BibTex format

author = {Imtiaz, SA and Mardell, JAMES and Saremi-Yarahmadi, SIAVASH and Rodriguez, Villegas ESTHER},
doi = {10.1049/htl.2016.0020},
journal = {Healthcare Technology Letters},
pages = {171--176},
title = {ECG Artefact Identification and Removal in mHealth Systems for Continuous Patient Monitoring},
url = {},
volume = {3},
year = {2016}

RIS format (EndNote, RefMan)

AB - Continuous patient monitoring systems acquire enormous amounts of data that is either manually analysed by doctors or automaticallyprocessed using intelligent algorithms. Sections of data acquired over long period of time can be corrupted with artefacts due to patientmovement, sensor placement and interference from other sources. Because of the large volume of data these artefacts need to be automaticallyidentified so that the analysis systems and doctors are aware of them while making medical diagnosis. This paper explores three importantfactors that must be considered and quantified for the design and evaluation of automatic artefact identification algorithms: signal quality,interpretation quality and computational complexity. The first two are useful to determine the effectiveness of an algorithm while the third isparticularly vital in mHealth systems where computational resources are heavily constrained. A series of artefact identification and filteringalgorithms are then presented focusing on the electrocardiography data. These algorithms are quantified using the three metrics to demonstratehow different algorithms can be evaluated and compared to select the best ones for a given wireless sensor network.
AU - Imtiaz,SA
AU - Mardell,JAMES
AU - Saremi-Yarahmadi,SIAVASH
AU - Rodriguez,Villegas ESTHER
DO - 10.1049/htl.2016.0020
EP - 176
PY - 2016///
SN - 2053-3713
SP - 171
TI - ECG Artefact Identification and Removal in mHealth Systems for Continuous Patient Monitoring
T2 - Healthcare Technology Letters
UR -
UR -
VL - 3
ER -