A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution

A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution

Mobile activity recognition is significant to the development of human-centric pervasive applications including elderly care, personalized recommendations, etc. Nevertheless, the distribution of inertial sensor data can be influenced to a great extent by varying users. This means that the performanc...

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Bibliographic Details
Main Authors: Shizhen Zhao, Wenfeng Li, Jingjing Cao
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Sensors
Subjects:
human activity recognition
user-adaptive algorithm
K-Means clustering
local outlier factor
multivariate Gaussian distribution
personalized classifier
Online Access:http://www.mdpi.com/1424-8220/18/6/1850

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