Publications citing the E3 wristband:

Updated:

Okruszek, Ł., Dolan, K., Lawrence, M., & Cella, M. (2016). The beat of social cognition: Exploring the role of heart rate variability as marker of mentalizing abilities. Social Neuroscience, 1-5. http://www.tandfonline.com/doi/abs/10.1080/17470919.2016.1244113

 

Winslow, B. D., Chadderdon, G. L., Dechmerowski, S. J., Jones, D. L., Kalkstein, S., Greene, J. L., & Gehrman, P. (2016). Development and clinical evaluation of an mhealth application for stress Management. Frontiers in Psychiatry, 7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4960497/

 

Schulz, E., Neumann, C., & Middeke, M. (2016). [PP. 08.14] EUSTAR: European Society of Hypertension Telemedicine in Arterial Hypertension Register-Design and Rationale. Journal of Hypertension, 34, e164. http://journals.lww.com/jhypertension/Abstract/2016/09002/_PP_08_14__EUSTAR___EUROPEAN_SOCIETY_OF.461.aspx

 

Gjoreski, M., Gjoreski, H., Luštrek, M., & Gams, M. (2016). How accurately can your wrist device recognize daily activities and detect falls?. Sensors, 16(6), 800. http://www.mdpi.com/1424-8220/16/6/800/htm

 

Miranda, D., Favela, J., Ibarra, C., & Cruz, N. (2016). Naturalistic Enactment to Elicit and Recognize Caregiver State Anxiety. Journal of medical systems, 40(9), 192. http://link.springer.com/article/10.1007/s10916-016-0551-0

 

Adams, Z. W., McClure, E. A., Gray, K. M., Danielson, C. K., Treiber, F. A., & Ruggiero, K. J. (2017). Mobile devices for the remote acquisition of physiological and behavioral biomarkers in psychiatric clinical research. Journal of psychiatric research, 85, 1-14. http://www.sciencedirect.com/science/article/pii/S0022395616305465

 

Mameli, C., Brunetti, D., Colombo, V., Bedogni, G., Schneider, L., Penagini, F., ... & Zuccotti, G. V. (2016). Combined use of a wristband and a smartphone to reduce body weight in obese children: randomized controlled trial. Pediatric Obesity. http://onlinelibrary.wiley.com/doi/10.1111/ijpo.12201/full

 

Majumder, S., Mondal, T., & Deen, M. J. (2017). Wearable Sensors for Remote Health Monitoring. Sensors, 17(1), 130. http://www.mdpi.com/1424-8220/17/1/130/htm

 

Karyotis, C., Doctor, F., Iqbal, R., James, A., & Chang, V. (2017). A fuzzy computational model of emotion for cloud based sentiment analysis. Information Sciences. http://www.sciencedirect.com/science/article/pii/S0020025517304164

 

Preejith, S. P., Alex, A., Joseph, J., & Sivaprakasam, M. (2016, May). Design, development and clinical validation of a wrist-based optical heart rate monitor. In Medical Measurements and Applications (MeMeA), 2016 IEEE International Symposium on (pp. 1-6). IEEE. http://ieeexplore.ieee.org/abstract/document/7533786/

 

Shirahama, K., & Grzegorzek, M. (2016). Emotion Recognition Based on Physiological Sensor Data Using Codebook Approach. In Information Technologies in Medicine (pp. 27-39). Springer International Publishing. http://link.springer.com/chapter/10.1007/978-3-319-39904-1_3

 

Fritz, T., & Müller, S. C. (2016, March). Leveraging biometric data to boost software developer productivity. In Software Analysis, Evolution, and Reengineering (SANER), 2016 IEEE 23rd International Conference on (Vol. 5, pp. 66-77). IEEE. http://www.smueller.li/papers/saner2016.pdf

 

Ricke, D. O., Harper, J., Shcherbina, A., & Chiu, N. (2016). Integrated Biomedical System. bioRxiv, 050138. http://biorxiv.org/content/biorxiv/early/2016/04/25/050138.full.pdf

 

Jones, D., & Dechmerowski, S. (2016, July). Measuring Stress in an Augmented Training Environment: Approaches and Applications. In International Conference on Augmented Cognition (pp. 23-33). Springer International Publishing. http://journals.lww.com/jhypertension/Abstract/2016/09002/_PP_08_16__AUTOMATICALLY_CLASSIFYING_ESSENTIAL.463.aspx

 

Boyce, M. W., Goldberg, B., & Moss, J. D. (2016, September). Electrodermal Activity Analysis for Training of Military Tactics. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 60, No. 1, pp. 1339-1343). SAGE Publications. http://pro.sagepub.com/content/60/1/1339.short

 

Melin, P., Pulido, M., Miramontes, I., & Prado-Arechiga, G. (2016). [PP. 08.15] A New Artificial Intelligence Method based on Modular Neural Networks for Classification of Arterial Hypertension. Journal of Hypertension, 34, e164. http://journals.lww.com/jhypertension/Abstract/2016/09002/_PP_08_15__A_NEW_ARTIFICIAL_INTELLIGENCE_METHOD.462.aspx

