Using Z-score to extract human readable logic rules from physiological data

Nectarios Costadopoulos; Zahid Islam; David Tien

doi:10.1109/KSE.2019.8919473

Using Z-score to extract human readable logic rules from physiological data

Nectarios Costadopoulos, Zahid Islam, David Tien

Research output: Book chapter/Published conference paper › Conference paper › peer-review

3 Citations (Scopus)

Abstract

In this work we investigate the effectiveness of using Z-score conversion on physiological data for extracting human-readable rules via decision trees. To accomplish this we have utilised a popular dataset to obtain raw voltage information from physiological sensors, and minimally preprocessed the signals to aid in the construction of decision trees for unearthing logic rules. We have found that raw voltages change from experiment to experiment and vary widely between participants. The use of Z-score conversion proved very effective at normalising signals and provided a range of useful rules from individual participants.

Original language	English
Title of host publication	Proceedings of 2019 11th International Conference on Knowledge and Systems Engineering, KSE 2019
Editors	Josiane Mothe, Le Hoang Son, Nguyen Tran Quoc Vinh
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781728130033
ISBN (Print)	9781728130026
DOIs	https://doi.org/10.1109/KSE.2019.8919473
Publication status	Published - Oct 2019
Event	The 11th IEEE International Conference on Knowledge and Systems Engineering (KSE 2019) - University of Education and Science, The University of Danang, Da Nang, Viet Nam Duration: 24 Oct 2019 → 26 Oct 2019 http://kse2019.ued.udn.vn/welcome http://kse2019.ued.udn.vn/sites/default/files/KSE%202019%20Program%20Ver13-23-10-2019%20-%20print.pdf (program)

Conference

Conference	The 11th IEEE International Conference on Knowledge and Systems Engineering (KSE 2019)
Country/Territory	Viet Nam
City	Da Nang
Period	24/10/19 → 26/10/19
Other	The 11th KSE is an international forum for presentation, discussion, and exchange of the state-of-the-art research, development, and applications in the field of knowledge and systems engineering. The main objective of the KSE is to bring together researchers, practitioners and students not only to share research results and practical applications but also to foster collaboration in the field. The KSE this year will be held in Da Nang, a coastal and tourism city with beautiful beaches and a lot of exciting experiences. The conference will be co-organized by The University of Da Nang - University of Science and Education (UD-USE) and VNU University of Engineering and Technology (VNU-UET).
Internet address	http://kse2019.ued.udn.vn/welcome http://kse2019.ued.udn.vn/sites/default/files/KSE%202019%20Program%20Ver13-23-10-2019%20-%20print.pdf (program)

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10.1109/KSE.2019.8919473

Cite this

Costadopoulos, N., Islam, Z., & Tien, D. (2019). Using Z-score to extract human readable logic rules from physiological data. In J. Mothe, L. H. Son, & N. T. Quoc Vinh (Eds.), Proceedings of 2019 11th International Conference on Knowledge and Systems Engineering, KSE 2019 (pp. 1-6). Article 8919473 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/KSE.2019.8919473

Costadopoulos, Nectarios ; Islam, Zahid ; Tien, David. / Using Z-score to extract human readable logic rules from physiological data. Proceedings of 2019 11th International Conference on Knowledge and Systems Engineering, KSE 2019. editor / Josiane Mothe ; Le Hoang Son ; Nguyen Tran Quoc Vinh. United States : IEEE, Institute of Electrical and Electronics Engineers, 2019. pp. 1-6

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abstract = "In this work we investigate the effectiveness of using Z-score conversion on physiological data for extracting human-readable rules via decision trees. To accomplish this we have utilised a popular dataset to obtain raw voltage information from physiological sensors, and minimally preprocessed the signals to aid in the construction of decision trees for unearthing logic rules. We have found that raw voltages change from experiment to experiment and vary widely between participants. The use of Z-score conversion proved very effective at normalising signals and provided a range of useful rules from individual participants.",

keywords = "Body Temperature, Classification, Data Mining, Decision Trees, Emotion, Heart Rate, Physiological Signals, Respiration, Skin Conductance",

author = "Nectarios Costadopoulos and Zahid Islam and David Tien",

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publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "The 11th IEEE International Conference on Knowledge and Systems Engineering (KSE 2019) ; Conference date: 24-10-2019 Through 26-10-2019",

url = "http://kse2019.ued.udn.vn/welcome, http://kse2019.ued.udn.vn/sites/default/files/KSE%202019%20Program%20Ver13-23-10-2019%20-%20print.pdf",

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Costadopoulos, N , Islam, Z & Tien, D 2019, Using Z-score to extract human readable logic rules from physiological data. in J Mothe, LH Son & NT Quoc Vinh (eds), Proceedings of 2019 11th International Conference on Knowledge and Systems Engineering, KSE 2019., 8919473, IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 1-6, The 11th IEEE International Conference on Knowledge and Systems Engineering (KSE 2019), Da Nang, Viet Nam, 24/10/19. https://doi.org/10.1109/KSE.2019.8919473

Using Z-score to extract human readable logic rules from physiological data. / Costadopoulos, Nectarios ; Islam, Zahid ; Tien, David.
Proceedings of 2019 11th International Conference on Knowledge and Systems Engineering, KSE 2019. ed. / Josiane Mothe; Le Hoang Son; Nguyen Tran Quoc Vinh. United States: IEEE, Institute of Electrical and Electronics Engineers, 2019. p. 1-6 8919473.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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AU - Islam, Zahid

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N2 - In this work we investigate the effectiveness of using Z-score conversion on physiological data for extracting human-readable rules via decision trees. To accomplish this we have utilised a popular dataset to obtain raw voltage information from physiological sensors, and minimally preprocessed the signals to aid in the construction of decision trees for unearthing logic rules. We have found that raw voltages change from experiment to experiment and vary widely between participants. The use of Z-score conversion proved very effective at normalising signals and provided a range of useful rules from individual participants.

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KW - Body Temperature

KW - Classification

KW - Data Mining

KW - Decision Trees

KW - Emotion

KW - Heart Rate

KW - Physiological Signals

KW - Respiration

KW - Skin Conductance

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Costadopoulos N , Islam Z , Tien D. Using Z-score to extract human readable logic rules from physiological data. In Mothe J, Son LH, Quoc Vinh NT, editors, Proceedings of 2019 11th International Conference on Knowledge and Systems Engineering, KSE 2019. United States: IEEE, Institute of Electrical and Electronics Engineers. 2019. p. 1-6. 8919473 doi: 10.1109/KSE.2019.8919473

Using Z-score to extract human readable logic rules from physiological data

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