[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
research-article
Open access

Reading Between the Heat: Co-Teaching Body Thermal Signatures for Non-intrusive Stress Detection

Published: 12 January 2024 Publication History

Abstract

Stress impacts our physical and mental health as well as our social life. A passive and contactless indoor stress monitoring system can unlock numerous important applications such as workplace productivity assessment, smart homes, and personalized mental health monitoring. While the thermal signatures from a user's body captured by a thermal camera can provide important information about the "fight-flight" response of the sympathetic and parasympathetic nervous system, relying solely on thermal imaging for training a stress prediction model often lead to overfitting and consequently a suboptimal performance. This paper addresses this challenge by introducing ThermaStrain, a novel co-teaching framework that achieves high-stress prediction performance by transferring knowledge from the wearable modality to the contactless thermal modality. During training, ThermaStrain incorporates a wearable electrodermal activity (EDA) sensor to generate stress-indicative representations from thermal videos, emulating stress-indicative representations from a wearable EDA sensor. During testing, only thermal sensing is used, and stress-indicative patterns from thermal data and emulated EDA representations are extracted to improve stress assessment. The study collected a comprehensive dataset with thermal video and EDA data under various stress conditions and distances. ThermaStrain achieves an F1 score of 0.8293 in binary stress classification, outperforming the thermal-only baseline approach by over 9%. Extensive evaluations highlight ThermaStrain's effectiveness in recognizing stress-indicative attributes, its adaptability across distances and stress scenarios, real-time executability on edge platforms, its applicability to multi-individual sensing, ability to function on limited visibility and unfamiliar conditions, and the advantages of its co-teaching approach. These evaluations validate ThermaStrain's fidelity and its potential for enhancing stress assessment.

