Olympia Simantiraki , Alexandros Roniotis , and Manolis Tsiknakis. 2022/1. “Review on Psychological Stress Detection Using Biosignals.” IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 13 (1): 440–60. [7] Alberdi, Ane, 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 (February): 49–75. [8] Ԭాকޗ. 2022. “ʮ͋ͳͨରΛָ͠ΜͰ͍·͔͢ʁʯ ʔରʹ͓͚Δ໘ঢ়ଶਪఆͷ՝ͱలʔ.” [9] Pramod Bobade, Vani M. 2020. “Stress Detection with Machine Learning and Deep Learning Using Multimodal Physiological Data.” 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA), September, 51–57. [10] Healey, J. A., and R. W. Picard. 2005. “Detecting Stress during Real-World Driving Tasks Using Physiological Sensors.” IEEE Transactions on Intelligent Transportation Systems 6 (2): 156–66.
ྨͷܭࢉίετ w ܭଌɿ୯Ұηϯαʔ w ੳɿٸੑετϨεঢ়ଶྨͷͨΊͷॲཧνΣʔϯΛఏҊ w ϊΠζʹରͯ͠ؤৎʹઃܭ w ଟΫϥεྨΛ࣮ Greco, Alberto, Gaetano Valenza, Jesus Lazaro, Jorge Mario Garzon-Rey, Jordi Aguilo, Concepcion de la Camara, Raquel Bailon, and Enzo Pasquale Scilingo. 2023. “Acute Stress State Classification Based on Electrodermal Activity Modeling.” IEEE Transactions on Affective Computing 14 (1): 788–99. &%"ʢൽෘిؾ׆ಈʣ৴߸͕DWY&%"ʹΑͬͯॲཧ͓Αͼղ͞Εɺ ͦͷ݁ՌಘΒΕͨ৴߸͔Βಛநग़͕ߦΘΕΔ
and Kristof Van Laerhoven. 2018. “Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection.” In Proceedings of the 20th ACM International Conference on Multimodal Interaction, 400–408. ICMI ’18. New York, NY, USA: Association for Computing Machinery. w ෳͷੜཧֶతԠΛܭଌ ݂ӷ༰ੵ຺ɺ৺ిਤɺൽෘిؾ׆ಈ ےిਤɺݺٵɺମԹɺࡾ࣠Ճܭ w ܭଌػث 3FTQJ#"/1SPGFTTJPOBM &NQBUJDB& w σʔληοτʮ8&4"%ʯͱͯ͠ެ։ w ຊݚڀͷΞϓϩʔν w 8&4"%ʹؚ·Ε͍ͯͳ͍Ԡܭଌ͍ͨ͠ w ݕূʹ8&4"%ͷσʔλΛ༻͍Δ͜ͱݕ౼ σʔληοτΛެ։͠ɺ͜ͷσʔληοτΛ׆༻ͨ͠ݚڀ͕ల։͞Ε͍ͯΔ Ҿ༻ɿIUUQTVCJDPNQFUJVOJTJFHFOEFIPNFEBUBTFUTJDNJ
of mental concentration and acute psychosocial stress on cervical muscle activity and posture, 2013, Journal of Electromyography and Kinesiology, volume23 issue5, pp1082-1089 ʢ্ʣԻ৴߸ͷΤωϧΪʔϨϕϧ ʢԼʣൽෘిҐԠʢ(43ʣͷڻ͖Ԡͷྫ w ԻͱൽෘిྲྀԠ৴߸ʢ(43ʣΛ༻ͨ͠ྨλεΫ w ԻσʔλൃಛੑΛөɺ(43ੜཧֶతԠ w ԾઆɿΈ߹ΘͤΔͱɺΑΓ৴པੑͷߴ͍ετϨεݕग़ʁ w ݁Ռɿ୯ମͰͷྨλεΫޭɺΈ߹Θࣦͤഊ w Իͱ(43ͷಛΛ༻͍ͨྨثɺਫ਼Λେ෯ʹվળͰ͖ͣ w ຊݚڀͷΞϓϩʔν w σʔλੳٕज़ͷ্ w ηϯαʔٕज़ͷվળ
