An on-node processing approach for anomaly detection in gait
File(s)article.pdf (644.66 KB)
Accepted version
Author(s)
Cola, G
Avvenuti, M
Vecchio, A
Yang, G-Z
Lo, B
Type
Journal Article
Date Issued
2015-08-05
Date Acceptance
2015-07-20
Citation
IEEE Sensors Journal, 2015, 15 (11), pp.6640-6649
ISSN
1558-1748
Publisher
IEEE
Start Page
6640
End Page
6649
Journal / Book Title
IEEE Sensors Journal
Volume
15
Issue
11
Copyright Statement
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/H009744/1
EP/K503733/1
EP/L014149/1
Subjects
Science & Technology
Technology
Physical Sciences
Engineering, Electrical & Electronic
Instruments & Instrumentation
Physics, Applied
Engineering
Physics
Activity monitoring
anomaly detection
fall risk assessment
gait analysis
wearable sensors
FALL RISK-ASSESSMENT
OLDER-ADULTS
COGNITIVE IMPAIRMENT
HUMAN MOVEMENT
SENSORS
SYSTEM
ACCELEROMETER
PARAMETERS
RECOGNITION
GYROSCOPES
Analytical Chemistry
0906 Electrical And Electronic Engineering
0913 Mechanical Engineering
Publication Status
Published