Project-gestures

This project presents an in-air writing gesture recognition system using a wrist-worn device.

In this project, we present a novel gesture input technique for off-the-shelf smartwatches.

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 present the design of SpiderWalk on smartphones to detect transportation activity.

In this project, we propose an approach to interpret EEG signals for multi-person and multi-class brain activity recognition.

This project presents a system to detect human respiration using Wi-Fi devices.

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.

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.

This paper aims to improve the energy efficiency of LoRa by enabling LoRa nodes to operate in a downclocked 'light sleep' mode for packet reception.

This project aims to investigate the fundamental problem of recognizing activities of multiple users using wearable sensors in a home environment.