This paper is in the following e-collection/theme issue:

Anxiety and Stress Disorders (881) Special Issue on Computing and Mental Health (2018) (32) Wearable Devices and Sensors (702) Novel Sensors and Data Acquisition Methods in Cardiology (164)

Published on in Vol 6 , No 4 (2019) :April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10140, first published .
Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging

Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging

Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging

Authors of this article:

Youngjun Cho 1, 2 Author Orcid Image ;   Simon J Julier 1 Author Orcid Image ;   Nadia Bianchi-Berthouze 2 Author Orcid Image
Article Authors Cited by (38) Tweetations (11) Metrics

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  7. Perpetuini D, Chiarelli A, Cardone D, Filippini C, Rinella S, Massimino S, Bianco F, Bucciarelli V, Vinciguerra V, Fallica P, Perciavalle V, Gallina S, Conoci S, Merla A. Prediction of state anxiety by machine learning applied to photoplethysmography data. PeerJ 2021;9:e10448 View
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  10. Inagaki K, Ohta Y. Capacity of Autonomous Sensory Meridian Response on the Reduction of Mental Stress. International Journal of Environmental Research and Public Health 2022;19(21):14577 View
  11. Novikov M, Anashkina D, Ivanov A, Konovalov A, Popov V. Thermographic analysis of postoperative changes in the nasal breathing efficiency in infants and young children with unilateral cleft lip. International Journal of Computer Assisted Radiology and Surgery 2021;16(12):2225 View
  12. Wang K, Julier S, Cho Y. Attention-Based Applications in Extended Reality to Support Autistic Users: A Systematic Review. IEEE Access 2022;10:15574 View
  13. Özdil A, Yilmaz B. Medical infrared thermal image based fatty liver classification using machine and deep learning. Quantitative InfraRed Thermography Journal 2023:1 View
  14. Ninan J, Kumar B, Padodara R. A Glimpse into Artificial Intelligence in Animal Physiology and Allied Sciences. Animal Reproduction Update 2022;2(1):72 View
  15. Rinella S, Massimino S, Fallica P, Giacobbe A, Donato N, Coco M, Neri G, Parenti R, Perciavalle V, Conoci S. Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison. Biosensors 2022;12(10):811 View
  16. Rachim V, Baek J, Kim Y, Kim Y, Park S. High Sampling Rate Smartphone-PPG via Built-in Rolling Shutter Image Sensor. IEEE Internet of Things Journal 2023;10(1):512 View
  17. Tump D, Narayan N, Verbiest V, Hermsen S, Goris A, Chiu C, Van Stiphout R. Stressors and Destressors in Working From Home Based on Context and Physiology From Self-Reports and Smartwatch Measurements: International Observational Study Trial. JMIR Formative Research 2022;6(11):e38562 View
  18. Volkov I, Sagaidachnyi A, Fomin A. Photoplethysmographic Imaging of Hemodynamics and Two-Dimensional Oximetry. Optics and Spectroscopy 2022;130(7):452 View
  19. Aydemir T, Şahin M, Aydemir O. Sequential forward mother wavelet selection method for mental workload assessment on N-back task using photoplethysmography signals. Infrared Physics & Technology 2021;119:103966 View
  20. Holloway C, Bhot W, Yong K, McCarthy I, Suzuki T, Carton A, Yang B, Serougne R, Boampong D, Tyler N, Crutch S, Berthouze N, Cho Y. STEP-UP: Enabling Low-Cost IMU Sensors to Predict the Type of Dementia During Everyday Stair Climbing. Frontiers in Computer Science 2022;3 View
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