Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables

Beitrag in einer Fachzeitschrift
(Originalarbeit)


Details zur Publikation

Autor(en): Martindale C, Sprager S, Eskofier B
Zeitschrift: Sensors
Jahr der Veröffentlichung: 2019
Band: 198
ISSN: 1424-8220
Sprache: Englisch


Abstract

Activity monitoring using wearables is becoming ubiquitous, although accurate cycle level  analysis, such as step-counting and gait analysis, are limited by a lack of realistic and labeled datasets. The effort required to obtain and annotate such datasets is massive, therefore we  propose a smart annotation pipeline which reduces the number of events needing manual adjustment to 14%. For scenarios dominated by walking, this annotation effort is as low as 8%. The pipeline consists of three smart annotation approaches, namely edge detection of the pressure data, local cyclicity estimation, and iteratively trained hierarchical hidden Markov models. Using this pipeline, we have collected and labeled a dataset with over 150,000 labeled cycles, each with 2 phases, from 80 subjects, which we have made publicly available. The dataset consists of 12 different task-driven activities, 10 of which are cyclic. These activities include not only straight and steady-state motions, but also transitions, different ranges of bouts, and changing directions. Each participant wore 5 synchronized inertial measurement units (IMUs) on the wrists, shoes, and in a pocket, as well as pressure insoles and video. We believe that this dataset and smart annotation pipeline are a good basis for creating a benchmark dataset for validation of other semi- and unsupervised algorithms.


FAU-Autoren / FAU-Herausgeber

Eskofier, Björn Prof. Dr.
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Martindale, Christine
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Sprager, Sebastijan Dr.
Lehrstuhl für Informatik 5 (Mustererkennung)


Zitierweisen

APA:
Martindale, C., Sprager, S., & Eskofier, B. (2019). Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables. Sensors, 198. https://dx.doi.org/10.3390/s19081820

MLA:
Martindale, Christine, Sebastijan Sprager, and Björn Eskofier. "Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables." Sensors 198 (2019).

BibTeX: 

Zuletzt aktualisiert 2019-17-04 um 12:53