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Wearable-sensor activity analysis using semi-Markov models with a grammar

Date

Authors

Thomas, Owen

Sunehag, Peter

Dror, Gideon

Yun, Sungrack

Kim, S

Robards, Matthew

Smola, Alexander

Green, Daniel

Saunders, Philo U

Publisher

Elsevier

Abstract

Detailed monitoring of training sessions of elite athletes is an important component of their training. In this paper we describe an application that performs a precise segmentation and labeling of swimming sessions. This allows a comprehensive breakdown

Keywords

Keywords: Activity analysis; Activity recognition; Discriminative hidden Markov models; Elite athlete; Human performance; Machine-learning; Margin setting; Semi Markov model; Sequential data; Training sessions; Wearable sensors; Accelerometers; Computational comple Accelerometer; Activity recognition; Human performance; Machine learning; Semi-Markov models

URI

http://hdl.handle.net/1885/58689

Collections

ANU Research Publications

Source

Pervasive and Mobile Computing

Type

Journal article

DOI

10.1016/j.pmcj.2010.01.002

Restricted until

2037-12-31

Downloads

File

Description

01_Thomas_Wearable-sensor_activity_2010.pdf (196.73 KB)

02_Thomas_Wearable-sensor_activity_2010.pdf (100.82 KB)

03_Thomas_Wearable-sensor_activity_2010.pdf (535.04 KB)

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