Published on in Vol 5, No 3 (2018): Jul-Sept

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10153, first published .
Emotion Recognition Using Smart Watch Sensor Data: Mixed-Design Study

Emotion Recognition Using Smart Watch Sensor Data: Mixed-Design Study

Emotion Recognition Using Smart Watch Sensor Data: Mixed-Design Study

Journals

  1. Day J, Freiberg K, Hayes A, Homel R. Towards Scalable, Integrative Assessment of Children’s Self-Regulatory Capabilities: New Applications of Digital Technology. Clinical Child and Family Psychology Review 2019;22(1):90 View
  2. Cho A, Lee H, Jo Y, Whang M. Embodied Emotion Recognition Based on Life-Logging. Sensors 2019;19(23):5308 View
  3. Bickman L. Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health. Administration and Policy in Mental Health and Mental Health Services Research 2020;47(5):795 View
  4. Geangu E, Vuong Q. Look up to the body: An eye-tracking investigation of 7-months-old infants’ visual exploration of emotional body expressions. Infant Behavior and Development 2020;60:101473 View
  5. Narziev N, Goh H, Toshnazarov K, Lee S, Chung K, Noh Y. STDD: Short-Term Depression Detection with Passive Sensing. Sensors 2020;20(5):1396 View
  6. Gasparini F, Giltri M, Bandini S. Discriminating affective state intensity using physiological responses. Multimedia Tools and Applications 2020;79(47-48):35845 View
  7. Park S, Constantinides M, Aiello L, Quercia D, Van Gent P. WellBeat: A Framework for Tracking Daily Well-Being Using Smartwatches. IEEE Internet Computing 2020;24(5):10 View
  8. Hilty D, Armstrong C, Luxton D, Gentry M, Krupinski E. A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions. Journal of Technology in Behavioral Science 2021;6(2):278 View
  9. Xu L, Zheng Y, Xu D, Xu L. Predicting the Preference for Sad Music: The Role of Gender, Personality, and Audio Features. IEEE Access 2021;9:92952 View
  10. Chakrabarti S, Biswas N, Jones L, Kesari S, Ashili S. Smart Consumer Wearables as Digital Diagnostic Tools: A Review. Diagnostics 2022;12(9):2110 View
  11. Qirtas M, Zafeiridi E, Pesch D, White E. Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping Review. JMIR mHealth and uHealth 2022;10(4):e34638 View
  12. Chung J, Brakey H, Reeder B, Myers O, Demiris G. Community‐dwelling older adults' acceptance of smartwatches for health and location tracking. International Journal of Older People Nursing 2023;18(1) View
  13. Jemioło P, Storman D, Mamica M, Szymkowski M, Żabicka W, Wojtaszek-Główka M, Ligęza A. Datasets for Automated Affect and Emotion Recognition from Cardiovascular Signals Using Artificial Intelligence— A Systematic Review. Sensors 2022;22(7):2538 View
  14. Mughal F, Raffe W, Stubbs P, Kneebone I, Garcia J. Fitbits for Monitoring Depressive Symptoms in Older Aged Persons: Qualitative Feasibility Study. JMIR Formative Research 2022;6(11):e33952 View
  15. Veeranki Y, Kumar H, Ganapathy N, Natarajan B, Swaminathan R. A Systematic Review of Sensing and Differentiating Dichotomous Emotional States Using Audio-Visual Stimuli. IEEE Access 2021;9:124434 View
  16. Xu L, Wang J, Xu D, Xu L. Integrating Individual Factors to Construct Recognition Models of Consumer Fraud Victimization. International Journal of Environmental Research and Public Health 2022;19(1):461 View
  17. Deligianni F, Guo Y, Yang G. From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology. IEEE Journal of Biomedical and Health Informatics 2019;23(6):2302 View
  18. Khanshan A, Van Gorp P, Nuijten R, Markopoulos P. Assessing the Influence of Physical Activity Upon the Experience Sampling Response Rate on Wrist-Worn Devices. International Journal of Environmental Research and Public Health 2021;18(20):10593 View
  19. Bocu R, Bocu D, Iavich M. An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors. Sensors 2022;23(1):294 View
  20. Jianwattanapaisarn N, Sumi K, Utsumi A, Khamsemanan N, Nattee C. Emotional characteristic analysis of human gait while real-time movie viewing. Frontiers in Artificial Intelligence 2022;5 View
  21. Delgado-Santos P, Stragapede G, Tolosana R, Guest R, Deravi F, Vera-Rodriguez R. A Survey of Privacy Vulnerabilities of Mobile Device Sensors. ACM Computing Surveys 2022;54(11s):1 View
  22. Ahmed N, Aghbari Z, Girija S. A systematic survey on multimodal emotion recognition using learning algorithms. Intelligent Systems with Applications 2023;17:200171 View
  23. Li Y, Yu L, Liao J, Su G, Ammarah H, Liu L, Wang S. A single smartwatch-based segmentation approach in human activity recognition. Pervasive and Mobile Computing 2022;83:101600 View
