Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach

Delaram Yazdansepas; Nitin Saroha; Lakshmish Ramaswamy; Khaled Rasheed

doi:10.1007/978-3-030-29897-5_10

Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach

Delaram Yazdansepas, Nitin Saroha, Lakshmish Ramaswamy, Khaled Rasheed

University of Georgia School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	13th EAI International Conference on Body Area Networks, 2018
Editors	Chika Sugimoto, Hamed Farhadi, Matti Hämäläinen
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	115-130
Number of pages	16
ISBN (Print)	9783030298968
DOIs	https://doi.org/10.1007/978-3-030-29897-5_10
State	Published - 2020
Externally published	Yes
Event	13th EAI International Conference on Body Area Networks, BODYNETS 2018 - Oulu, Finland Duration: Oct 2 2018 → Oct 3 2018

Publication series

Name	EAI/Springer Innovations in Communication and Computing
Volume	3
ISSN (Print)	2522-8595
ISSN (Electronic)	2522-8609

Conference

Conference	13th EAI International Conference on Body Area Networks, BODYNETS 2018
Country/Territory	Finland
City	Oulu
Period	10/2/18 → 10/3/18

ASJC Scopus Subject Areas

Information Systems
Health Informatics
Computer Networks and Communications
Electrical and Electronic Engineering

Access to Document

10.1007/978-3-030-29897-5_10

Cite this

Yazdansepas, D., Saroha, N., Ramaswamy, L., & Rasheed, K. (2020). Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach. In C. Sugimoto, H. Farhadi, & M. Hämäläinen (Eds.), 13th EAI International Conference on Body Area Networks, 2018 (pp. 115-130). (EAI/Springer Innovations in Communication and Computing; Vol. 3). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-29897-5_10

Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach. / Yazdansepas, Delaram; Saroha, Nitin; Ramaswamy, Lakshmish et al.
13th EAI International Conference on Body Area Networks, 2018. ed. / Chika Sugimoto; Hamed Farhadi; Matti Hämäläinen. Springer Science and Business Media Deutschland GmbH, 2020. p. 115-130 (EAI/Springer Innovations in Communication and Computing; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yazdansepas, D, Saroha, N, Ramaswamy, L & Rasheed, K 2020, Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach. in C Sugimoto, H Farhadi & M Hämäläinen (eds), 13th EAI International Conference on Body Area Networks, 2018. EAI/Springer Innovations in Communication and Computing, vol. 3, Springer Science and Business Media Deutschland GmbH, pp. 115-130, 13th EAI International Conference on Body Area Networks, BODYNETS 2018, Oulu, Finland, 10/2/18. https://doi.org/10.1007/978-3-030-29897-5_10

Yazdansepas D, Saroha N, Ramaswamy L, Rasheed K. Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach. In Sugimoto C, Farhadi H, Hämäläinen M, editors, 13th EAI International Conference on Body Area Networks, 2018. Springer Science and Business Media Deutschland GmbH. 2020. p. 115-130. (EAI/Springer Innovations in Communication and Computing). doi: 10.1007/978-3-030-29897-5_10

Yazdansepas, Delaram ; Saroha, Nitin ; Ramaswamy, Lakshmish et al. / Towards efficient and real-time human activity recognition using wearable sensors : A shapelet-based pattern matching approach. 13th EAI International Conference on Body Area Networks, 2018. editor / Chika Sugimoto ; Hamed Farhadi ; Matti Hämäläinen. Springer Science and Business Media Deutschland GmbH, 2020. pp. 115-130 (EAI/Springer Innovations in Communication and Computing).

@inproceedings{09fb448cb8a144c58c0e17e963f54164,

title = "Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach",

author = "Delaram Yazdansepas and Nitin Saroha and Lakshmish Ramaswamy and Khaled Rasheed",

year = "2020",

doi = "10.1007/978-3-030-29897-5_10",

language = "English",

isbn = "9783030298968",

series = "EAI/Springer Innovations in Communication and Computing",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "115--130",

editor = "Chika Sugimoto and Hamed Farhadi and Matti H{\"a}m{\"a}l{\"a}inen",

booktitle = "13th EAI International Conference on Body Area Networks, 2018",

note = "13th EAI International Conference on Body Area Networks, BODYNETS 2018 ; Conference date: 02-10-2018 Through 03-10-2018",

}

TY - GEN

T1 - Towards efficient and real-time human activity recognition using wearable sensors

T2 - 13th EAI International Conference on Body Area Networks, BODYNETS 2018

AU - Yazdansepas, Delaram

AU - Saroha, Nitin

AU - Ramaswamy, Lakshmish

AU - Rasheed, Khaled

PY - 2020

Y1 - 2020

UR - http://www.scopus.com/inward/record.url?scp=85096436472&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85096436472&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-29897-5_10

DO - 10.1007/978-3-030-29897-5_10

M3 - Conference contribution

AN - SCOPUS:85096436472

SN - 9783030298968

T3 - EAI/Springer Innovations in Communication and Computing

SP - 115

EP - 130

BT - 13th EAI International Conference on Body Area Networks, 2018

A2 - Sugimoto, Chika

A2 - Farhadi, Hamed

A2 - Hämäläinen, Matti

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 2 October 2018 through 3 October 2018

ER -

Towards efficient and real-time human activity recognition using wearable sensors: A shapelet-based pattern matching approach

Publication series

Conference

ASJC Scopus Subject Areas

Access to Document

Other files and links

Cite this