An Educational and Research Kit for Activity and Context Recognition from On-body Sensors

Daniel Roggen,Marc Bächlin,Johannes Schumm,Thomas Holleczek,Clemens Lombriser,Gerhard Tröster,Lars Widmer,Dennis Majoe,Jürg Gutknecht

Body Sensor Networks（2010）

引用 25|浏览0

暂无评分

摘要

We present an educational and research kit to support hands-on teaching and experience of real-time activity or gesture recognition from on-body sensors. The kit is comprised of: wireless wearable sensor nodes for motion and ECG sensing; software infrastructure for synchronized data acquisition from multiple sensors, data visualization, signal alignment, and synchronized signal/video exploration; algorithm demonstration and education software with a hidden Markov model-based activity recognition system and a low-latency gesture recognition for a platform game; support hardware for the annotation of user activities from a wireless keypad, and for prototyping of other wireless sensor nodes. All hardware and software is open-source.

查看译文

关键词

wireless wearable sensor node,data acquisition,data visualization,low-latency gesture recognition,wireless sensor node,on-body sensors,gesture recognition,recognition system,research kit,software infrastructure,education software,context recognition,wireless keypad,hardware,wearable computer,wireless sensor networks,hidden markov models,real time,engineering education,activity recognition,biomechanics,biomedical engineering,wireless communication,machine learning,hidden markov model,wearable computing,programming,educational software,sensors,low latency,acceleration

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要