Wearable sensor-based activity recognition for housekeeping task

Kai Chun Liu; Chien Yi Yen; Li Han Chang; Chia Yeh Hsieh; Chia Tai Chan

doi:10.1109/BSN.2017.7936009

Wearable sensor-based activity recognition for housekeeping task

Kai Chun Liu
, Chien Yi Yen
, Li Han Chang
, Chia Yeh Hsieh
, Chia Tai Chan

生物醫學工程學系

研究成果 › 同行評審

25 引文斯高帕斯（Scopus）

摘要

In order to improve healthcare services and support clinical professionals, it is important to develop the unobstructive and automatic ADLs monitoring system for healthcare applications. Currently, various works have been developed for the monitoring of daily activities, such as ambulation, kitchen task, food and fluid intake, dressing, and medication intake while only few works paid attention to the housekeeping task. Housekeeping activity is a complex task, generally important for the several clinical assessment tools. In this work, we design and develop a wearable sensor-based activity recognition system recognize housekeeping tasks and classify the activity level. The proposed system achieves 90.67% accuracy for housekeeping tasks recognition, and 94.35% accuracy for activity level classification, respectively. The results of the experiment demonstrate that the system is reliable and fulfills the requirements of the unobstructive, objective, and long-Term monitoring system.

原文	English
主出版物標題	2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017
發行者	Institute of Electrical and Electronics Engineers Inc.
頁面	67-70
頁數	4
ISBN（電子）	9781509062447
DOIs	https://doi.org/10.1109/BSN.2017.7936009
出版狀態	Published - 30 5月 2017
事件	14th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017 - Eindhoven, 荷蘭持續時間: 9 5月 2017 → 12 5月 2017

出版系列

名字	2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017

Conference

Conference	14th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017
國家/地區	荷蘭
城市	Eindhoven
期間	9/05/17 → 12/05/17

UN SDG

此研究成果有助於以下永續發展目標

SDG 3 良好的健康和福祉

存取文件

10.1109/BSN.2017.7936009

其它文件與鏈接

Link to publication in Scopus

引用此

Liu, K. C., Yen, C. Y., Chang, L. H., Hsieh, C. Y., & Chan, C. T. (2017). Wearable sensor-based activity recognition for housekeeping task. 於 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017 (頁 67-70). 文章 7936009 (2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BSN.2017.7936009

Liu, Kai Chun ; Yen, Chien Yi ; Chang, Li Han 等. / Wearable sensor-based activity recognition for housekeeping task. 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 頁 67-70 (2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017).

@inproceedings{b5ab8845aaa4470c8206698834f71a38,

title = "Wearable sensor-based activity recognition for housekeeping task",

abstract = "In order to improve healthcare services and support clinical professionals, it is important to develop the unobstructive and automatic ADLs monitoring system for healthcare applications. Currently, various works have been developed for the monitoring of daily activities, such as ambulation, kitchen task, food and fluid intake, dressing, and medication intake while only few works paid attention to the housekeeping task. Housekeeping activity is a complex task, generally important for the several clinical assessment tools. In this work, we design and develop a wearable sensor-based activity recognition system recognize housekeeping tasks and classify the activity level. The proposed system achieves 90.67\% accuracy for housekeeping tasks recognition, and 94.35\% accuracy for activity level classification, respectively. The results of the experiment demonstrate that the system is reliable and fulfills the requirements of the unobstructive, objective, and long-Term monitoring system.",

author = "Liu, \{Kai Chun\} and Yen, \{Chien Yi\} and Chang, \{Li Han\} and Hsieh, \{Chia Yeh\} and Chan, \{Chia Tai\}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017 ; Conference date: 09-05-2017 Through 12-05-2017",

year = "2017",

month = may,

day = "30",

doi = "10.1109/BSN.2017.7936009",

language = "English",

series = "2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017",

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

pages = "67--70",

booktitle = "2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017",

address = "美國",

}

Liu, KC, Yen, CY, Chang, LH, Hsieh, CY & Chan, CT 2017, Wearable sensor-based activity recognition for housekeeping task. 於 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017., 7936009, 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017, Institute of Electrical and Electronics Engineers Inc., 頁 67-70, 14th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017, Eindhoven, 荷蘭, 9/05/17. https://doi.org/10.1109/BSN.2017.7936009

Wearable sensor-based activity recognition for housekeeping task. / Liu, Kai Chun; Yen, Chien Yi; Chang, Li Han 等.
2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 67-70 7936009 (2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017).

研究成果 › 同行評審

TY - GEN

T1 - Wearable sensor-based activity recognition for housekeeping task

AU - Liu, Kai Chun

AU - Yen, Chien Yi

AU - Chang, Li Han

AU - Hsieh, Chia Yeh

AU - Chan, Chia Tai

PY - 2017/5/30

Y1 - 2017/5/30

N2 - In order to improve healthcare services and support clinical professionals, it is important to develop the unobstructive and automatic ADLs monitoring system for healthcare applications. Currently, various works have been developed for the monitoring of daily activities, such as ambulation, kitchen task, food and fluid intake, dressing, and medication intake while only few works paid attention to the housekeeping task. Housekeeping activity is a complex task, generally important for the several clinical assessment tools. In this work, we design and develop a wearable sensor-based activity recognition system recognize housekeeping tasks and classify the activity level. The proposed system achieves 90.67% accuracy for housekeeping tasks recognition, and 94.35% accuracy for activity level classification, respectively. The results of the experiment demonstrate that the system is reliable and fulfills the requirements of the unobstructive, objective, and long-Term monitoring system.

AB - In order to improve healthcare services and support clinical professionals, it is important to develop the unobstructive and automatic ADLs monitoring system for healthcare applications. Currently, various works have been developed for the monitoring of daily activities, such as ambulation, kitchen task, food and fluid intake, dressing, and medication intake while only few works paid attention to the housekeeping task. Housekeeping activity is a complex task, generally important for the several clinical assessment tools. In this work, we design and develop a wearable sensor-based activity recognition system recognize housekeeping tasks and classify the activity level. The proposed system achieves 90.67% accuracy for housekeeping tasks recognition, and 94.35% accuracy for activity level classification, respectively. The results of the experiment demonstrate that the system is reliable and fulfills the requirements of the unobstructive, objective, and long-Term monitoring system.

UR - https://www.scopus.com/pages/publications/85025466428

U2 - 10.1109/BSN.2017.7936009

DO - 10.1109/BSN.2017.7936009

M3 - Conference contribution

AN - SCOPUS:85025466428

T3 - 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017

SP - 67

EP - 70

BT - 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017

Y2 - 9 May 2017 through 12 May 2017

ER -

Liu KC, Yen CY, Chang LH, Hsieh CY, Chan CT. Wearable sensor-based activity recognition for housekeeping task. 於 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 67-70. 7936009. (2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2017). doi: 10.1109/BSN.2017.7936009

Wearable sensor-based activity recognition for housekeeping task

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出版系列

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