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Detecting Changes in the Variance of Multi-Sensory Accelerometer Data Using MCMC

Ahrabian, Alireza, Elsaleh, Tarek, Fathy, Yasmin and Barnaghi, Payam (2017) Detecting Changes in the Variance of Multi-Sensory Accelerometer Data Using MCMC In: IEEE Sensors 2017, 29 Oct - 01 Nov 2017, Glasgow, Scotland.

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Abstract

An important field in exploratory sensory data analysis is the segmentation of time-series data to identify activities of interest. In this work, we analyse the performance of univariate and multi-sensor Bayesian change detection algorithms in segmenting accelerometer data. In particular, we provide theoretical analysis and also performance evaluation on synthetic data and real-world data. The results illustrate the advantages of using multi-sensory variance change detection in the segmentation of dynamic data (e.g. accelerometer data).

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Ahrabian, Alirezaa.ahrabian@surrey.ac.ukUNSPECIFIED
Elsaleh, TarekT.Elsaleh@surrey.ac.ukUNSPECIFIED
Fathy, YasminUNSPECIFIEDUNSPECIFIED
Barnaghi, PayamP.Barnaghi@surrey.ac.ukUNSPECIFIED
Date : 1 November 2017
Copyright Disclaimer : © 2017 IEEE.
Uncontrolled Keywords : Variance Change Detection; Multivariate Change Detection
Related URLs :
Depositing User : Clive Harris
Date Deposited : 30 Aug 2017 10:14
Last Modified : 01 Nov 2017 02:08
URI: http://epubs.surrey.ac.uk/id/eprint/842080

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