ඪɿˋͷඃݧऀʹରͯ͠ˋΛ͑Δ w ੜମ৴߸͕σόΠεʹΒͳ͍ඃݧऀग़ͯ͘ΔͨΊɺશһෆՄೳ w ࠷Ͱˋͷ༗ҙࠩΛ͑Δ͜ͱ͕݅ w ൃలɿ·ͣܭଌਫ਼ͷ্Λࢦ͢ w ࣮ݧൣғͷ֦େɿҟͳΔ݈߁ঢ়ଶͷඃݧऀɺҟͳΔڥ݅ԼͰͷσʔλऩू w σόΠεͷ։ൃɿݚڀڠྗΛ௨ͯ͡ɺࢦඪͱͳΔԠΛશͯܭଌͯ͠σʔλΛੳͰ͖ΔσόΠεͷ։ൃ
ϦΞϧλΠϜॲཧͷࠔ͞ w ํ๏ཱ͕֬ͯ͠ɺৗੜ׆Ͱɺෳͷ৴߸ΛϦΞϧλΠϜͰॲཧ͠ੳ͢Δқͷߴ͞ w ணͷෆศ͞ͱίετ w ෳͷηϯαʔʹΑΓணͷෆศ͕͞૿͠ɺඃݧऀͷߦಈΛ͛Δ Greco, Alberto, Gaetano Valenza, Jesus Lazaro, Jorge Mario Garzon-Rey, Jordi Aguilo, Concepcion de la Camara, Raquel Bailon, and Enzo Pasquale Scilingo. 2023. “Acute Stress State Classification Based on Electrodermal Activity Modeling.” IEEE Transactions on Affective Computing 14 (1): 788–99.
ˠ؊ଁʹάϧίʔεΛ์ग़ͤ͞ɺΤωϧΪʔΛڙڅ w ˠଉΕɺ৺ഥͷ૿Ճɺےͷۓுɺ݂ѹͷ্ঢɺײ֮ͷဏਐΛҾ͖ى͜͢ w ྨʢ&QFMFUBMʣ w ٸੑ৺ཧతετϨεɿ௨ৗ͔Β࣌ؒʹΘͨͬͯൃੜ w ຫੑ৺ཧతετϨεɿظؒʹΘͨͬͯൃੜɻظؒඇৗʹ෯͍ Selye H., 1950, “Stress and the General Adaptation Syndrome,” British Medical Journal, 1 (4667): 1383–92. Epel, Elissa S., Alexandra D. Crosswell, Stefanie E. Mayer, Aric A. Prather, George M. Slavich, Eli Puterman, and Wendy Berry Mendes. 2018. “More than a Feeling: A Unified View of Stress Measurement for Population ɹ ɹScience.” Frontiers in Neuroendocrinology 49 (April): 146–69. Smirthy M, Dhanushree M, Ashisha G R. 2023. “Investigation of Machine Learning Techniques and Sensing Devices for Mental Stress Detection.”
fitbit Inc. “fitbit”. fitbit,. https://www.fitbit.com/global/jp/technology/stress, ʢࢀর 2024-01-02ʣ Gagnon, Joel, Michelle Khau, Léandre Lavoie-Hudon, François Vachon, Vicky Drapeau, and Sébastien Tremblay. 2022. “Comparing a Fitbit Wearable to an Electrocardiogram Gold Standard as a Measure of Heart Rate Under Psychological Stress: A Validation Study.” JMIR Formative Research 6 (12): e37885.
w ྫɿੜཧֶతԠͱ৺ཧֶతԠ w ྆ऀʮ͠͠૬ؔ͠ͳ͍͔ɺऑ͘૬ؔ͢Δʯ w ͲͪΒ͕ਖ਼͍͔͠ˠͲͪΒʮਖ਼͍͠ʯͱߟ͑Δͷ͕ଥ w ޓ͍ʹิతͳใΛఏڙ͍ͯ͠Δ w ετϨεͷશମ૾ΛΑΓਂ͘ཧղ͢ΔͨΊʹɺ྆ऀΛߟྀʹೖΕΔ͜ͱ͕ॏཁ Giorgos Giannakakis , Dimitris Grigoriadis, Katerina Giannakaki , Olympia Simantiraki , Alexandros Roniotis , and Manolis Tsiknakis. 2022/1. “Review on Psychological Stress Detection Using Biosignals.” IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 13 (1): 440–60 Hellhammer, D. H., Stone, A. A., Hellhammer, J., & Broderick, J. 2010. “Measuring Stress.” 2010.