References

[1]
Yomna Abdelrahman, Eduardo Velloso, Tilman Dingler, Albrecht Schmidt, and Frank Vetere. 2017. Cognitive heat: exploring the usage of thermal imaging to unobtrusively estimate cognitive load. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 1--20.
[2]
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, and Masanori Koyama. 2019. Optuna: A Next-generation Hyperparameter Optimization Framework. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
[3]
Mustafa MM Al Qudah, Ahmad SA Mohamed, and Syaheerah L Lutfi. 2021. Affective State Recognition Using Thermal-Based Imaging: A Survey. Comput. Syst. Sci. Eng. 37, 1 (2021), 47--62.
[4]
Ane Alberdi, Asier Aztiria, and Adrian Basarab. 2016. Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review. Journal of biomedical informatics 59 (2016), 49--75.
[5]
Ane Alberdi, Asier Aztiria, Adrian Basarab, and Diane J Cook. 2018. Using smart offices to predict occupational stress. International Journal of Industrial Ergonomics 67 (2018), 13--26.
[6]
Jerone TA Andrews, Dora Zhao, William Thong, Apostolos Modas, Orestis Papakyriakopoulos, Shruti Nagpal, and Alice Xiang. 2023. Ethical considerations for collecting human-centric image datasets. arXiv preprint arXiv:2302.03629 (2023).
[7]
Apple. 2023. Apple Watch. https://support.apple.com/.
[8]
Jeroen HM Bergmann, Vikesh Chandaria, and Alison McGregor. 2012. Wearable and implantable sensors: The patient's perspective. Sensors 12, 12 (2012), 16695--16709.
[9]
Wolfram Boucsein. 2012. Electrodermal activity. Springer Science & Business Media.
[10]
Jason J Braithwaite, Derrick G Watson, Robert Jones, and Mickey Rowe. 2013. A guide for analysing electrodermal activity (EDA) & skin conductance responses (SCRs) for psychological experiments. Psychophysiology 49, 1 (2013), 1017--1034.
[11]
Anne-Marie Brouwer and Maarten A Hogervorst. 2014. A new paradigm to induce mental stress: the Sing-a-Song Stress Test (SSST). Frontiers in neuroscience 8 (2014), 224.
[12]
Ruud M Buijs and Corbert G Van Eden. 2000. The integration of stress by the hypothalamus, amygdala and prefrontal cortex: balance between the autonomic nervous system and the neuroendocrine system. In Progress in brain research. Vol. 126. Elsevier, 117--132.
[13]
Sara Campanella, Ayham Altaleb, Alberto Belli, Paola Pierleoni, and Lorenzo Palma. 2023. A Method for Stress Detection Using Empatica E4 Bracelet and Machine-Learning Techniques. Sensors 23, 7 (2023), 3565.
[14]
Yekta Said Can, Niaz Chalabianloo, Deniz Ekiz, and Cem Ersoy. 2019. Continuous stress detection using wearable sensors in real life: Algorithmic programming contest case study. Sensors 19, 8 (2019), 1849.
[15]
Gavin C Cawley and Nicola LC Talbot. 2010. On over-fitting in model selection and subsequent selection bias in performance evaluation. The Journal of Machine Learning Research 11 (2010), 2079--2107.
[16]
CDW. 2023. Future Proofing & New Work Dynamic. Retrieved July, 2023 from https://shorturl.at/ehAGX
[17]
Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer Chayes, Levent Sagun, and Riccardo Zecchina. 2019. Entropy-sgd: Biasing gradient descent into wide valleys. Journal of Statistical Mechanics: Theory and Experiment 2019, 12 (2019), 124018.
[18]
Sheng-Yang Chiu, Yu-Ting Huang, Chieh-Ting Lin, Yu-Chee Tseng, Jen-Jee Chen, Meng-Hsuan Tu, Bo-Chen Tung, and YuJou Nieh. 2023. Privacy-preserving video conferencing via thermal-generative images. In 2023 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 9478--9485.
[19]
Youngjun Cho and Nadia Bianchi-Berthouze. 2019. Physiological and affective computing through thermal imaging: A survey. arXiv preprint arXiv:1908.10307 (2019).
[20]
Youngjun Cho, Simon J Julier, and Nadia Bianchi-Berthouze. 2019. Instant stress: detection of perceived mental stress through smartphone photoplethysmography and thermal imaging. JMIR mental health 6, 4 (2019), e10140.
[21]
Pau Climent-Pérez and Francisco Florez-Revuelta. 2021. Protection of visual privacy in videos acquired with RGB cameras for active and assisted living applications. Multimedia Tools and Applications 80, 15 (2021), 23649--23664.
[22]
Samantha L Connolly and Lauren B Alloy. 2018. Negative event recall as a vulnerability for depression: Relationship between momentary stress-reactive rumination and memory for daily life stress. Clinical Psychological Science 6, 1 (2018), 32--47.
[23]
