Bioelectronics | EPFL Graph Search

Bioelectronics is a field of research in the convergence of biology and electronics. Definitions At the first C.E.C. Workshop, in Brussels in November 1991, bioelectronics was defined as 'the use of biological materials and biological architectures for information processing systems and new devices'. Bioelectronics, specifically bio-molecular electronics, were described as 'the research and development of bio-inspired (i.e. self-assembly) inorganic and organic materials and of bio-inspired (i.e. massive parallelism) hardware architectures for the implementation of new information processing systems, sensors and actuators, and for molecular manufacturing down to the atomic scale'. The National Institute of Standards and Technology (NIST), an agency of the United States Department of Commerce, defined bioelectronics in a 2009 report as "the discipline resulting from the convergence of biology and electronics". Sources for information about the field include the Institute of E

A lightweight learning-based decoding algorithm for intraneural vagus nerve activity classification in pigs

Silvestro Micera, Leonardo Pollina, Ivo Strauss

Objective. Bioelectronic medicine is an emerging field that aims at developing closed-loop neuromodulation protocols for the autonomic nervous system (ANS) to treat a wide range of disorders. When designing a closed-loop protocol for real time modulation of the ANS, the computational execution time and the memory and power demands of the decoding step are important factors to consider. In the context of cardiovascular and respiratory diseases, these requirements may partially explain why closed-loop clinical neuromodulation protocols that adapt stimulation parameters on patient's clinical characteristics are currently missing. Approach. Here, we developed a lightweight learning-based decoder for the classification of cardiovascular and respiratory functional challenges from neural signals acquired through intraneural electrodes implanted in the cervical vagus nerve (VN) of five anaesthetized pigs. Our algorithm is based on signal temporal windowing, nine handcrafted features, and random forest (RF) model for classification. Temporal windowing ranging from 50 ms to 1 s, compatible in duration with cardio-respiratory dynamics, was applied to the data in order to mimic a pseudo real-time scenario. Main results. We were able to achieve high balanced accuracy (BA) values over the whole range of temporal windowing duration. We identified 500 ms as the optimal temporal windowing duration for both BA values and computational execution time processing, achieving more than 86% for BA and a computational execution time of only similar to 6.8 ms. Our algorithm outperformed in terms of BA and computational execution time a state of the art decoding algorithm tested on the same dataset (Vallone et al 2021 J. Neural Eng. 18 0460a2). We found that RF outperformed other machine learning models such as support vector machines, K-nearest neighbors, and multi-layer perceptrons. Significance. Our approach could represent an important step towards the implementation of a closed-loop neuromodulation protocol relying on a single intraneural interface able to perform real-time decoding tasks and selective modulation of the VN.

IOP Publishing Ltd2022

Development of a Transient Neural Interface for Minimally Invasive Recording and Stimulation

Adele Fanelli

Transient electronics enabling devices to safely disappear in the environment can be applied not only in green electronics, but also in bioelectronic medicine. Neural implants able to degrade harmlessly inside the body eliminate the need for removal surgery, allow for safe tissue remodelling, and potentially reduce inflammation responses and the chronic adverse reactions hindering device functionality and putting patients' health at risk. Sadly, current transient neurotechnology can be used only for very short-term applications. Fast degrading metals generally used to build these interfaces allow in fact for operations rarely longer than a few days, strongly limiting the available time window for collecting information or for a therapy to be finished.To solve this problem, we propose a transient, all-polymeric neural interface able to work for longer time scales. This would enable new applications of transient neurotechnology, such as recording of brain activity for a prolonged and more useful period of time before resection of epilepsy foci or tumours. The device consists of a polycaprolactone (PCL) scaffold with patterned poly 3,4-ethylene dioxythiophene : polystyrene sulfonate (PEDOT:PSS) traces and electrodes. In vivo neural recording demonstrated low noise levels for twelve weeks and histological analysis highlighted the cellular infiltration inside the PCL scaffold over time, hinting to potential tissue remodelling processes, which would not occur with a non-degradable device. To increase the device potential for a clinical translation, a minimally invasive procedure for its implantation has been proposed. The blood vasculature supplying the brain and nerves can be used as an access route to the neural tissue, offering a close enough location without direct damage to the tissue. By re-shaping the all-polymeric transient neural probe using a stent-inspired design, the new interface can be navigated through a 5Fr catheter and deployed inside 2 mm-diameter channels. Characterization showed promising electrodes endurance to pulsatile flow and prolonged stimulation, together with a good safety profile. This device can be used for neural recording or stimulation from within a blood vessel, for either central or peripheral nervous system. By simplifying the implantation procedure of the neural interface and maintaining its transiency, physicians and patients could feel more confident in applying innovative neurotechnology-based treatments, widening for example the access to deep brain stimulation therapy. To enable crossing of complex vasculature without wall ruptures caused by current manual push of guidewires, a new navigation paradigm for endovascular devices has been designed and tested on thin polyimide strips. A physiological pulsatile flow can propel these probes, even at curvatures as high as 0.25 mm-1, and low amplitude magnetic fields can steer their direction. Electrodes and sensors for temperature and flow can be embedded onto these micro-probes, for unprecedented local interrogation of deep vasculature regions. In conclusion, this thesis introduces new neural interfaces in the field of minimally invasive neurotechnology, reducing adverse effects and complications of non-degradable implants and open surgery. These devices and their concepts have the potential one day to be new tools of the bioelectronic medicine toolbox, contributing to the advancement of innovative treatments for neurodegenerative disorders.

EPFL2022

A lightweight learning-based decoding algorithm for intraneural vagus nerve activity classification in pigs

Silvestro Micera, Leonardo Pollina, Ivo Strauss

IOP Publishing Ltd2022

Development of a Transient Neural Interface for Minimally Invasive Recording and Stimulation

Adele Fanelli

EPFL2022