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Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms. (2023)
Conference Proceeding
FOUGH, F., JANJUA, G., ZHAO, Y. and DON, A.W. 2023. Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea (MetroSea 2023); learning to measure sea health parameters, 4-6 October 2023, La Valletta, Malta. Piscataway: IEEE [online], pages 121-126. Available from: https://doi.org/10.1109/MetroSea58055.2023.10317294

Antimicrobial resistance (AMR) is an increasingly critical public health issue necessitating precise and efficient methodologies to achieve prompt results. The accurate and early detection of AMR is crucial, as its absence can pose life-threatening r... Read More about Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms..

Influence of the training set composition on the estimation performance of linear ECG-lead transformations. (2023)
Conference Proceeding
GULDENRING, D., FINLAY, D.D., BOND, R.R., KENNEDY, A., DOGGART, P., JANJUA, G. and MCLAUGHLIN, J. 2023. Influence of the training set composition on the estimation performance of linear ECG-lead transformations. In Proceedings of the 50th Computing in cardiology 2023 (CinC 2023), 1-4 October 2023, Atlanta, GA, USA. Piscataway: IEEE/CinC [online], 50, article number 263. Available from: https://doi.org/10.22489/CinC.2023.263

Linear ECG-lead transformations (LELTs) are used to estimate unrecorded target leads by applying a number of recorded basis leads to a LELT matrix. Such LELT matrices are commonly developed using training datasets that are composed of ECGs that belon... Read More about Influence of the training set composition on the estimation performance of linear ECG-lead transformations..

Use of optimized centroid and weighted centroid algorithms to locate a partial discharge source by using received signal strength. (2021)
Conference Proceeding
KHAN, U.F., JANJUA, G.M.W., AYUB, A., ILYAS, M.A., SHAHZAD, K. and MOHAMED, H. 2020. Use of optimized centroid and weighted centroid algorithms to locate a partial discharge source by using received signal strength. In Proceedings of 23rd Wireless personal multimedia communications symposium 2020 (WPMC2020): bridging wireless and business worlds, 19-26 October 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9309452. Available from: https://doi.org/10.1109/WPMC50192.2020.9309452

Received signal strength (RSS) based localization of a source is a simple but effective technique. In RSS based localization source location is estimated by converting obtained signal into distance. In this paper, centroid and weighted centroid algor... Read More about Use of optimized centroid and weighted centroid algorithms to locate a partial discharge source by using received signal strength..

Heartrate variability comparison between electrocardiogram, photoplethysmogram and ballistic pulse waveforms at fiducial points. (2017)
Conference Proceeding
JANJUA, G.M.W., HADIA, R., GULDENRING, D., FINLAY, D.D. and MCLAUGHLIN, J.A.D. 2018. Heartrate variability comparison between electrocardiogram, photoplethysmogram and ballistic pulse waveforms at fiducial points. In Maglaveras, N., Chouvarda, I. and de Carvalho, P. (eds.) Precision medicine powered by pHealth and connected health: proceedings of 3rd International conference on biomedical and health informatics (ICBHI 2017), 18-21 November 2017, Thessaloniki, Greece. IFMBE proceedings, 66. Singapore: Springer [online], pages 171-177. Available from: https://doi.org/10.1007/978-981-10-7419-6_29

Heart rate variability analysis (HRVA) gives valuable insight to the cardiovascular system. Electrocardiogram (ECG) based HRVA has been assessment gold standard but eavesdropping of wearable technology requires the comparison of its surrogacy to an a... Read More about Heartrate variability comparison between electrocardiogram, photoplethysmogram and ballistic pulse waveforms at fiducial points..

Wireless chest wearable vital sign monitoring platform for hypertension. (2017)
Conference Proceeding
JANJUA, G., GULDENRING, D., FINLAY, D. and MCLAUGHLIN, J. 2017. Wireless chest wearable vital sign monitoring platform for hypertension. In Proceedings of the 39th Institute of Electrical and Electronics Engineers (IEEE) Engineering in Medicine and Biology Society annual international conference 2017 (EMBC 2017): smarter technology for a healthier world, 11-15 July 2017, Jeju, South Korea. Piscataway: IEEE [online], pages 821-824. Available from: https://doi.org/10.1109/EMBC.2017.8036950

Hypertension, a silent killer, is the biggest challenge of the 21 st century in public health agencies worldwide. World Health Organization (WHO) statistic shows that the mortality rate of hypertension is 9.4 million per year and causes 55.3% of tota... Read More about Wireless chest wearable vital sign monitoring platform for hypertension..

Morphology-based detection of premature ventricular contractions (2017)
Conference Proceeding
HADIA, R., GULDENRING, D., FINLAY, D.D., KENNEDY, A., JANJUA, G., BOND, R. and MCLAUGHLIN, J. 2017. Morphology-based detection of premature ventricular contractions. In Proceedings of 2017 Computing in cardiology, 24-27 September 2017, Rennes, France. Piscataway: IEEE [online], 44, pages 1-4. Available from: https://doi.org/10.22489/CinC.2017.211-260

Premature ventricular contraction (PVC) is the type of ectopic heartbeat, commonly found in the healthy population and is often considered benign. However, they are reported to adversely affect the accuracy of R-R variability based electrocardiograph... Read More about Morphology-based detection of premature ventricular contractions.