Carl B Cross, Julie A Skipper, and Douglas T Petkie. 2013. Thermal imaging to detect physiological indicators of stress in humans. In Thermosense: thermal infrared applications XXXV, Vol. 8705. SPIE, 141--155.
[24]
Sally S Dickerson and Margaret E Kemeny. 2004. Acute stressors and cortisol responses: a theoretical integration and synthesis of laboratory research. Psychological bulletin 130, 3 (2004), 355.
[25]
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al. 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020).
[26]
Veronika Engert, Arcangelo Merla, Joshua A Grant, Daniela Cardone, Anita Tusche, and Tania Singer. 2014. Exploring the use of thermal infrared imaging in human stress research. PloS one 9, 3 (2014), e90782.
[27]
Hyukmin Eum, Jeisung Lee, Changyong Yoon, and Mignon Park. 2013. Human action recognition for night vision using temporal templates with infrared thermal camera. In 2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 617--621.
[28]
Victor Foo Siang Fook, Pham Viet Thang, That Mon Htwe, Qiu Qiang, Aung Aung Phyo Wai, Maniyeri Jayachandran, Jit Biswas, and Philip Yap. 2007. Automated recognition of complex agitation behavior of dementia patients using video camera. In 2007 9th International Conference on e-Health Networking, Application and Services. IEEE, 68--73.
[29]
Mathieu Pagé Fortin and Brahim Chaib-Draa. 2019. Multimodal Sentiment Analysis: A Multitask Learning Approach. In ICPRAM. 368--376.
[30]
Mihai Gavrilescu and Nicolae Vizireanu. 2019. Predicting Depression, Anxiety, and Stress Levels from Videos Using the Facial Action Coding System. Sensors 19, 17 (2019), 3693.
[31]
Sayandeep Ghosh, Seongki Kim, Muhammad Fazal Ijaz, Pawan Kumar Singh, and Mufti Mahmud. 2022. Classification of mental stress from wearable physiological sensors using image-encoding-based deep neural network. Biosensors 12, 12 (2022), 1153.
[32]
G. Giannakakis, M. Pediaditis, D. Manousos, E. Kazantzaki, F. Chiarugi, P.G. Simos, K. Marias, and M. Tsiknakis. 2017. Stress and anxiety detection using facial cues from videos. Biomedical Signal Processing and Control 31 (2017), 89--101. https://doi.org/10.1016/j.bspc.2016.06.020
[33]
Ian J Goodfellow, Oriol Vinyals, and Andrew M Saxe. 2014. Qualitatively characterizing neural network optimization problems. arXiv preprint arXiv:1412.6544 (2014).
[34]
William K Goodman, Johanna Janson, and Jutta M Wolf. 2017. Meta-analytical assessment of the effects of protocol variations on cortisol responses to the Trier Social Stress Test. Psychoneuroendocrinology 80 (2017), 26--35.
[35]
Erin Griffiths, Salah Assana, and Kamin Whitehouse. 2018. Privacy-preserving image processing with binocular thermal cameras. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 4 (2018), 1--25.
[36]
James J Gross and Hooria Jazaieri. 2014. Emotion, emotion regulation, and psychopathology: An affective science perspective. Clinical Psychological Science 2, 4 (2014), 387--401.
[37]
Aline C Gubrium, Amy L Hill, and Sarah Flicker. 2014. A situated practice of ethics for participatory visual and digital methods in public health research and practice: A focus on digital storytelling. American journal of public health 104, 9 (2014), 1606--1614.
[38]
Constance Hammen. 2005. Stress and depression. Annu. Rev. Clin. Psychol. 1 (2005), 293--319.
[39]
Margot Hanley, Apoorv Khandelwal, Hadar Averbuch-Elor, Noah Snavely, and Helen Nissenbaum. 2020. An ethical highlighter for people-centric dataset creation. arXiv preprint arXiv:2011.13583 (2020).
[40]
Emily C Helminen, Melissa L Morton, Qiu Wang, and Joshua C Felver. 2019. A meta-analysis of cortisol reactivity to the Trier Social Stress Test in virtual environments. Psychoneuroendocrinology 110 (2019), 104437.
[41]
Seongsil Heo, Sunyoung Kwon, and Jaekoo Lee. 2021. Stress detection with single PPG sensor by orchestrating multiple denoising and peak-detecting methods. IEEE Access 9 (2021), 47777--47785.
[42]
Katherine A Herborn, James L Graves, Paul Jerem, Neil P Evans, Ruedi Nager, Dominic J McCafferty, and Dorothy EF McKeegan. 2015. Skin temperature reveals the intensity of acute stress. Physiology & behavior 152 (2015), 225--230.
[43]
Sepp Hochreiter and Jürgen Schmidhuber. 1997. Flat minima. Neural computation 9, 1 (1997), 1--42.
[44]
Bonnie D Hodge, Terrence Sanvictores, and Robert T Brodell. 2018. Anatomy, skin sweat glands. (2018).
[45]