w ˠରΤʔδΣϯτ͔ͩΒʁࢀՃऀ͕ΤʔδΣϯτʹૣ͘׳Ε͔ͨΒʁ w ৗੜ׆ʹ͓͚ΔετϨεΛҾ͖ى͜͢ձΛݕग़͠ɺετϨεԠͱͷ૬ؔΛੳ w ετϨεձΛݕग़͢ΔετϨεձͷ۩ମతͳ༰͕໌Β͔ʹ͞Εͣ w ຊݚڀͰͳͥձλεΫΛબ͢Δͷ͔ʁ w εϐʔνλεΫͱҧ͍ɺϦΞϧλΠϜͷ૬ޓ࡞༻͕͋ΔɻײతͳԠ͕ෳࡶͰมಈ͍͢͠ɻ w ˠετϨεԠͷΑΓৄࡉͳཧղΛͨΒ͢Մೳੑ͕͋Δ ҰൠతͳετϨεςετͷ༰ͱɺձλεΫΛબΜͩཧ༝ Datar, Shreya, Libby Ferland, Esther Foo, Michael Kotlyar, Brad Holschuh, Maria Gini, Martin Michalowski, and Serguei Pakhomov. 2022. “Measuring Physiological Markers of Stress during Conversational Agent Interactions.” In AI for Disease Surveillance and Pandemic Intelligence, 247–65. Studies in Computational Intelligence. Cham: Springer International Publishing. Bari, Rummana, Md Mahbubur Rahman, Nazir Saleheen, Megan Battles Parsons, Eugene H. Buder, and Santosh Kumar. 2020. “Automated Detection of Stressful Conversations Using Wearable Physiological and Inertial Sensors.” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4 (4).
successor”. Emphatic. https://www.empatica.com/research/e4/, ʢࢀর 2024-01-02ʣ Tamaki, Emi, Satoshi Hosono, and Ken Iwasaki. 2019. “FirstVR: A Muscle Deformation Sensors Array Device to Detect Finger Gestures and Noise Reduction Case.” In Proceedings of the 2019 2nd International Conference on Electronics, Communications and Control Engineering, 21–24. ICECC ’19. New York, NY, USA: Association for Computing Machinery. Schmidt, Philip, Attila Reiss, Robert Duerichen, Claus Marberger, and Kristof Van Laerhoven. 2018. “Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection.” In Proceedings of the 20th ACM International Conference on Multimodal Interaction, 400–408. ICMI ’18. New York, NY, USA: Association for Computing Machinery. ʲ&NQBUJDB&ʳ w खटʹண w ݂ӷྔ຺ഥηϯαʔɺࡾ࣠Ճηϯαʔɺ ൽෘిؾ৴߸ηϯαʔɺ֎ઢαʔϞύΠϧ w ˠൽෘిؾ׆ಈɺ৺ഥɺ݂ӷͷྲྀΕɺൽ ෘԹ ʲ'JSTU73ʳʢ5BNBLJʣ w ;͘Β͗ͳͲʹணՄೳ w ےऩॖ࣌ʹےுྗΛܭଌ w ˠখنͳےͷಈ͖ w ૐےʹணՄೳ͔Λࢼ͢ ʲ3FTQJ#"/1SPGFTTJPOBMʳ w ڳʹண w Ճܭͱݺٵηϯαʔʴ࠷େͭͷ ՃϞμϦςΟͷϋϒͱͯ͠ػೳ w ˠݺٵʴےͷిؾ৴߸ʢՃʣ
