Real-time integration of bio-signals for personalized synchronized vagus nerve stimulation

Abstract

The use of electrical stimulation of the vagus nerve as a treatment for neurological or mental disorders has gained significant attention in recent years. One of the newest and most convenient methods of stimulating the vagus nerve is through auricular vagus nerve stimulation. This method involves modulating the afferent vagus nerve and thus impact a wide range of physiological processes. In order to maximize the efficiency of the stimulation, it is crucial to monitor the physiological processes during stimulation and adjust the stimulation accordingly. Such monitorization can be achieved by using a closed-loop stimulation with biofeedback.This thesis examines the effectiveness of using the MAX30001 sensor in a closed-loop biofeedback auricular vagus nerve stimulation device. The sensor is ideal for this application due to its ability to measure both electrocardiogram and bioimpedance data simultaneously, easy integration into wearable devices, and integrated signal filtering and communication via the SPI protocol. The sensor was utilized with MATLAB for data recording, analysis, and real-time visualization. A platform for adaptive auricular vagus nerve stimulation was previously developed in Simulink, which was modified and used to test and validate the use of the MAX30001 sensor in a closed-loop auricular vagus nerve stimulation.The MAX30001 sensor was found to be compatible with the STM LQFP64 microcontroller for the purpose of closed-loop auricular vagus nerve stimulation. The microcontroller is capable of configuring data acquisition, timestamping the data, and saving the data to local memory or transmitting it to another device. Additionally, it is able to manage data processing and activation of the stimulator. Communication between the two devices was achieved through the use of the SPI protocol at speeds up to 12 MHz, allowing for data to be acquired, processed, and transmitted in approximately 24 ms.The developed system was integrated with the aforementioned simulation platform. After calibration, a simulation of the closed loop auricular vagus nerve stimulation was done. In this simulation the microcontroller was able not only to acquire, process and send the data to the simulation, but also receive a command from the simulated stimulator.Although there is still some work to be done to use this sensor at its full potential, the initial results are promising. Using the bioimpedance module from the sensor could drastically increase the accuracy of the stimulation and bring another layer of personalization. Also, integrating both the sensor and the stimulator in a single stand-alone device would make the closed loop personalized vagus nerve stimulator easier for patients to use.