Daniel Jiwoong Im, Michael Tao, and Kristin Branson. 2016. An empirical analysis of the optimization of deep network loss surfaces. arXiv preprint arXiv:1612.04010 (2016).
[46]
Talha Iqbal, Andrew J Simpkin, Davood Roshan, Nicola Glynn, John Killilea, Jane Walsh, Gerard Molloy, Sandra Ganly, Hannah Ryman, Eileen Coen, et al. 2022. Stress Monitoring Using Wearable Sensors: A Pilot Study and Stress-Predict Dataset. Sensors 22, 21 (2022), 8135.
[47]
CA James, AJ Richardson, PW Watt, and NS Maxwell. 2014. Reliability and validity of skin temperature measurement by telemetry thermistors and a thermal camera during exercise in the heat. Journal of thermal biology 45 (2014), 141--149.
[48]
Hayeon Jeong, Heepyung Kim, Rihun Kim, Uichin Lee, and Yong Jeong. 2017. Smartwatch wearing behavior analysis: a longitudinal study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 1--31.
[49]
Marcin Jukiewicz, Paweł Łupkowski, Radomir Majchrowski, Joanna Marcinkowska, and Dawid Ratajczyk. 2021. Electrodermal and thermal measurement of users' emotional reaction for a visual stimuli. Case Studies in Thermal Engineering 27 (2021), 101303.
[50]
Kenji Kawaguchi, Leslie Pack Kaelbling, and Yoshua Bengio. 2017. Generalization in deep learning. arXiv preprint arXiv:1710.05468 (2017).
[51]
N Keshan, PV Parimi, and Isabelle Bichindaritz. 2015. Machine learning for stress detection from ECG signals in automobile drivers. In 2015 IEEE International conference on big data (Big Data). IEEE, 2661--2669.
[52]
Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, and Ping Tak Peter Tang. 2016. On large-batch training for deep learning: Generalization gap and sharp minima. arXiv preprint arXiv:1609.04836 (2016).
[53]
Reza Khosrowabadi. 2018. Stress and Perception of Emotional Stimuli: Long-term Stress Rewiring the Brain. Basic and clinical neuroscience 9, 2 (2018), 107.
[54]
Hye-Geum Kim, Eun-Jin Cheon, Dai-Seg Bai, Young Hwan Lee, and Bon-Hoon Koo. 2018. Stress and heart rate variability: a meta-analysis and review of the literature. Psychiatry investigation 15, 3 (2018), 235.
[55]
JongBae Kim. 2019. Pedestrian detection and distance estimation using thermal camera in night time. In 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). IEEE, 463--466.
[56]
Yoonkyoung Kim, Yosep Park, Jinman Kim, and Eui Chul Lee. 2018. Remote heart rate monitoring method using infrared thermal camera. Int. J. Eng. Res. Technol 11, 3 (2018), 493--500.
[57]
Ayca Kirimtat, Ondrej Krejcar, Ali Selamat, and Enrique Herrera-Viedma. 2020. FLIR vs SEEK thermal cameras in biomedicine: comparative diagnosis through infrared thermography. BMC bioinformatics 21, 2 (2020), 1--10.
[58]
Clemens Kirschbaum, Karl-Martin Pirke, and Dirk H Hellhammer. 1993. The 'Trier Social Stress Test'--a tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiology 28, 1-2 (1993), 76--81.
[59]
Alexandra König, Carlos Fernando Crispim Junior, Alexandre Derreumaux, Gregory Bensadoun, Pierre-David Petit, François Bremond, Renaud David, Frans Verhey, Pauline Aalten, and Philippe Robert. 2015. Validation of an automatic video monitoring system for the detection of instrumental activities of daily living in dementia patients. Journal of Alzheimer's Disease 44, 2 (2015), 675--685.
[60]
Ethan Kross, David Gard, Patricia Deldin, Jessica Clifton, and Ozlem Ayduk. 2012. "Asking why" from a distance: Its cognitive and emotional consequences for people with major depressive disorder. Journal of abnormal psychology 121, 3 (2012), 559.
[61]
Alan T Krzywicki, Gary G Berntson, and Barbara L O'Kane. 2014. A non-contact technique for measuring eccrine sweat gland activity using passive thermal imaging. International journal of psychophysiology 94, 1 (2014), 25--34.
[62]
Satish Kumar, ASM Iftekhar, Michael Goebel, Tom Bullock, Mary H MacLean, Michael B Miller, Tyler Santander, Barry Giesbrecht, Scott T Grafton, and BS Manjunath. 2021. StressNet: detecting stress in thermal videos. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 999--1009.
[63]
Angeliki Kylili, Paris A Fokaides, Petros Christou, and Soteris A Kalogirou. 2014. Infrared thermography (IRT) applications for building diagnostics: A review. Applied Energy 134 (2014), 531--549.
[64]
Juwon Lee, Megan Lam, and Caleb Chiu. 2019. Clara: design of a new system for passive sensing of depression, stress and anxiety in the workplace. In Pervasive Computing Paradigms for Mental Health: 9th International Conference, MindCare 2019, Buenos Aires, Argentina, April 23--24, 2019, Proceedings 9. Springer, 12--28.
