Skin-interfaced wireless wearables for physiological monitoring: Applications in syndromic tracking of COVID19

2021 ◽  
Author(s):  
John A. Rogers
Keyword(s):  
Physiological Monitoring ◽  
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.

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

scholarly journals Development of a Novel Contactless Mechanocardiograph Device

2008 ◽  
Vol 2008 ◽  
pp. 1-5 ◽  
Author(s):  
Kouhyar Tavakolian ◽  
Faranak M. Zadeh ◽  
Yindar Chuo ◽  
Ali Vaseghi ◽  
Bozena Kaminska
Keyword(s):  
Heart Rate ◽  
Respiration Rate ◽  
Research Work ◽  
Physiological Monitoring ◽  
Monitoring Applications ◽  
Novel Method ◽  
Highly Correlated ◽  
Mechanical Movement

A novel method of detecting mechanical movement of the heart, Mechanocardiography (MCG), with no connection to the subject's body is presented. This measurement is based on radar technology and it has been proven through this research work that the acquired signal is highly correlated to the phonocardiograph signal and acceleration-based ballistocardiograph signal (BCG) recorded directly from the sternum. The heart rate and respiration rate have been extracted from the acquired signal as two possible physiological monitoring applications of the radar-based MCG device.

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