 

Natarajan, A., Xu, K. S., & Eriksson, B. (2016, August). Detecting divisions of the autonomic nervous system using wearables. In Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the (pp. 5761-5764). IEEE. http://ieeexplore.ieee.org/abstract/document/7592036/

 

Boccanfuso, L., Wang, Q., Leite, I., Li, B., Torres, C., Chen, L., ... & Scassellati, B. (2016, August). A thermal emotion classifier for improved human-robot interaction. In Robot and Human Interactive Communication (RO-MAN), 2016 25th IEEE International Symposium on (pp. 718-723). IEEE. http://scazlab.yale.edu/sites/default/files/files/boccanfuso_ROMAN_2016.pdf

 

Gjoreski, M., Gjoreski, H., Luštrek, M., & Gams, M. (2016, September). Continuous stress detection using a wrist device: in laboratory and real life. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (pp. 1185-1193). ACM. http://dl.acm.org/citation.cfm?id=2968306

 

Gillies, R. M., Carroll, A., Cunnington, R., Rafter, M., Palghat, K., Bednark, J., & Bourgeois, A. (2016). Multimodal representations during an inquiry problem-solving activity in a Year 6 science class: A case study investigating cooperation, physiological arousal and belief states. Australian Journal of Education, 60(2), 111-127. http://aed.sagepub.com/content/60/2/111.short

 

Singh, N. K., & Ricke, D. O. (2016, June). Towards an open data framework for body sensor networks supporting bluetooth low energy. In Wearable and Implantable Body Sensor Networks (BSN), 2016 IEEE 13th International Conference on (pp. 396-401). IEEE. http://biorxiv.org/content/biorxiv/early/2016/09/19/076166.full.pdf

 

Hemmelmann, J. (2016). Self-reported stress evaluation and physiological response (Bachelor's thesis, University of Twente). http://essay.utwente.nl/69101/1/Hemmelmann%20Jan_BA_Human%20Factors%20Engineering.pdf

 

Pijeira-Díaz, H. J., Drachsler, H., Järvelä, S., & Kirschner, P. A. (2016, April). Investigating collaborative learning success with physiological coupling indices based on electrodermal activity. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (pp. 64-73). ACM. http://dl.acm.org/citation.cfm?id=2883897

 

Hänsel, K. (2016, September). Wearable and ambient sensing for well-being and emotional awareness in the smart workplace. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (pp. 411-416). ACM. https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/15524/Hansel%20Wearable%20and%20Ambient%20Sensing%202016%20Published.pdf?sequence=1

 

Alqaraawi, A., Alwosheel, A., & Alasaad, A. (2016, May). Towards efficient heart rate variability estimation in artifact-induced Photoplethysmography signals. In Electrical and Computer Engineering (CCECE), 2016 IEEE Canadian Conference on (pp. 1-6). IEEE. http://ieeexplore.ieee.org/abstract/document/7726853/

 

Greco, A., Lanata, A., Citi, L., Vanello, N., Valenza, G., & Scilingo, E. P. (2016). Skin admittance measurement for emotion recognition: A study over frequency sweep. Electronics, 5(3), 46. http://www.mdpi.com/2079-9292/5/3/46/htm

 

Gjoreski, M. (2016). Continuous Stress Monitoring Using a Wrist Device and a Smartphone (Doctoral dissertation, Master thesis, Jozef Stefan International Postgraduate School, Slovenia, DOI: 10.13140/RG. 2.2. 23697.84322). https://www.researchgate.net/profile/Martin_Gjoreski/publication/308611962_CONTINUOUS_STRESS_MONITORING_USING_A_WRIST_DEVICE_AND_A_SMARTPHONE/links/57e8d89608ae9e5e4558d4a7.pdf

 

Greco, A., Valenza, G., & Scilingo, E. P. (2016). Electrodermal Phenomena and Recording Techniques. In Advances in Electrodermal Activity Processing with Applications for Mental Health (pp. 1-17). Springer International Publishing. http://link.springer.com/chapter/10.1007/978-3-319-46705-4_1

 

Saadatzi, M. N., Tafazzoli, F., Welch, K. C., & Graham, J. H. (2016, August). EmotiGO: Bluetooth-enabled eyewear for unobtrusive physiology-based emotion recognition. In Automation Science and Engineering (CASE), 2016 IEEE International Conference on (pp. 903-909). IEEE. https://www.researchgate.net/profile/Mohammad_Nasser_Saadatzi/publication/308780847_EmotiGO_Bluetooth-enabled_Eyewear_for_Unobtrusive_Physiology-based_Emotion_Recognition/links/57f025a108ae8da3ce4aec7a.pdf

 

Umlauft, M., Raffelsberger, C., Kercek, A., Almer, A., Schnabel, T., Luley, P., & Ladstaetter, S. (2016, December). A communication and multi-sensor solution to support dynamic generation of a situational picture. In Information and Communication Technologies for Disaster Management (ICT-DM), 2016 3rd International Conference on (pp. 1-7). IEEE. http://ieeexplore.ieee.org/abstract/document/7857205/

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