A real-time physiological signal acquisition and analyzing method based on fractional calculus and stream computing

2020 ◽  
Author(s):  
Taizhi Lv ◽  
Lian Tong ◽  
Jun Zhang ◽  
Yong Chen
Keyword(s):  
Fractional Calculus ◽  
Real Time ◽  
Signal Acquisition ◽  
Stream Computing ◽  
Physiological Signal

scholarly journals A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 104
Author(s):  
Jin-Woo Jeong ◽  
Woochan Lee ◽  
Young-Joon Kim
Keyword(s):  
Real Time ◽  
Physiological Data ◽  
Process Time ◽  
P Value ◽  
Signal Acquisition ◽  
Daily Routine ◽  
Physiological Signal ◽  
Emg Signal ◽  
Compact Size ◽  
Signal Coverage

The acquisition of physiological data are essential to efficiently predict and treat cardiac patients before a heart attack occurs and effectively expedite motor recovery after a stroke. This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring. In this paper, we present a wireless physiological signal acquisition device and a smartphone-based software platform for real-time data processing and monitor and cloud server access for everyday ECG/EMG signal monitoring. The device is implemented in a compact size (diameter: 30 mm, thickness: 4.5 mm) where the biopotential is measured and wirelessly transmitted to a smartphone or a laptop for real-time monitoring, data recording and analysis. Adaptive digital filtering is applied to eliminate any interference noise that can occur during a regular at-home environment, while minimizing the data process time. The accuracy of ECG and EMG signal coverage is assessed using Bland–Altman analysis by comparing with a reference physiological signal acquisition instrument (RHS2116 Stim/Recording System, Intan). Signal coverage of R-R peak intervals showed almost identical outcome between this proposed work and the RHS2116, showing a mean difference in heart rate of 0.15 4.65 bpm and a Wilcoxon’s p value of 0.133. A 24 h continuous recording session of ECG and EMG is conducted to demonstrate the robustness and stability of the device based on extended time wearability on a daily routine.

scholarly journals Re-Stream: Real-time and energy-efficient resource scheduling in big data stream computing environments

2015 ◽  
Vol 319 ◽  
pp. 92-112 ◽  
Author(s):  
Dawei Sun ◽  
Guangyan Zhang ◽  
Songlin Yang ◽  
Weimin Zheng ◽  
Samee U. Khan ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Energy Efficient ◽  
Data Stream ◽  
Resource Scheduling ◽  
Stream Computing ◽  
Efficient Resource ◽  
Computing Environments ◽  
Time And Energy

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.

scholarly journals An Improved High-Intelligence Method of Gas and Oil Pipeline Prewarning System in Real Soil Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Fang Wang ◽  
Jichuan Xing ◽  
Jinxin Li ◽  
Feng Zhao ◽  
Shufeng Zhang
Keyword(s):  
Optical Fiber ◽  
Real Time ◽  
Recognition Accuracy ◽  
Signal Acquisition ◽  
Soil Environment ◽  
Long Distance ◽  
Vibration Signals ◽  
Oil Pipeline ◽  
Time Performance ◽  
High Intelligence

With the development of technology, the total extent of global pipeline transportation is also increased. However, the traditional long-distance optical fiber prewarning system has poor real-time performance and high false alarm rate when recognizing events threatening pipeline safety. The same vibration signal would vary greatly when collected in different soil environments and this problem would reduce the signal recognition accuracy of the prewarning system. In this paper, we studied this effect theoretically and analyzed soil vibration signals under different soil conditions. Then we studied the signal acquisition problem of long-distance gas and oil pipeline prewarning system in real soil environment. Ultimately, an improved high-intelligence method was proposed for optimization. This method is based on the real application environment, which is more suitable for the recognition of optical fiber vibration signals. Through experiments, the method yielded high recognition accuracy of above 95%. The results indicate that the method can significantly improve signal acquisition and recognition and has good adaptability and real-time performance in the real soil environment.

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