Attention-based stress detection exploiting non-contact monitoring of movement patterns with IR-UWB radar

Jonghoon Shin, Junhyung Moon, Beomsik Kim, Jihwan Eom, Noseong Park, Kyoungwoo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Detecting one's stress state is essential to prevent severe health problems. However, most of the existing stress detection techniques require direct contact between the user and the sensor devices, leading to user inconvenience. Further, it is difficult to provide reliable stress detection because of loosened wearing of sensor devices and the limited battery life of the devices. In this paper, we present i) a non-contact stress detection technique based on the user movement patterns using an impulse-radio ultra-wideband (IR-UWB) radar without estimating vital signals and ii) an attention-based neural network. We design novel radar signal features to accurately represent user movements that are related to the stress state. For the demonstration, we collect a multi-modal dataset from 50 subjects under stress-inducing experiments using both contact and non-contact sensor devices. Consequently, we achieve a binary stress detection accuracy of 76.22% which outperforms the wearable-based approach with movement data by up to 11.57%.

Original languageEnglish
Title of host publicationProceedings of the 36th Annual ACM Symposium on Applied Computing, SAC 2021
PublisherAssociation for Computing Machinery
Pages637-640
Number of pages4
ISBN (Electronic)9781450381048
DOIs
Publication statusPublished - 2021 Mar 22
Event36th Annual ACM Symposium on Applied Computing, SAC 2021 - Virtual, Online, Korea, Republic of
Duration: 2021 Mar 222021 Mar 26

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Conference

Conference36th Annual ACM Symposium on Applied Computing, SAC 2021
CountryKorea, Republic of
CityVirtual, Online
Period21/3/2221/3/26

Bibliographical note

Funding Information:
This work was supported by Institute of Information & Communications Technology Planning Evaluation (IITP) grant funded by the Korea government(MSIT) [2016-0-00562(R0124-16-0002), Emotional Intelligence Technology to Infer Human Emotion and Carry on Dialogue Accordingly].

Publisher Copyright:
© 2021 Owner/Author.

All Science Journal Classification (ASJC) codes

  • Software

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