BAYesian Inference with FLEXible electronics for biomedical Applications

Introduction

The long term vision in BAYFLEX is to create a radically new technology that uses low cost, green organic electronics for probabilistic computing in order to allow continuous and private monitoring of bio-signals on flexible substrates.

Vision

The vision of flexible green AI sensors with on-chip classification extends well beyond biomedical devices and the democratization of health care, with the possibility to transform sensor data at the edge of large networks.

Objectives

To achieve our goal, BAYFLEX will demonstrate a patch using active physiological sensors based on organic materials that interface with the soft human body. This patch will also include classification circuits (~ 100 transistors) fabricated using Thin Organic Large Area Electronics (TOLAE) processes.

Technical Approach

These circuits use spiking neurons realized in Organic Thin Film Transistors (OTFTs) to transform the non-stationary electrical signals from the sensors into stochastic bit streams. Bayesian inference is then used to classify the data using circuits of cascaded Muller C-elements.

Innovations

Taking advantage of the unique properties of organic electrochemical transistors (OECTs), low transistor count dynamic Muller C-elements are targeted. The patch will be tested on a simple task using healthy humans.

Consortium

The project brings together an interdisciplinary consortium with expertise in:

• Modeling emerging devices
• Biologically inspired circuit design
• Machine learning involving electrophysiological data (including an SME)
• OTFT and OECT fabrication

Dissemination

BAYFLEX targets dissemination to a variety of publics including:

1. Scientists via publications in (open access) high impact journals and conferences
2. Industrials and end-users through an industrial advisory board, a workshop, and demonstrations at targeted conferences
3. The general public with the creation of a transferable workshop for non-scientific communities
4. Training the next generation of experts through specialized schools and workshops