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Simple, Transparent, and Flexible Automated Quality Assessment Procedures for Ambulatory Electrodermal Activity

Date: April 9 2020

Summary: A simple, transparent, flexible, and automated quality assessment procedure for ambulatory EDA data

Keywords: ##bibliography #eda #rochester #eda #rules #simple #transparent #autism #children #pediatrics #archive

Bibliography

I. R. Kleckner et al., "Simple, Transparent, and Flexible Automated Quality Assessment Procedures for Ambulatory Electrodermal Activity Data," IEEE Trans. Biomed. Eng., vol. 65, no. 7, pp. 1460–1467, Jul. 2018, doi: 10.1109/TBME.2017.2758643.

Table of Contents

    1. Rule-based Algorithm
      1. Notes on Algorithm Rules
    2. Misc Notes
  1. How To Cite
  2. References
  3. Discussion:

Rule-based Algorithm

The authors also decided to create a very simple rule-based algorithm in an effort to make results easily reproducible and understandable to researchers of differing backgrounds. This algorithm for assessing data quality was as is follows:

NumberRuleRationale
1EDA is not within the range of 0.0560μS0.05 - 60 \mu SPrevent "floor" and "ceiling" artifacts
2EDA fluctuates too fast (+/10μSsecond)(+/- 10 \frac{\mu S}{second})To prevent "jump" artifacts
3Temperature not within 30-40 CCPreserve best accuracy of data
4EDA data within 55 sec of invalid sectionsInvalid sections based on rules 131-3

If the data did not adhere to these rules, it was classified as artifact.

Notes on Algorithm Rules

1. In Rule 1, 60 was chosen as an upper limit specifically because that was the upper limit of the Q Sensor.

2. Rule 2's rationale came from [1]–[3]

3. For Rule 3, their data recorded temperatures of 32 - 36 CC consistently for individuals

Misc Notes

How To Cite

Zelko, Jacob. Simple, Transparent, and Flexible Automated Quality Assessment Procedures for Ambulatory Electrodermal Activity. https://jacobzelko.com/04092020195141-transparent-eda-data. April 9 2020.

References

[1] W. Boucsein, Electrodermal Activity. Boston, MA: Springer US, 2012.

[2] R. Kocielnik, N. Sidorova, F. M. Maggi, M. Ouwerkerk, and J. H. Westerink, “Smart technologies for long-term stress monitoring at work,” in Proceedings of the 26th IEEE international symposium on computer-based medical systems, 2013, pp. 53–58.

[3] F. H. Wilhelm and W. T. Roth, “Ambulatory assessment of clinical anxiety,” Ambul. Assess. Comput.-Assist. Psychol. Psychophysiological Methods Monit. Field Stud., pp. 317–345, 1996.

Discussion:

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