Emotion Recognition by Point Process Characterization of Heartbeat Dynamics

Akshay Sujatha Ravindran, Sho Nakagome, Dilranjan S. Wickramasuriya, Jose L. Contreras Vidal, Rose T. Faghih

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

3 Scopus citations

Abstract

Recognizing human emotion from heartbeat information alone is a challenging but ongoing research area. Here, we utilize a point process model to characterize heartbeat dynamics and use it to extract instantaneous heart rate variability (HRV) features. These features are then fed into a convolutional neural network (CNN) to characterize different emotional states from small windows. On average, we achieved over 60% classification accuracy and as high as 77% in some subjects. This is comparable to other studies that use a combination of physiological signals as opposed to only HRV measures as done here. Informative features were identified for the different affective states. These findings enable the possibility of augmenting electrocardiogram or photoplethysmogram monitoring wearable devices with automated human emotion recognition capabilities for mental health applications. They also allow for the use of instantaneous estimation of HRV features to be used in combination with models that use other types of physiological signals for instantaneous emotion recognition.

Original languageEnglish (US)
Title of host publication2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-16
Number of pages4
ISBN (Electronic)9781728138121
DOIs
StatePublished - Nov 1 2019
Event2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019 - Bethesda, United States
Duration: Nov 20 2019Nov 22 2019

Other

Other2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019
CountryUnited States
CityBethesda
Period11/20/1911/22/19

Keywords

  • emotion
  • heart rate
  • point process modeling

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Biomedical Engineering
  • Health Informatics
  • Instrumentation
  • Health(social science)

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  • Cite this

    Ravindran, A. S., Nakagome, S., Wickramasuriya, D. S., Contreras Vidal, J. L., & Faghih, R. T. (2019). Emotion Recognition by Point Process Characterization of Heartbeat Dynamics. In 2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019 (pp. 13-16). [8962886] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HI-POCT45284.2019.8962886