A digital nervous system aiming toward personalized IoT healthcare
Astrid Armgarth, Sandra Pantzare, Patrik Arvén, Roman Lassnig, Hiroaki Jinno, Erik O. Gabrielsson, Yonatan Kifle, Dennis Cherian, Theresia Arbring Sjöström, Gautier Berthou, Jim Dowling, Takao Someya, J. Jacob Wikner, G. Gustafsson, Daniel T. Simon, Magnus Berggren
Abstract
Body area networks (BANs), cloud computing, and machine learning are platforms that can potentially enable advanced healthcare outside the hospital. By applying distributed sensors and drug delivery devices on/in our body and connecting to such communication and decision-making technology, a system for remote diagnostics and therapy is achieved with additional autoregulation capabilities. Challenges with such autarchic on-body healthcare schemes relate to integrity and safety, and interfacing and transduction of electronic signals into biochemical signals, and vice versa. Here, we report a BAN, comprising flexible on-body organic bioelectronic sensors and actuators utilizing two parallel pathways for communication and decision-making. Data, recorded from strain sensors detecting body motion, are both securely transferred to the cloud for machine learning and improved decision-making, and sent through the body using a secure body-coupled communication protocol to auto-actuate delivery of neurotransmitters, all within seconds. We conclude that both highly stable and accurate sensing-from multiple sensors-are needed to enable robust decision making and limit the frequency of retraining. The holistic platform resembles the self-regulatory properties of the nervous system, i.e., the ability to sense, communicate, decide, and react accordingly, thus operating as a digital nervous system.