1. The sensor system includes two parts, an ECG test clothing with five electrode patches and an acquisition device. Compared with the traditional 12-lead wired ECG detection instrument, which limits patient mobility and needs medical staff assistance to acquire the ECG signal, the proposed vest-type ECG acquisition system is very comfortable and easy to use by patients themselves anytime and anywhere, especially for the elderly. The proposed study incorporates three methods to reduce the power consumption of the system by optimizing the micro control unit (MCU) working mode, adjusting the radio frequency (RF) parameters, and compressing the transmitted data. In addition, Huffman lossless coding is used to compress the transmitted data in order to increase the sampling rate of the acquisition system. It makes the whole system operate continuously for a long period of time and acquire abundant ECG information, which is helpful for clinical diagnosis. Finally, a series of tests were performed on the designed wearable ECG device. The results have demonstrated that the multi-lead wearable ECG device can collect, process, and transmit ECG data through Bluetooth technology. The ECG waveforms collected by the device are clear, complete, and can be displayed in real-time on a mobile phone. The sampling rate of the proposed wearable sensor system is 250 Hz per lead, which is dependent on the lossless compression scheme. The device achieves a compression ratio of 2.31. By implementing a low power design on the device, the resulting overall operational current of the device is reduced by 37.6% to 9.87 mA under a supply voltage of 2.1 V. The proposed vest-type multi-lead ECG acquisition device can be easily employed by medical staff for clinical diagnosis and is a suitable wearable device in monitoring and nursing the off-ward patients.

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