Neuromorphic Detection of Abnormal Respiratory Patterns Using Smart Textile Sensors
Respiratory diseases like asthma, COPD, sleep apnoea, and other conditions such as cancer, Parkinson’s, and sepsis reveal themselves through distinct respiratory patterns, including shallow breathing, tachypnoea, bradypnea, and gasping. These biomarkers present a unique opportunity for early detection and monitoring, vital for improving patient outcomes.
This innovative project leverages cutting-edge smart textile sensors based on knitted coils to monitor thoracic movements at the chest and abdomen. These sensors not only offer superior sensitivity compared to commercial belts but also provide exceptional comfort, making them ideal for continuous wear.
To accurately measure breathing patterns, we typically require healthy volunteers or patients. However, we have developed a thorax phantom capable of replicating any desired breathing pattern, eliminating the need for human subjects in the initial testing phase.
This project aims in the development of algorithms capable of detecting abnormal breathing patterns. These algorithms will be implemented in ultra-low power electronics, tailored for wearable devices, and tested using signals from our advanced sensor and programmable thorax phantom.
Project Tasks: Design and test a shallow neural network using a neuromorphic approach to detect abnormal breathing patterns. This involves:
-
- Breathing Pattern Analysis and Feature Extraction: Dive deep into respiratory signal processing to identify key features indicative of various respiratory conditions.
-
- SNN Design, Implementation, and Optimization: Develop, implement, and optimize spiking neural networks (SNNs) tailored for respiratory motion signals.
Learning Outcomes: Participants in this project will gain invaluable skills in breathing pattern analysis, feature extraction, and the design and optimization of neuromorphic algorithms. This project offers the potential for groundbreaking work suitable for publication in scientific journals, providing a significant boost to your academic and professional profile.
Prerequisites:
This project is a collaboration between ETH Zurich and the University of Cyprus, promising an enriching experience and a chance to contribute to solutions for real-world problems in respiratory health.
For further details, please contact:
Join us in pioneering the future of respiratory monitoring and making a tangible impact on healthcare technology.