Development of an intelligent ambulatory ECG recording and analysis system.
Project ID: PSM15
Supervisor: Dr. Hugh Matthews
Second Supervisor: Prof. Christopher Huang
Second Supervisor DepartmentPDN
Cardiac arrhythmia is a major cause of death in the developed world. However, electrocardiographic investigations are frequently carried out in a clinic-based setting, precluding long-term studies under normal conditions. Ambulatory ECG recording devices are typically costly, bulky, and often offer only limited information about cardiac performance through a single limb lead with little local analysis. There is thus an unfulfilled need for an inexpensive ambulatory ECG device with capability for not only local recording and storage, but also on-the-fly analysis of arrhythmias and pre-arrhythmic conditions.
The starting point for this project is the former open-source project “Biosignal Pi”, initiated at the Royal Institute of Technology in Stockholm, Sweden (Abtahi et al., 2014). Unfortunately, despite some subsequent software development, the project seems to have terminated in early 2016 following the implementation of data acquisition and control, but without further progress towards local ECG processing. The aim of this project is to implement an improved version of this system using evaluation boards for the Analog Devices ADAS1000 bioprocessor on more powerful Raspberry Pi Model C hardware. This system will initially be characterised using an ECG patient simulator, using the existing Biosignal Pi data acquisition framework as a starting point. In parallel, a scaleable chest lead-frame will be designed for multilead precordial recordings using 3D printing technology. In addition, once a working system has been obtained, strategies for “on-the-fly” ECG analysis and vectorcardiography will be developed. The ultimate goal is to miniaturise the entire system for fully ambulatory but wirelessly-connected use by means of the recently-introduced thumb-sized Pi-zero W microcomputer.
Our application will provide a technological platform for the development of noninvasive ambulant ECG monitoring applicable in a community as opposed to a hospital setting. It will be particularly useful in applications requiring acquisition of lengthy records and their computational diagnostic analysis, opening up completely new avenues for cardiological monitoring.
Abtahi F, Snäll J, Aslamy B, Abtahi S, Seoane F & Lindecrantz K (2014). Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System. Sensors 15, 93–109.
This project fits in the core remit of Cambridge Cardiovascular. There is thus clear potential to link this work to translational and clinical research groups in the University. The medical partner in the proposal is part of Cambridge Cardiovascular, a multi-disciplinary consortium of cardiovascular researchers and clinicians based at the University of Cambridge, including the BHF Cambridge Centre for Cardiovascular Research Excellence and the BHF Oxbridge Centre of Regenerative Medicine. Cambridge. This provides a framework integrating world-class cardiovascular basic biological, physical, and biomedical research, and connecting this with clinical, epidemiological and health services studies.