Adaptive Cardiac Re-synchronization

CResPace is a H2020 consortium of 8 academic and industrial partners which develops adaptive bioelectronics.  One application area of the methodology we are developing is adaptive cardiac resynchronization.  The technology relies on small neural networks known as central pattern generators that respond to physiological feedback in real time to provide realistic pacing.  CResPace is working to extend patient’s life and quality of life.


The technology mimics the function of medullary neural circuits located at the base of the brain which regulate cardiac function by responding to changes in physiological feedback. These circuits, known as Central Pattern Generators (CPGs), are small neural networks which control respiration and heart rate, the coordination between muscles responsible for swallowing.  We implement these central  pattern generators using physical hardware to replicate natural control of heart rate and re-synchronize heart chambers.


VLSI pacemaker
To build models, we first learn from biological networks by measuring their behaviour under a range of conditions using data assimilation and then transfer this information into hardware networks.  The networks are then used to produce bioelectronic implants.
An example of network modelling is shown below where biological oscillations (black line) acquired over the first period (green line) are used to predict the responses of the membrane voltage (red line).



University of BathPhysics
Prof Alain Nogaret,

University of Bristol, Physiology
Prof Julian Paton

University of Zurich, Neuromorphic Engineering
Prof Giacomo Indiveri

Mr Tracy Wotherspoon

Dr Berthold Steggemann

University of Vienna, Cardiology
Prof Mariann Gyongyosi

University of Utrecht, Physiology
Prof Marc Vos

International Clinical Research Centre, Brno
Dr Viola Galligioni

Blog at

Up ↑