[65]
Kwangyoung Lee, Hyewon Cho, Kobiljon Toshnazarov, Nematjon Narziev, So Young Rhim, Kyungsik Han, YoungTae Noh, and Hwajung Hong. 2020. Toward future-centric personal informatics: Expecting stressful events and preparing personalized interventions in stress management. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1--13.
[66]
Alessandro Leone, Gabriele Rescio, Pietro Siciliano, Alessandra Papetti, Agnese Brunzini, and Michele Germani. 2020. Multi sensors platform for stress monitoring of workers in smart manufacturing context. In 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 1--5.
[67]
Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer, and Tom Goldstein. 2018. Visualizing the loss landscape of neural nets. Advances in neural information processing systems 31 (2018).
[68]
Yi Li, Rameswar Panda, Yoon Kim, Chun-Fu Richard Chen, Rogerio S Feris, David Cox, and Nuno Vasconcelos. 2022. VALHALLA: Visual Hallucination for Machine Translation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 5216--5226.
[69]
Kevin Lin, Lijuan Wang, Kun Luo, Yinpeng Chen, Zicheng Liu, and Ming-Ting Sun. 2020. Cross-domain complementary learning using pose for multi-person part segmentation. IEEE Transactions on Circuits and Systems for Video Technology 31, 3 (2020), 1066--1078.
[70]
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014. Microsoft coco: Common objects in context. In European conference on computer vision. Springer, 740--755.
[71]
Bing Liu. 2017. Many facets of sentiment analysis. In A practical guide to sentiment analysis. Springer, 11--39.
[72]
Scott M Lundberg and Su-In Lee. 2017. A unified approach to interpreting model predictions. In Advances in neural information processing systems. 4765--4774.
[73]
Dominique Makowski, Tam Pham, Zen J Lau, Jan C Brammer, François Lespinasse, Hung Pham, Christopher Schölzel, and SH Annabel Chen. 2021. NeuroKit2: A Python toolbox for neurophysiological signal processing. Behavior research methods (2021), 1--8.
[74]
Peter Mantello and Manh-Tung Ho. 2023. Emotional AI and the future of wellbeing in the post-pandemic workplace. AI & society (2023), 1--7.
[75]
marcellodebernardi. 2019. loss-landscapes. https://github.com/marcellodebernardi/loss-landscapes.
[76]
Maurizio Mauri, Valentina Magagnin, Pietro Cipresso, Luca Mainardi, Emery N Brown, Sergio Cerutti, Marco Villamira, and Riccardo Barbieri. 2010. Psychophysiological signals associated with affective states. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology. IEEE, 3563--3566.
[77]
Pauline Maurice, Ludivine Allienne, Adrien Malaisé, and Serena Ivaldi. 2018. Ethical and social considerations for the introduction of human-centered technologies at work. In 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO). IEEE, 131--138.
[78]
Mary L McHugh. 2012. Interrater reliability: the kappa statistic. Biochemia medica 22, 3 (2012), 276--282.
[79]
Luca Menghini, Evelyn Gianfranchi, Nicola Cellini, Elisabetta Patron, Mariaelena Tagliabue, and Michela Sarlo. 2019. Stressing the accuracy: Wrist-worn wearable sensor validation over different conditions. Psychophysiology 56, 11 (2019), e13441.
[80]
Arcangelo Merla and Gian Luca Romani. 2007. Thermal signatures of emotional arousal: a functional infrared imaging study. In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 247--249.
[81]
Shekhar Neema, DM Tripathy, Sweta Mukherjee, Anwita Sinha, Senkadhir Vendhan, and Biju Vasudevan. 2021. Infrared thermography in the diagnosis of palmar hyperhidrosis: A diagnostic study. Medical Journal Armed Forces India (2021).
[82]
Thu Nguyen, Khang Tran, and Hung Nguyen. 2018. Towards thermal region of interest for human emotion estimation. In 2018 10th International Conference on Knowledge and Systems Engineering (KSE). IEEE, 152--157.
[83]
Søren Z Nielsen, Rikke Gade, Thomas B Moeslund, and Hans Skov-Petersen. 2014. Taking the temperature of pedestrian movement in public spaces. Transportation Research Procedia 2 (2014), 660--668.
[84]
Simon Ollander, Christelle Godin, Aurélie Campagne, and Sylvie Charbonnier. 2016. A comparison of wearable and stationary sensors for stress detection. In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 004362--004366.
[85]
Ioannis Pavlidis, Norman L Eberhardt, and James A Levine. 2002. Seeing through the face of deception. Nature 415, 6867 (2002), 35--35.
