A similarity measure approach for identifying causes of anomaly in activities of daily living

Salisu Wada Yahaya; Ahmad Lotfi; Mufti Mahmud

doi:10.1145/3316782.3322783

A similarity measure approach for identifying causes of anomaly in activities of daily living

Salisu Wada Yahaya, Ahmad Lotfi^*, Mufti Mahmud

^*Corresponding author for this work

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

Abstract

Anomaly detection in Activities of Daily Living is a challenging task driven by the need to improve the quality of life and promote independent living of the increasing ageing population. There are many computational methodologies for detecting anomalies. They are mainly based on the concept of learning usual activities of daily living routines and detect abnormalities in it. However, they are limited by their inability to predict the actual cause of the anomaly. Understanding the cause of the anomalies can enable robust anomaly detection system to be built with a low rate of false alarms. This paper proposes a similarity measure approach for identifying the cause of anomalies in activities of daily living routine. The proposed approach is based on a pair-wise similarity measure of the features present in a dataset. Preliminary experiments conducted on both real and synthetic data achieve an excellent result with an overall accuracy of 96%.

Original language	English
Title of host publication	Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019
Publisher	Association for Computing Machinery
Pages	575-579
Number of pages	5
ISBN (Electronic)	9781450362320
DOIs	https://doi.org/10.1145/3316782.3322783
State	Published - 5 Jun 2019
Externally published	Yes
Event	12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019 - Rhodes, Greece Duration: 5 Jun 2019 → 7 Jun 2019

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019
Country/Territory	Greece
City	Rhodes
Period	5/06/19 → 7/06/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

Keywords

ADL
Activities of Daily Living
Anomaly Detection
Novelty Detection
Similarity Measure

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3316782.3322783

Cite this

Wada Yahaya, S., Lotfi, A., & Mahmud, M. (2019). A similarity measure approach for identifying causes of anomaly in activities of daily living. In Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019 (pp. 575-579). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3316782.3322783

Wada Yahaya, Salisu ; Lotfi, Ahmad ; Mahmud, Mufti. / A similarity measure approach for identifying causes of anomaly in activities of daily living. Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019. Association for Computing Machinery, 2019. pp. 575-579 (ACM International Conference Proceeding Series).

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title = "A similarity measure approach for identifying causes of anomaly in activities of daily living",

abstract = "Anomaly detection in Activities of Daily Living is a challenging task driven by the need to improve the quality of life and promote independent living of the increasing ageing population. There are many computational methodologies for detecting anomalies. They are mainly based on the concept of learning usual activities of daily living routines and detect abnormalities in it. However, they are limited by their inability to predict the actual cause of the anomaly. Understanding the cause of the anomalies can enable robust anomaly detection system to be built with a low rate of false alarms. This paper proposes a similarity measure approach for identifying the cause of anomalies in activities of daily living routine. The proposed approach is based on a pair-wise similarity measure of the features present in a dataset. Preliminary experiments conducted on both real and synthetic data achieve an excellent result with an overall accuracy of 96\%.",

keywords = "ADL, Activities of Daily Living, Anomaly Detection, Novelty Detection, Similarity Measure",

author = "\{Wada Yahaya\}, Salisu and Ahmad Lotfi and Mufti Mahmud",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019 ; Conference date: 05-06-2019 Through 07-06-2019",

year = "2019",

month = jun,

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doi = "10.1145/3316782.3322783",

language = "English",

series = "ACM International Conference Proceeding Series",

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Wada Yahaya, S, Lotfi, A & Mahmud, M 2019, A similarity measure approach for identifying causes of anomaly in activities of daily living. in Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 575-579, 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019, Rhodes, Greece, 5/06/19. https://doi.org/10.1145/3316782.3322783

A similarity measure approach for identifying causes of anomaly in activities of daily living. / Wada Yahaya, Salisu; Lotfi, Ahmad; Mahmud, Mufti.
Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019. Association for Computing Machinery, 2019. p. 575-579 (ACM International Conference Proceeding Series).

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

TY - GEN

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AU - Lotfi, Ahmad

AU - Mahmud, Mufti

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N2 - Anomaly detection in Activities of Daily Living is a challenging task driven by the need to improve the quality of life and promote independent living of the increasing ageing population. There are many computational methodologies for detecting anomalies. They are mainly based on the concept of learning usual activities of daily living routines and detect abnormalities in it. However, they are limited by their inability to predict the actual cause of the anomaly. Understanding the cause of the anomalies can enable robust anomaly detection system to be built with a low rate of false alarms. This paper proposes a similarity measure approach for identifying the cause of anomalies in activities of daily living routine. The proposed approach is based on a pair-wise similarity measure of the features present in a dataset. Preliminary experiments conducted on both real and synthetic data achieve an excellent result with an overall accuracy of 96%.

AB - Anomaly detection in Activities of Daily Living is a challenging task driven by the need to improve the quality of life and promote independent living of the increasing ageing population. There are many computational methodologies for detecting anomalies. They are mainly based on the concept of learning usual activities of daily living routines and detect abnormalities in it. However, they are limited by their inability to predict the actual cause of the anomaly. Understanding the cause of the anomalies can enable robust anomaly detection system to be built with a low rate of false alarms. This paper proposes a similarity measure approach for identifying the cause of anomalies in activities of daily living routine. The proposed approach is based on a pair-wise similarity measure of the features present in a dataset. Preliminary experiments conducted on both real and synthetic data achieve an excellent result with an overall accuracy of 96%.

KW - ADL

KW - Activities of Daily Living

KW - Anomaly Detection

KW - Novelty Detection

KW - Similarity Measure

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BT - Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019

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Wada Yahaya S, Lotfi A, Mahmud M. A similarity measure approach for identifying causes of anomaly in activities of daily living. In Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019. Association for Computing Machinery. 2019. p. 575-579. (ACM International Conference Proceeding Series). doi: 10.1145/3316782.3322783

A similarity measure approach for identifying causes of anomaly in activities of daily living

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this