Ultrasonic circular array sensing for human arm motion classification

R. Van Sloun; A. Pandharipande; D. Caicedo; S. Srinivasan; P. Sommen

doi:10.1109/ICCE-Berlin.2014.7034298

Ultrasonic circular array sensing for human arm motion classification

R. Van Sloun, A. Pandharipande, D. Caicedo, S. Srinivasan, P. Sommen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Downloads (Pure)

Abstract

Classification of human arm movements is an important problem in healthcare and well-being applications. In this paper, an ultrasonic Uniform Circular Array (UCA) Doppler sensing method is proposed for classifying arm movements from a given set. The method uses velocity and angular information, derived from Doppler frequencies and direction-of-arrival (DoA) by processing the signals received at the UCA, and employs a Bayesian classifier to distinguish between movements. The performance of the sensing method is evaluated using experimental datasets. The proposed ultrasonic UCA Doppler sensor and processing methods provide a compact solution for human arm movement classification.

Original language	English
Title of host publication	Consumer Electronics – Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference, Berlin, 7-10 September 2014
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	24-25
Number of pages	2
ISBN (Electronic)	978-1-4799-6165-8
DOIs	https://doi.org/10.1109/ICCE-Berlin.2014.7034298
Publication status	Published - 5 Feb 2015
Event	4th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2014 - Berlin, Germany, Berlin, Germany Duration: 7 Sept 2014 → 10 Sept 2014 Conference number: 4 http://www.icce-berlin.org/2014/

Conference

Conference	4th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2014
Abbreviated title	ICCE-Berlin 2014
Country/Territory	Germany
City	Berlin
Period	7/09/14 → 10/09/14
Internet address	http://www.icce-berlin.org/2014/

Keywords

Human arm movement classification
UCA Doppler sensor

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICCE-Berlin.2014.7034298

Cite this

Van Sloun, R., Pandharipande, A., Caicedo, D., Srinivasan, S., & Sommen, P. (2015). Ultrasonic circular array sensing for human arm motion classification. In Consumer Electronics – Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference, Berlin, 7-10 September 2014 (pp. 24-25). Article 7034298 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICCE-Berlin.2014.7034298

@inproceedings{682b4a0dabf347b6bed0e84e39eff33f,

title = "Ultrasonic circular array sensing for human arm motion classification",

abstract = "Classification of human arm movements is an important problem in healthcare and well-being applications. In this paper, an ultrasonic Uniform Circular Array (UCA) Doppler sensing method is proposed for classifying arm movements from a given set. The method uses velocity and angular information, derived from Doppler frequencies and direction-of-arrival (DoA) by processing the signals received at the UCA, and employs a Bayesian classifier to distinguish between movements. The performance of the sensing method is evaluated using experimental datasets. The proposed ultrasonic UCA Doppler sensor and processing methods provide a compact solution for human arm movement classification.",

keywords = "Human arm movement classification, UCA Doppler sensor",

author = "{Van Sloun}, R. and A. Pandharipande and D. Caicedo and S. Srinivasan and P. Sommen",

year = "2015",

month = feb,

day = "5",

doi = "10.1109/ICCE-Berlin.2014.7034298",

language = "English",

pages = "24--25",

booktitle = "Consumer Electronics – Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference, Berlin, 7-10 September 2014",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "4th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2014, ICCE-Berlin 2014 ; Conference date: 07-09-2014 Through 10-09-2014",

url = "http://www.icce-berlin.org/2014/",

}

Van Sloun, R , Pandharipande, A, Caicedo, D, Srinivasan, S & Sommen, P 2015, Ultrasonic circular array sensing for human arm motion classification. in Consumer Electronics – Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference, Berlin, 7-10 September 2014., 7034298, Institute of Electrical and Electronics Engineers, Piscataway, pp. 24-25, 4th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2014, Berlin, Germany, 7/09/14. https://doi.org/10.1109/ICCE-Berlin.2014.7034298

Ultrasonic circular array sensing for human arm motion classification. / Van Sloun, R.; Pandharipande, A.; Caicedo, D. et al.
Consumer Electronics – Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference, Berlin, 7-10 September 2014. Piscataway: Institute of Electrical and Electronics Engineers, 2015. p. 24-25 7034298.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Ultrasonic circular array sensing for human arm motion classification

AU - Van Sloun, R.

AU - Pandharipande, A.

AU - Caicedo, D.

AU - Srinivasan, S.

AU - Sommen, P.

N1 - Conference code: 4

PY - 2015/2/5

Y1 - 2015/2/5

N2 - Classification of human arm movements is an important problem in healthcare and well-being applications. In this paper, an ultrasonic Uniform Circular Array (UCA) Doppler sensing method is proposed for classifying arm movements from a given set. The method uses velocity and angular information, derived from Doppler frequencies and direction-of-arrival (DoA) by processing the signals received at the UCA, and employs a Bayesian classifier to distinguish between movements. The performance of the sensing method is evaluated using experimental datasets. The proposed ultrasonic UCA Doppler sensor and processing methods provide a compact solution for human arm movement classification.

AB - Classification of human arm movements is an important problem in healthcare and well-being applications. In this paper, an ultrasonic Uniform Circular Array (UCA) Doppler sensing method is proposed for classifying arm movements from a given set. The method uses velocity and angular information, derived from Doppler frequencies and direction-of-arrival (DoA) by processing the signals received at the UCA, and employs a Bayesian classifier to distinguish between movements. The performance of the sensing method is evaluated using experimental datasets. The proposed ultrasonic UCA Doppler sensor and processing methods provide a compact solution for human arm movement classification.

KW - Human arm movement classification

KW - UCA Doppler sensor

UR - http://www.scopus.com/inward/record.url?scp=84937943469&partnerID=8YFLogxK

U2 - 10.1109/ICCE-Berlin.2014.7034298

DO - 10.1109/ICCE-Berlin.2014.7034298

M3 - Conference contribution

SP - 24

EP - 25

BT - Consumer Electronics – Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference, Berlin, 7-10 September 2014

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 4th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2014

Y2 - 7 September 2014 through 10 September 2014

ER -

Van Sloun R , Pandharipande A, Caicedo D, Srinivasan S, Sommen P. Ultrasonic circular array sensing for human arm motion classification. In Consumer Electronics – Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference, Berlin, 7-10 September 2014. Piscataway: Institute of Electrical and Electronics Engineers. 2015. p. 24-25. 7034298 doi: 10.1109/ICCE-Berlin.2014.7034298

Ultrasonic circular array sensing for human arm motion classification

Abstract

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this