[86]
Ioannis Pavlidis, Panagiotis Tsiamyrtzis, Dvijesh Shastri, Avinash Wesley, Yan Zhou, Peggy Lindner, Pradeep Buddharaju, Rohan Joseph, Anitha Mandapati, Brian Dunkin, et al. 2012. Fast by nature-how stress patterns define human experience and performance in dexterous tasks. Scientific Reports 2, 1 (2012), 305.
[87]
Verónica Pérez-Rosas, Alexis Narvaez, Mihai Burzo, and Rada Mihalcea. 2013. Thermal imaging for affect detection. In Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments. 1--4.
[88]
David Perpetuini, Damiano Formenti, Daniela Cardone, Chiara Filippini, and Arcangelo Merla. 2021. Regions of interest selection and thermal imaging data analysis in sports and exercise science: a narrative review. Physiological Measurement 42, 8 (2021), 08TR01.
[89]
Rosalind W Picard. 2016. Automating the recognition of stress and emotion: From lab to real-world impact. IEEE MultiMedia 23, 3 (2016), 3--7.
[90]
Colin Puri, Leslie Olson, Ioannis Pavlidis, James Levine, and Justin Starren. 2005. StressCam: Non-contact measurement of users' emotional states through thermal imaging. Proceedings of the 2005 ACM Conference on Human Factors in Computing Systems 2, 1725--1728. https://doi.org/10.1145/1056808.1057007
[91]
Siyuan Qiao, Liang-Chieh Chen, and Alan Yuille. 2020. DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution. arXiv preprint arXiv:2006.02334 (2020).
[92]
Jose Ignacio Priego Quesada, Natividad Martínez Guillamón, Rosa Ma Cibrián Ortiz de Anda, Agnes Psikuta, Simon Annaheim, René Michel Rossi, José Miguel Corberán Salvador, Pedro Pérez-Soriano, and Rosario Salvador Palmer. 2015. Effect of perspiration on skin temperature measurements by infrared thermography and contact thermometry during aerobic cycling. Infrared Physics & Technology 72 (2015), 68--76.
[93]
Vandana Rajan, Alessio Brutti, and Andrea Cavallaro. 2021. Robust Latent Representations Via Cross-Modal Translation and Alignment. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 4315--4319.
[94]
Edna Maria Vissoci Reiche, Sandra Odebrecht Vargas Nunes, and Helena Kaminami Morimoto. 2004. Stress, depression, the immune system, and cancer. The lancet oncology 5, 10 (2004), 617--625.
[95]
Adrian Rosebrock. 2016. Intersection over Union (IoU) for object detection. Diambil kembali dari PYImageSearch: https://www.pyimagesearch. com/2016/11/07/intersection-over-union-iou-for-object-detection (2016).
[96]
Nazreen Rusli, Shahrul Naim Sidek, Hazlina Md Yusof, Nor Izzati Ishak, Madihah Khalid, and Ahmad Aidil Arafat Dzulkarnain. 2020. Implementation of wavelet analysis on thermal images for affective states recognition of children with autism spectrum disorder. IEEE Access 8 (2020), 120818--120834.
[97]
SafelyYou. 2022. Transform care delivery with world-leading AI + clinical expertise. Retrieved July, 2023 from https://www.safely-you.com/
[98]
Asif Salekin, Hongning Wang, Kristine Williams, and John Stankovic. 2017. Dave: detecting agitated vocal events. In 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). IEEE, 157--166.
[99]
Zhanna Sarsenbayeva, Niels van Berkel, Danula Hettiachchi, Weiwei Jiang, Tilman Dingler, Eduardo Velloso, Vassilis Kostakos, and Jorge Goncalves. 2019. Measuring the effects of stress on mobile interaction. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 1 (2019), 1--18.
[100]
Alexandre Schaefer, Frédéric Nils, Xavier Sanchez, and Pierre Philippot. 2010. Assessing the effectiveness of a large database of emotion-eliciting films: A new tool for emotion researchers. Cognition and emotion 24, 7 (2010), 1153--1172.
[101]
ProTech Security. 2023. How Thermal Cameras for Businesses Can Keep Employees and Customers Safe. Retrieved July, 2023 from https://protechsecurity.com/how-thermal-cameras-for-businesses-can-keep-employees-and-customers-safe/
[102]
Cornelia Setz, Bert Arnrich, Johannes Schumm, Roberto La Marca, Gerhard Tröster, and Ulrike Ehlert. 2009. Discriminating stress from cognitive load using a wearable EDA device. IEEE Transactions on information technology in biomedicine 14, 2 (2009), 410--417.
[103]
Lloyd S Shapley. 1953. Stochastic games. Proceedings of the national academy of sciences 39, 10 (1953), 1095--1100.
[104]
Harshit Sharma, Yi Xiao, Victoria Tumanova, and Asif Salekin. 2022. Psychophysiological Arousal in Young Children Who Stutter: An Interpretable AI Approach. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, 3 (2022), 1--32.
