ActDetector: Detecting Daily Activities Using Smartwatches

Xiao Sun; Li Qiu; Yibo Wu; Guohong Cao

doi:10.1109/MASS.2017.35

ActDetector: Detecting Daily Activities Using Smartwatches

Xiao Sun
, Li Qiu
, Yibo Wu
, Guohong Cao

Computer Science and Engineering

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

10 Scopus citations

Abstract

Detecting daily activities is helpful for health care and clinical medicine. In this paper, we present ActDetector, a smartwatch based application which detects 8 common daily activities, including sitting, walking, running, going upstairs, going downstairs, eating, driving and sitting in a vehicle. By leveraging the built-in sensors on smartwatch, a multi-level classification system is proposed which considers both detection accuracy and energy efficiency. ActDetector is designed to work unobtrusively, no matter on which wrist the smartwatch is worn. We have implemented ActDetector on Sony Smartwatch 3 and evaluated its performance in real experiments involving 12 users. Experimental results show that ActDetector is energy efficient and can detect the daily activities with high accuracy.

Original language	English (US)
Title of host publication	Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-9
Number of pages	9
ISBN (Electronic)	9781538623237
DOIs	https://doi.org/10.1109/MASS.2017.35
State	Published - Nov 14 2017
Event	14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017 - Orlando, United States Duration: Oct 22 2017 → Oct 25 2017

Publication series

Name	Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017

Other

Other	14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
Country/Territory	United States
City	Orlando
Period	10/22/17 → 10/25/17

UN SDGs

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

SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

Mechanical Engineering
Instrumentation
Electrical and Electronic Engineering

Access to Document

10.1109/MASS.2017.35

Cite this

Sun, X., Qiu, L., Wu, Y., & Cao, G. (2017). ActDetector: Detecting Daily Activities Using Smartwatches. In Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017 (pp. 1-9). Article 8108722 (Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MASS.2017.35

@inproceedings{5a910efd572b475f95212337b7190f81,

title = "ActDetector: Detecting Daily Activities Using Smartwatches",

abstract = "Detecting daily activities is helpful for health care and clinical medicine. In this paper, we present ActDetector, a smartwatch based application which detects 8 common daily activities, including sitting, walking, running, going upstairs, going downstairs, eating, driving and sitting in a vehicle. By leveraging the built-in sensors on smartwatch, a multi-level classification system is proposed which considers both detection accuracy and energy efficiency. ActDetector is designed to work unobtrusively, no matter on which wrist the smartwatch is worn. We have implemented ActDetector on Sony Smartwatch 3 and evaluated its performance in real experiments involving 12 users. Experimental results show that ActDetector is energy efficient and can detect the daily activities with high accuracy.",

author = "Xiao Sun and Li Qiu and Yibo Wu and Guohong Cao",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017 ; Conference date: 22-10-2017 Through 25-10-2017",

year = "2017",

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language = "English (US)",

series = "Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017",

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Sun, X, Qiu, L, Wu, Y & Cao, G 2017, ActDetector: Detecting Daily Activities Using Smartwatches. in Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017., 8108722, Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017, Institute of Electrical and Electronics Engineers Inc., pp. 1-9, 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017, Orlando, United States, 10/22/17. https://doi.org/10.1109/MASS.2017.35

ActDetector: Detecting Daily Activities Using Smartwatches. / Sun, Xiao; Qiu, Li; Wu, Yibo et al.
Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-9 8108722 (Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017).

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

TY - GEN

T1 - ActDetector

T2 - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017

AU - Sun, Xiao

AU - Qiu, Li

AU - Wu, Yibo

AU - Cao, Guohong

PY - 2017/11/14

Y1 - 2017/11/14

N2 - Detecting daily activities is helpful for health care and clinical medicine. In this paper, we present ActDetector, a smartwatch based application which detects 8 common daily activities, including sitting, walking, running, going upstairs, going downstairs, eating, driving and sitting in a vehicle. By leveraging the built-in sensors on smartwatch, a multi-level classification system is proposed which considers both detection accuracy and energy efficiency. ActDetector is designed to work unobtrusively, no matter on which wrist the smartwatch is worn. We have implemented ActDetector on Sony Smartwatch 3 and evaluated its performance in real experiments involving 12 users. Experimental results show that ActDetector is energy efficient and can detect the daily activities with high accuracy.

AB - Detecting daily activities is helpful for health care and clinical medicine. In this paper, we present ActDetector, a smartwatch based application which detects 8 common daily activities, including sitting, walking, running, going upstairs, going downstairs, eating, driving and sitting in a vehicle. By leveraging the built-in sensors on smartwatch, a multi-level classification system is proposed which considers both detection accuracy and energy efficiency. ActDetector is designed to work unobtrusively, no matter on which wrist the smartwatch is worn. We have implemented ActDetector on Sony Smartwatch 3 and evaluated its performance in real experiments involving 12 users. Experimental results show that ActDetector is energy efficient and can detect the daily activities with high accuracy.

UR - https://www.scopus.com/pages/publications/85040574064

UR - https://www.scopus.com/pages/publications/85040574064#tab=citedBy

U2 - 10.1109/MASS.2017.35

DO - 10.1109/MASS.2017.35

M3 - Conference contribution

AN - SCOPUS:85040574064

T3 - Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017

SP - 1

EP - 9

BT - Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 22 October 2017 through 25 October 2017

ER -

Sun X, Qiu L, Wu Y, Cao G. ActDetector: Detecting Daily Activities Using Smartwatches. In Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-9. 8108722. (Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017). doi: 10.1109/MASS.2017.35

ActDetector: Detecting Daily Activities Using Smartwatches

Abstract

Publication series

Other

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

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