An ECG front-end subsystem for portable physiological monitoring applications

2011 ◽  
Author(s):  
Hsiu-Cheng Lee ◽  
Ching-Sung Lee ◽  
Yu-Ming Hsiao ◽  
Miin-Shyue Shiau ◽  
Kuang-Hung Chen ◽  
...  
Keyword(s):  
Physiological Monitoring ◽  
Front End ◽  
Monitoring Applications

scholarly journals Augmentation of Dispersion Entropy for Handling Missing and Outlier Samples in Physiological Signal Monitoring

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 319 ◽  
Author(s):  
Evangelos Kafantaris ◽  
Ian Piper ◽  
Tsz-Yan Milly Lo ◽  
Javier Escudero
Keyword(s):  
Time Series ◽  
Wearable Devices ◽  
Physiological Monitoring ◽  
Disruptive Effect ◽  
Respiratory Impedance ◽  
Common Occurrence ◽  
Original Algorithm ◽  
Physiological Signal ◽  
Monitoring Applications ◽  
Improved Performance

Entropy quantification algorithms are becoming a prominent tool for the physiological monitoring of individuals through the effective measurement of irregularity in biological signals. However, to ensure their effective adaptation in monitoring applications, the performance of these algorithms needs to be robust when analysing time-series containing missing and outlier samples, which are common occurrence in physiological monitoring setups such as wearable devices and intensive care units. This paper focuses on augmenting Dispersion Entropy (DisEn) by introducing novel variations of the algorithm for improved performance in such applications. The original algorithm and its variations are tested under different experimental setups that are replicated across heart rate interval, electroencephalogram, and respiratory impedance time-series. Our results indicate that the algorithmic variations of DisEn achieve considerable improvements in performance while our analysis signifies that, in consensus with previous research, outlier samples can have a major impact in the performance of entropy quantification algorithms. Consequently, the presented variations can aid the implementation of DisEn to physiological monitoring applications through the mitigation of the disruptive effect of missing and outlier samples.

A 32-channel front-end ASIC for GEM detectors used in beam monitoring applications

2017 ◽  
Vol 12 (11) ◽  
pp. T11005-T11005 ◽  
Author(s):  
F. Ciciriello ◽  
P.R. Altieri ◽  
F. Corsi ◽  
G. De Robertis ◽  
G. Felici ◽  
...  
Keyword(s):  
Front End ◽  
Monitoring Applications ◽  
Beam Monitoring ◽  
Gem Detectors

A high CMRR analog front-end IC for wearable physiological monitoring

2012 ◽  
Author(s):  
D. Susheel Kumar ◽  
K. P. Safeer ◽  
P. S. Pandian ◽  
V. C. Padaki ◽  
D. Shravan Kumar ◽  
...  
Keyword(s):  
Physiological Monitoring ◽  
Front End ◽  
Analog Front End ◽  
High Cmrr

Growth of CNT array for physiological monitoring applications

2008 ◽  
Author(s):  
J. K. Radhakrishnan ◽  
H. Bhusan ◽  
P. S. Pandian ◽  
K. U. B. Rao ◽  
V. C. Padaki ◽  
...  
Keyword(s):  
Physiological Monitoring ◽  
Monitoring Applications
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