“Detecting Stress during Real-World Driving Tasks Using Physiological Sensors.” IEEE Transactions on Intelligent Transportation Systems 6 (2): 156–66. Schmidt, Philip, Attila Reiss, Robert Duerichen, Claus Marberger, and Kristof Van Laerhoven. 2018. “Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection.” In Proceedings of the 20th ACM International Conference on Multimodal Interaction, 400–408. ICMI ’18. New York, NY, USA: Association for Computing Machinery. w άϥϯυτΡϧʔεͷઃఆͱͯ͠ඃݧऀͷओ؍తͳධՁΛ༻͍͍ͯΔݚڀଟ͍ w ӡసதͷࣗͷετϨεΛओ؍తʹධՁ͢ΔΞϯέʔτʢ)FBMFZ+"ʣ w ϑϦʔεέʔϧධՁʢετϨεΛʙͷεέʔϧͰධՁʣɺڧ੍ϥϯΩϯάධՁʢʙͷεέʔϧͰϥϯΫ͚ʣ w ϙδςΟϒɾΞϯυɾωΨςΟϒɾΞϑΣΫτɾεέδϡʔϧʢ1"/"4ʣ w ͷϙδςΟϒ߲ͱͷωΨςΟϒ߲͔ΒͳΔΞϯέʔτ w γϣʔτɾετϨεɾεςʔτɾΫΤενϣφϦʔʢ4442ʣ w ඃݧऀ͕ͲͷλΠϓͷετϨεʢ৺ɺؔ༩ɺۤʣΛ࠷ڧ͘ײ͍ͯ͡Δ͔Λಛఆ w ຊݚڀͰͷΞϯέʔτɿ)FBMFZ+"ʢʣͷΞϯέʔτͱɺ4442Λ౿ऻ w ٖ໘ͷ߹ϙδςΟϒΑΓωΨςΟϒΛײ͡ΔՄೳੑ͕ߴ͍ w ओ؍తʹײͨ͡ετϨελΠϓʹΑͬͯมԽΛࣔ͢Ԡ͕ҟͳΔͷ͔Λݕূ͍ͨ͠ w ຊݚڀʹ͓͍ͯɺΞϯέʔτʹө͞Εͳ͍ετϨεΛͲ͏ߟ͑Δ͔ w Ξϯέʔτʹద߹͠ͳ͍݁Ռ͕͋Δ߹ɺҟৗͷੳΛݕ౼͢Δ w ΠϯλϏϡʔͷΑ͏ͳ࣭తௐࠪΛऔΓೖΕɺݸʑͷετϨεମݧΛΑΓৄࡉʹଊ͑Δ
ྨʹڧ͘ɺগྔͷσʔλͰߴ͍ύϑΥʔϚϯεΛൃش w ετϨεݕग़ʹ͓͍ͯɺଞͷػցֶशΞϧΰϦζϜΑΓಛʹ༗ޮ w ਂֶशɿ"//ʢਓχϡʔϥϧωοτϫʔΫʣ w ਓؒͷͷػೳΛ฿͠ɺσʔλॲཧͱύλʔϯೝࣝʹ༻͞ΕΔΞϧΰϦζϜ w େنͳσʔληοτ͕ඞཁ͕ͩɺసҠֶशʹΑͬͯখنσʔληοτͰੳՄೳ w ͳͥྨλεΫͱͯ͠ॲཧ͢Δͷ͔ʁ w ετϨεܭଌɺجຊతʹճؼλεΫͰͳ͘ྨλεΫͱͯ͠ॲཧ͞ΕΔέʔε͕ଟ͍ w ࢦඪ୯Ґఆ·͍ͬͯͳ͍ஈ֊ͳͷͰɺ࿈ଓͰͷଌఆΑΓɺਖ਼֬ͳྨΛ༏ઌ Pramod Bobade, Vani M. 2020. “Stress Detection with Machine Learning and Deep Learning Using Multimodal Physiological Data.” 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA), September, 51–57.
Amir Zadeh, Yao Chong Lim, and Louis-Philippe Morency. 2018. “OpenFace 2.0: Facial Behavior Analysis Toolkit.” In 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), 59–66. IEEE. Devlin, Jacob, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. “BERT: Pre-Training of Deep Bidirectional Transformers for Language Understanding.” arXiv [cs.CL]. arXiv. http://arxiv.org/abs/1810.04805. Eyben, Florian, Martin Wöllmer, and Björn Schuller. 2010. “Opensmile: The Munich Versatile and Fast Open-Source Audio Feature Extractor.” In Proceedings of the 18th ACM International Conference on Multimedia, 1459–62. MM ’10. New York, NY, USA: Association for Computing Machinery. w ൃ༰ɿ#&35 w ݴޠཧղͷͨΊͷਂํτϥ ϯεϑΥʔϚʔϞσϧ w දɿ0QFO'BDF w إಈ࡞ੳΞϧΰϦζϜΛ࣮͢ ΔϑϨʔϜϫʔΫ
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