Analysing physiology of interpersonal conflicts using a wrist device
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 11249 LNCS, Page: 162-167
2018
- 7Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures7
- Readers7
Conference Paper Description
We present a study in which 59 participants logged their interpersonal conflicts while wearing an Empatica E4 wristband. They marked the beginnings and endings of the conflicts, as well as their intensity. In this paper, the dataset is described and a preliminary analysis is performed. We describe data segmentation and feature calculation process. Next, the interrelationships between the features and labels are explored. A logistic regression model for conflict recognition was built and significant features were selected. Finally, we constructed a machine learning model and proposed how to improve it.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85056487546&origin=inward; http://dx.doi.org/10.1007/978-3-030-03062-9_13; http://link.springer.com/10.1007/978-3-030-03062-9_13; http://link.springer.com/content/pdf/10.1007/978-3-030-03062-9_13; https://doi.org/10.1007%2F978-3-030-03062-9_13; https://dx.doi.org/10.1007/978-3-030-03062-9_13; https://link.springer.com/chapter/10.1007/978-3-030-03062-9_13
Springer Nature America, Inc
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