This project presents the design of an audio-based highly-accurate system for human respiration monitoring, leveraging on commodity speaker and microphone widely available in home environments.
In this project, we propose an approach to interpret EEG signals for multi-person and multi-class brain activity recognition.
In this work, we propose a system using low-cost RFID tags, which enables device-free, unobtrusive monitoring of elderly people by leveraging machine learning algorithms and the Internet of Things (IoT) technology.