  24. Anderson L, Hall L, Crosby R, Crow S, Berg K, Durkin N, Engel S, Peterson C. “Feeling fat,” disgust, guilt, and shame: Preliminary evaluation of a mediation model of binge-eating in adults with higher-weight bodies. Body Image 2022;42:32 View
  25. Yokoyama K, Hayashi E, Ito H, Kawahara Y. Estimation of heart rate variability from heart rate measured with wristwatch‐type heart rate monitor. Electronics and Communications in Japan 2022;105(2) View
  26. Yokoyama K, Hayashi E, Ito H, Kawahara Y. Estimation of Heart Rate Variability from Heartrate Measured with Wristwatch-Type Heartrate Monitor. IEEJ Transactions on Electronics, Information and Systems 2022;142(1):46 View
  27. Huhn S, Axt M, Gunga H, Maggioni M, Munga S, Obor D, Sié A, Boudo V, Bunker A, Sauerborn R, Bärnighausen T, Barteit S. The Impact of Wearable Technologies in Health Research: Scoping Review. JMIR mHealth and uHealth 2022;10(1):e34384 View
  28. Wen X, Huang Z, Sun Z, Xu L. What a deep song: The role of music features in perceived depth. PsyCh Journal 2022;11(5):673 View
  29. Roemmich K, Andalibi N. Data Subjects' Conceptualizations of and Attitudes Toward Automatic Emotion Recognition-Enabled Wellbeing Interventions on Social Media. Proceedings of the ACM on Human-Computer Interaction 2021;5(CSCW2):1 View
  30. Ab. Aziz N, K. T, Ismail S, Hasnul M, Ab. Aziz K, Ibrahim S, Abd. Aziz A, Raja J. Asian Affective and Emotional State (A2ES) Dataset of ECG and PPG for Affective Computing Research. Algorithms 2023;16(3):130 View
  31. Leppich D, Bieber C, Proschek K, Harms P, Schubert U. DUX: a dataset of user interactions and user emotions. i-com 2023;22(2):101 View
  32. Saganowski S, Perz B, Polak A, Kazienko P. Emotion Recognition for Everyday Life Using Physiological Signals From Wearables: A Systematic Literature Review. IEEE Transactions on Affective Computing 2023;14(3):1876 View
  33. Olesen K, Lønfeldt N, Das S, Pagsberg A, Clemmensen L. Predicting Obsessive-Compulsive Disorder Events in Children and Adolescents in the Wild Using a Wearable Biosensor (Wrist Angel): Protocol for the Analysis Plan of a Nonrandomized Pilot Study. JMIR Research Protocols 2023;12:e48571 View
  34. Gohumpu J, Xue M, Bao Y. Emotion recognition with multi-modal peripheral physiological signals. Frontiers in Computer Science 2023;5 View
  35. Xu S, Fang J, Hu X, Ngai E, Wang W, Guo Y, Leung V. Emotion Recognition From Gait Analyses: Current Research and Future Directions. IEEE Transactions on Computational Social Systems 2024;11(1):363 View
  36. Baroudi L, Barton K, Cain S, Shorter K. Classification of human walking context using a single-point accelerometer. Scientific Reports 2024;14(1) View
  37. Deguchi N, Osuka Y, Kojima N, Motokawa K, Iwasaki M, Inagaki H, Miyamae F, Okamura T, Hirano H, Awata S, Sasai H. Sex-specific factors associated with acceptance of smartwatches among urban older adults: the Itabashi longitudinal study on aging. Frontiers in Public Health 2024;12 View
  38. Felber N, Alavi H, Mugellini E, Wangmo T. The smart home, a true home? How new technologies disrupt the experience of home for older persons. Universal Access in the Information Society 2024 View
  39. Gebhardt C, Brombach A, Luong T, Hilliges O, Holz C. Detecting Users' Emotional States during Passive Social Media Use. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2024;8(2):1 View
  40. Kaur H, Rani V, Kumar M. Human activity recognition: A comprehensive review. Expert Systems 2024;41(11) View
  41. Halabi R, Gonzalez-Torres C, MacLean S, Husain M, Pratap A, Alda M, Mulsant B, Ortiz A. A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder. IEEE Journal of Biomedical and Health Informatics 2024;28(8):4903 View
  42. Oh K, Ko J, Jin N, Han S, Yoon C, Shin J, Ko M. Understanding Morning Emotions by Analyzing Daily Wake-Up Alarm Usage: A Longitudinal Observational Study (Preprint). JMIR Human Factors 2023 View

Books/Policy Documents

  1. Martinho D, Carneiro J, Novais P, Neves J, Corchado J, Marreiros G. Progress in Artificial Intelligence. View
  2. Zhuang Y, Lin L, Tong R, Liu J, Iwamoto Y, Chen Y. Computer Vision – ACCV 2020 Workshops. View
  3. Cipriano M, Costagliola G, De Rosa M, Fuccella V, Shevchenko S. Innovation in Medicine and Healthcare. View
  4. Jianwattanapaisarn N, Sumi K, Utsumi A. Intelligent Video Surveillance - New Perspectives. View
  5. Bocu R, Bocu D. Advanced Information Networking and Applications. View