A new physiological signal acquisition patch designed with advanced respiration monitoring algorithm based on 3-axis accelerator and gyroscope

2018 ◽  
Author(s):  
Sikai Wang ◽  
Ming Liu ◽  
Bo Pang ◽  
Peng Li ◽  
Zhaolin Yao ◽  
...  
Keyword(s):  
Signal Acquisition ◽  
Respiration Monitoring ◽  
Physiological Signal ◽  
Monitoring Algorithm

scholarly journals Design of Pulse Wave Feature Vigilance Detection System Based on Computer Software Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yidong Zeng ◽  
Jun Ji ◽  
Jinghua Wang ◽  
Jiasuo Gao ◽  
Jie Hu ◽  
...  
Keyword(s):  
Pulse Wave ◽  
Detection System ◽  
Skin Resistance ◽  
Computer Software ◽  
Pulse Amplitude ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Blood Oxygen Saturation ◽  
Software Technology ◽  
Physiological Signal

In this paper, the pulse wave feature alertness detection system based on computer software technology is researched. First, the computer software technology designs the alertness detection system and then conducts the system alertness test experiment using a system that can not affect the subjects’ alertness, a portable multichannel physiological signal acquisition system that measures the subjects’ ECG signal, skin resistance, blood oxygen saturation, and other physiological signals in the case of a degree task experiment. The multichannel physiological signal acquisition system collects the signals during the vigilance task experiment. At the same time, before, during, and after the experiment, subjects are required to fill in the Stanford Sleepiness Scale (SSS) and evaluate the level of individual alertness through subjective self-evaluation. The relevant experimental data show that, 10 minutes before the experiment, the pulse amplitude increased rapidly, then slowly decreased at the beginning, reached a peak in about 25 minutes, and then began to rise.

Design of ECG Signal Acquisition and Processing Circult

2012 ◽  
Vol 236-237 ◽  
pp. 856-861 ◽  
Author(s):  
Jing Ma ◽  
Jun Xu ◽  
Hai Bo Xu ◽  
Yu Wang ◽  
Sheng Xu Yin
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Low Frequency ◽  
Low Noise ◽  
Cardiac Conduction ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Physiological Signal ◽  
Heart Study ◽  
Low Pass

ECG signal is, as a vital method performed on the heart study and clinical diagnosis of cardiovascular diseases, an important human physiological signal, containing the human cardiac conduction system of physiological and pathological information. Aiming at the weak low frequency characteristic of ECG signals, the core circuit based on the AD620 and LM324 amplifier is given. After analyzing the major components of the ECG signal and the frequency range of interference, weak ECG signal collected by the electrodes is amplified by the preamplifier circuit, and the interference then is wiped out by using a low-pass filer, a high-pass filer, 50Hz notch filer and back amplifier circuit, finally a right wave of ECG is received. The characteristics of the system features the merits of high input impedance, high CMRR, low noise, less excursion and high SNR(signal to noise ratio), low cost and so on.

Context-Aware Monitoring of Cardiac Health

2012 ◽  
Vol 239-240 ◽  
pp. 785-793
Author(s):  
Han Xiao Wu ◽  
Lian Ying Ji ◽  
Jian Kang Wu
Keyword(s):  
Original Data ◽  
Signal Acquisition ◽  
Context Aware ◽  
Human Machine Interaction ◽  
Cardiac Health ◽  
Physiological Signal ◽  
Health Indices ◽  
Status Monitoring ◽  
Sd Card ◽  
Machine Interaction

As the technology of sensor network advances, wearable health monitoring becomes feasible. Here we present a context-aware monitoring system for cardiac health, which consists of three modules: signal acquisition for physiological signal as well as context information; processing, analysis and interpretation of signal modality as well as fusion of context to generate cardiac health indices; interface for human-machine interaction. Both captured original data and analysis results are stored in an SD card for further processing in the server. The system works continuously for 24 hours. The proposed cardiac health indices can be applied for health status monitoring and early prediction of cardiovascular disease.

Sign in / Sign up

Export Citation Format

Share Document