UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

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

Ahrabian, A; Elsaleh, T; Fathy, Y; Barnaghi, P; (2017) Detecting Changes in the Variance of Multi-Sensory Accelerometer Data Using MCMC. In: 2017 IEEE SENSORS. (pp. pp. 1152-1154). IEEE Green open access

[img]
Preview
Text
Detecting Changes in the Variance of Multi-Sensory Accelerometer Data Using MCMC.pdf - Accepted version

Download (369kB) | Preview

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).

Type: Proceedings paper
Title: Detecting Changes in the Variance of Multi-Sensory Accelerometer Data Using MCMC
Event: 16th IEEE SENSORS Conference, 29 October - 1 November 2017, Glasgow, UK
Location: Glasgow, SCOTLAND
Dates: 29 October 2017 - 01 November 2017
ISBN-13: 9781509010127
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ICSENS.2017.8234260
Publisher version: https://doi.org/10.1109/ICSENS.2017.8234260
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Variance Change Detection, Multivariate Change Detection, Sensors, Analytical models, Accelerometers, Data models, Detection algorithms, Indexes, Bayes methods
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10058859
Downloads since deposit
49Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item