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Optimization of signal quality over comfortability of textile electrodes for ECG monitoring in fog computing based medical applications
Wu W, Pirbhulal S, , Mukhopadhyay S.C, Li G.
Published in Elsevier BV
2018
Volume: 86
   
Pages: 515 - 526
Abstract
Fog computing is the backbone of modern healthcare systems, it not only cut-downs the associated treatment and medicine costs but also decreases the logistics requirements. Recently, both stationary and wearable systems are utilized for long-term monitoring of Electrocardiogram (ECG) signals in fog computing based medical applications. However, the comfort of monitored patients is not at a satisfactory level and therefore, a well-designed textile electrode with excellent signal quality and comfortability (SQC) plays a significant role in collecting ECG signals. In this study, in order to provide SQC optimization, a textile electrode with knitted structure and conductive material comprising cotton /nylon fiber coated silver is investigated. This textile composite is integrated to a wearable carrier (T-Shirt) with a miniaturized wireless sensing platform to collect ECG signals from the human. As a design strategy to acquire dimensional stability, the fabric was knitted with two layers that form the same technical face on both fabric surfaces. The conducted experiment elaborate that to find out a balance between the quality of signal and wearable comfort level by finely adjusting the composition of fiber type, yarn density, fabric pattern, fabric density, and thickness. From our experimental results, it is observed that textile electrodes having cotton (30) /nylon fiber coated silver (70) provides less air resistance (0.17 KPa•s/m), optimized tactile comfort (9/10), reasonable signal to noise ratio (SNR) value of 30.78dB, and better thermal conductivity (0.018W/m•K) than compared electrodes. Thus, it can be concluded that developed textile electrode can be useful for future research to offer the balance for SQC ratio for ECG measurement in fog computing based healthcare systems. © 2018 Elsevier B.V.
About the journal
JournalData powered by TypesetFuture Generation Computer Systems
PublisherData powered by TypesetElsevier BV
ISSN0167-739X
Open Access0