[105]
Ben Shneiderman. 2020. Bridging the gap between ethics and practice: guidelines for reliable, safe, and trustworthy human-centered AI systems. ACM Transactions on Interactive Intelligent Systems (TiiS) 10, 4 (2020), 1--31.
[106]
Saurabh Sonkusare, David Ahmedt-Aristizabal, Matthew J Aburn, Vinh Thai Nguyen, Tianji Pang, Sascha Frydman, Simon Denman, Clinton Fookes, Michael Breakspear, and Christine C Guo. 2019. Detecting changes in facial temperature induced by a sudden auditory stimulus based on deep learning-assisted face tracking. Scientific reports 9, 1 (2019), 4729.
[107]
Nattapong Thammasan, Koichi Moriyama, Ken-ichi Fukui, and Masayuki Numao. 2017. Familiarity effects in EEG-based emotion recognition. Brain informatics 4 (2017), 39--50.
[108]
Victoria Tumanova and Nicole Backes. 2019. Autonomic nervous system response to speech production in stuttering and normally fluent preschool-age children. Journal of Speech, Language, and Hearing Research 62, 11 (2019), 4030--4044.
[109]
Marieke van Dooren, Joris H Janssen, et al. 2012. Emotional sweating across the body: Comparing 16 different skin conductance measurement locations. Physiology & behavior 106, 2 (2012), 298--304.
[110]
Maarten Vandersteegen. 2018. SEEK thermal compact camera driver supporting the thermal Compact, thermal CompactXR and and thermal CompactPRO. https://github.com/maartenvds/libseek-thermal
[111]
Wilhelm Von Rosenberg, Theerasak Chanwimalueang, Tricia Adjei, Usman Jaffer, Valentin Goverdovsky, and Danilo P Mandic. 2017. Resolving ambiguities in the LF/HF ratio: LF-HF scatter plots for the categorization of mental and physical stress from HRV. Frontiers in physiology 8 (2017), 360.
[112]
Rahee Walambe, Pranav Nayak, Ashmit Bhardwaj, and Ketan Kotecha. 2021. Employing multimodal machine learning for stress detection. Journal of Healthcare Engineering 2021 (2021), 1--12.
[113]
Qianqian Wang, Zhiqiang Tao, Wei Xia, Quanxue Gao, Xiaochun Cao, and Licheng Jiao. 2022. Adversarial multiview clustering networks with adaptive fusion. IEEE transactions on neural networks and learning systems (2022).
[114]
Zhikang Wang, Feng Zhu, Shixiang Tang, Rui Zhao, Lihuo He, and Jiangning Song. 2022. Feature erasing and diffusion network for occluded person re-identification. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 4754--4763.
[115]
Kay Wright and Swaran Singh. 2022. Reducing falls in dementia inpatients using vision-based technology. Journal of Patient Safety 18, 3 (2022), 177.
[116]
Jiacheng Yang. 2022. Enabling Privacy-Preserving Model Personalization via On-Device Incremental Training. Ph.D. Dissertation. University of Toronto (Canada).
[117]
Bin Yu, Mathias Funk, Jun Hu, Qi Wang, and Loe Feijs. 2018. Biofeedback for everyday stress management: A systematic review. Frontiers in ICT 5 (2018), 23.
[118]
Huijun Zhang, Ling Feng, Ningyun Li, Zhanyu Jin, and Lei Cao. 2020. Video-Based Stress Detection through Deep Learning. Sensors 20, 19 (2020), 5552.
[119]
Jing Zhang, Hang Yin, Jiayu Zhang, Gang Yang, Jing Qin, and Ling He. 2022. Real-time mental stress detection using multimodality expressions with a deep learning framework. Frontiers in Neuroscience 16 (2022).
[120]
Zhuo Zheng, Ailong Ma, Liangpei Zhang, and Yanfei Zhong. 2021. Deep multisensor learning for missing-modality all-weather mapping. ISPRS Journal of Photogrammetry and Remote Sensing 174 (2021), 254--264.
[121]
Kaiyang Zhou and Tao Xiang. 2019. Torchreid: A library for deep learning person re-identification in pytorch. arXiv preprint arXiv:1910.10093 (2019).
[122]
Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, and Tao Xiang. 2019. Omni-scale feature learning for person re-identification. In Proceedings of the IEEE/CVF international conference on computer vision. 3702--3712.
[123]
Lili Zhu, Pai Chet Ng, Yuanhao Yu, Yang Wang, Petros Spachos, Dimitrios Hatzinakos, and Konstantinos N Plataniotis. 2022. Feasibility study of stress detection with machine learning through eda from wearable devices. In ICC 2022-IEEE International Conference on Communications. IEEE, 4800--4805.
[124]
The Guardian Zoë Corbyn. 2021. The future of elder care is here -- and it's artificial intelligence. Retrieved July, 2023 from https://www.theguardian.com/us-news/2021/jun/03/elder-care-artificial-intelligence-software

