.png){kind=icon}
返回
User-Centric Coordinates for Applications Leveraging 3-Axis Accelerometer Data
.png){kind=icon}
PRE
AI
DOI：10.1109/JSEN.2017.2723840.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Mobile devices are becoming ubiquitous and, sometimes, even extensions of ourselves. These devices are growing fast in terms of delivered computational power, storage capacity, battery duration, and built-in sensors. Time and again, we see headlines advertising new unforeseen applications leveraging this power, especially the sensors, for solving diverse problems, including fall detection, user's activity recognition, location identification, or even user authentication based on the way of walking (gait). In this paper, we focus on motion sensors and discuss how the provided data can be interpreted and transformed to better serve different purposes. We propose a method to process the data from such sensors that reduces the acquisition noise and possible artifacts, and turns the data invariant to the device's position and the user's movement direction. We introduce a new coordinate system referred to as user-centric, as opposed to the two most common coordinate systems used-the device and world-coordinate systems. For testing, we design and develop a user recognition system based on gait, in which the three coordinates systems are compared and discussed considering a one-versus-rest authentication setup. The results show the importance of properly pre-processing the acquired data to enable more reliable applications underpinned by mobile sensors.
Keyword:
Accelerometers
mobile applications
gait recognition
data preprocessing
digital filters
signal analysis
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.5
论文数:
2.1W
被引数:
7.3W
机构
引用论文
The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication.png)
PATTERN RECOGNITION
OAAI
PATTERN RECOGNITIONIF7.6
OAAI分享收藏分享收藏
查看更多内容