Arm-based Wearable Sensing Techniques for Diagnostic Methods in Long-term Monitoring of ECG and ICG of Heart Failure and Atrial Fibrillation.

Apply and key information  

This project is funded by:

    • Department for the Economy (DfE)

Summary

Atrial fibrillation (AF) and heart failure (HF) are often manifest as coexistent conditions increasingly recognised as global cardiovascular epidemics over the last decade and expected to increase in prevalence over the coming years. Cardiac rhythm monitoring is important for the early diagnosis of these cardiac conditions. Furthermore, non-invasive, long-term cardiac output (CO) and left-ventricular ejection time (LVET) measurements from impedance cardiography (ICG) signal recording is currently not available. An implantable-loop-recorder (ILR) would accurately monitor cardiac rhythm for extended periods, but they cannot monitor CO; additionally, they require a surgical procedure. The simultaneous integration of long-term non-invasive ECG and ICG signal recordings and real-time arrhythmia detection, would be a significant advance on current cardiac diagnostic methodologies and enabling technologies. A wearable cardiac monitoring armband device would offer advantages for long-term continuous recordings of cardiac vital signals (ECG and ICG): no adhesives, no irritating electrode gels, no connecting cables and comfortable to wear. Thus, automatic ECG-based detection/classification of AF in addition to ICG sensing from the arm location will be evaluated as non-conventional alternative methods. Reproducibility agreement assessed against conventional sensing methods on the chest. A clinical knowledge database from patient armband ECG and ICG recordings gathered from the Craigavon Area Hospital (Northern Ireland) will be made available, allowing production of linear regression models to predict conventional (chest based sensors) ICG hemodynamic measurements.

AF and HF armband methods and technology will have multiple applications, addressing significant unmet needs in clinical cardiology. It will be useful in the diagnosis of palpitations, dizzy episodes and HF signs of common presentations in general practice. Detection of atrial fibrillation will allow early treatment with reduction in stroke risk.

A PhD researcher for this project having a major background knowledge in the fields of Biomedical Engineering and/or Electronic Engineering, with additional expertise in digital-signal-processing, would be advantageous.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

  • Experience using research methods or other approaches relevant to the subject domain
  • A comprehensive and articulate personal statement

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Masters at 65%
  • Publications - peer-reviewed

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

  • Department for the Economy (DfE)

These scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of £900 per annum is also available.

To be eligible for these scholarships, applicants must meet the following criteria:

  • Be a UK National, or
  • Have settled status, or
  • Have pre-settled status, or
  • Have indefinite leave to remain or enter, or
  • be an Irish National

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.

Recommended reading

  • Lee Park K, Anter E. (2013). Atrial Fibrillation and Heart Failure: A Review of the Intersection of Two Cardiac Epidemics. J Atr Fibrillation. 2013;6(1):751. Published 2013 Jun 30. doi:10.4022/jafib.751
  • Hayashi H, Abe Y, Morita Y, et al. (2019). Impact of stroke volume on prognostic outcome in patients with atrial fibrillation and concomitant heart failure with preserved ejection fraction. J Cardiol. 2019;73(4):307-312. doi:10.1016/j.jjcc.2018.12.011
  • Escalona OJ, Abdul-Qayum G, Hilton A, et al.(2022). Cardiac contractility assessment from arm impedance plethysmography (IPG). World Congress on Medical Physics and Biomedical Engineering, IFMBE Proceedings, accepted (21/Feb-2022), in press.
  • Lynn WD, Escalona OJ, McEneaney, DJ(2013), “Arm and wrist surface potential mapping for wearable ECG rhythm recording devices: a pilot clinical study”. Journal of Physics: Conference Series, 450, 012026, 2013.
  • Vizcaya P, Perpiñan G, McEneaney D, Escalona OJ (2019). Standard ECG Lead I Prospective Estimation Study from Far-field Bipolar Leads on the Left Upper Arm: A Neural Network Approach. Journal of Biomedical Signal Processing and Control; 51: 171-180, DOI: https://doi.org/10.1016/j.bspc.2019.01.020.
  • Lynn WD, Escalona O, McEneaney DJ,(2014). A Low Latency Electrocardiographic QRS Activity Recovery Technique for Use on the Upper Left Arm. Electronics (Switzerland), 3: 409-418.
  • O. Escalona, W. Lynn, G. Perpiñan, L. McFrederick, et al.(2017), “Data-Driven ECG Denoising Techniques for Characterising Bipolar Lead Sets along the Left Arm in Wearable Long-Term Heart Rhythm Monitoring,” Electronics, vol. 6, no. 4, p. 84, 2017
  • Escalona, OJ, McFrederick, L, Borges, M, Linares, P, et al.(2017). Wrist and Arm Body Surface Bipolar ECG Leads Signal and Sensor Study for Long-term Rhythm Monitoring.44th Computing in Cardiology Conference 2017, Vol 44.
  • Villegas, Angel, McEneaney, David, Escalona, Omar. (2019). Arm-ECG Wireless Sensor System for Wearable Long-Term Surveillance of Heart Arrhythmias. Electronics 8, No.11: 1300. DOI: 10.3390/electronics8111300.
  • Escalona, O.J.; Villegas, A.; Mukhtar, S.; et al.(2020). Wireless Arm Wearable Sensor Band for Long-Term Heart Rhythms Surveillance Using a Bipolar Arm-ECG Lead. In Proceedings of Computing in Cardiology, 2020; Volume 47, published in IEEE Xplore, doi: 10.22489/CinC.2020.470
  • McCallan N, Biglarbeigi P, Finlay D, Perpiñan G, McLaughlin J, Escalona OJ (2019). Wearable Technology: Signal Recovery of ECG from Short Spaced Leads in the Far-field Using Discrete Wavelet Transform Based Techniques. Computing in Cardiology (4-page paper), Conference Proceedings, Vol. 46, published in IEEE Xplore, doi: 10.22489/CinC.2019.313
  • Escalona, O.J., Magwood, S., McCallan, N., Hilton, A. (2022). Feasibility of Wearable Armband Bipolar ECG Lead-1 for Long-term HRV Monitoring Using a Combined Signal Averaging and 2-stage Wavelet Denoising Technique. In Proceedings of Computing in Cardiology, vol. 49, doi: 10.22489/CinC.2022.409
  • Escalona, O.; Mukhtar, S.; McEneaney, D.; Finlay, D. (2022). Armband Sensors Location Assessment for Left Arm-ECG Bipolar Leads Waveform Components Discovery Tendencies Around the MUAC Line. Sensors 2022, 22, 7240, https://doi.org/10.3390/s22197240
  • Escalona, O., Cullen, N., Weli, I., McCallan, N., Ng, K.Y., Finlay, D. (2023). Robust Arm Impedocardiography Signal Quality Enhancement Using Recursive Signal Averaging and Multi-Stage Wavelet Denoising Methods for Long-Term Cardiac Contractility Monitoring Armbands Sensors 2023, 23, 5892. https://doi.org/10.3390/s23135892
  • Cullen, N,  Escalona, O, Fahima, R, Weli, I (2023). In Proceedings of Computing in Cardiology 2023, in press, Open Access,      https://cinc.org/2023/Program/accepted/444_CinCFinalPDF.pdf

The Doctoral College at Ulster University

Key dates

Submission deadline
Monday 24 February 2025
04:00PM

Interview Date
Mach 2025

Preferred student start date
15th September 2025

Applying

Apply Online  

Contact supervisor

Professor Omar Escalona

Other supervisors