Cited By

View all
  • (2024)The challenge of stress induction in serious games, considering gameplayProceedings of the 26th Symposium on Virtual and Augmented Reality10.1145/3691573.3691598(177-184)Online publication date: 30-Sep-2024
  • (2024)Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided MaskProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671708(3551-3562)Online publication date: 25-Aug-2024
  • (2024)Contextual Distillation Model for Diversified RecommendationProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671514(5307-5316)Online publication date: 25-Aug-2024
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 7, Issue 4
December 2023
1613 pages
EISSN:2474-9567
DOI:10.1145/3640795
Issue’s Table of Contents
This work is licensed under a Creative Commons Attribution-NonCommercial International 4.0 License.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 January 2024
Published in IMWUT Volume 7, Issue 4

Check for updates

Author Tags

  1. Affective Computing
  2. Co-teaching
  3. Contactless sensing
  4. Health Sensing
  5. Machine Learning
  6. Multimodality
  7. Stress detection
  8. Thermal sensing

Qualifiers

  • Research-article
  • Research
  • Refereed

Funding Sources

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)728
  • Downloads (Last 6 weeks)110
Reflects downloads up to 09 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2024)The challenge of stress induction in serious games, considering gameplayProceedings of the 26th Symposium on Virtual and Augmented Reality10.1145/3691573.3691598(177-184)Online publication date: 30-Sep-2024
  • (2024)Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided MaskProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671708(3551-3562)Online publication date: 25-Aug-2024
  • (2024)Contextual Distillation Model for Diversified RecommendationProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671514(5307-5316)Online publication date: 25-Aug-2024
  • (2024)EEG-based signature recognition using visual stimulation of RGB colors2024 IEEE VII Congreso Internacional en Inteligencia Ambiental, Ingeniería de Software y Salud Electrónica y Móvil (AmITIC)10.1109/AmITIC62658.2024.10747627(1-6)Online publication date: 25-Sep-2024

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Full Access

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media