Requirements for a Reference Dataset for Multimodal Human Stress Detection
Autor: | Erwin Prassler, Teena Hassan, Bhargavi Mahesh, Jens-Uwe Garbas |
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Rok vydání: | 2019 |
Předmět: |
Coping (psychology)
Data collection Modalities Remote patient monitoring Computer science business.industry 05 social sciences Comparability Machine learning computer.software_genre 03 medical and health sciences 0302 clinical medicine Data acquisition Empirical research 0501 psychology and cognitive sciences 050102 behavioral science & comparative psychology Artificial intelligence business computer Requirements analysis 030217 neurology & neurosurgery |
Zdroj: | PerCom Workshops |
DOI: | 10.1109/percomw.2019.8730884 |
Popis: | Stress is necessary for optimal performance and functioning in daily life. However, when stress exceeds person-specific coping levels, then it begins to negatively impact health and productivity. An automatic stress monitoring system that tracks stress levels based on physical and physiological parameters, can assist the user in maintaining stress within healthy limits. In order to build such a system, we need to develop and test various algorithms on a reference dataset consisting of multimodal stress responses. Such a reference dataset should fulfil requirements derived from results and practices of clinical and empirical research. This paper proposes a set of such requirements to support the establishment of a reference dataset for multimodal human stress detection. The requirements cover person-dependent and technical aspects such as selection of sample population, choice of stress stimuli, inclusion of multiple stress modalities, selection of annotation methods, and selection of data acquisition devices. Existing publicly available stress datasets were evaluated based on criteria derived from the proposed requirements. It was found that none of these datasets completely fulfilled the requirements. Therefore, efforts should be made in the future to establish a reference dataset, satisfying the specified requirements, in order to ensure comparability and reliability of results. |
Databáze: | OpenAIRE |
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