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Feel the science


What is emotion? Current psychological science suggests that the experience of emotion is constructed out of at least three key “ingredients”: a) Internal sensations from our body; b) Information we collect from the external world (e.g. Where am I? What is happening around me? What is that smell?);
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How do our bodies process emotions? A look at the Sympathetic and Parasympathetic nerve systems provides insight. Imagine that you’re taking a stroll in the park when suddenly, an angry bear appears. Your heart starts to beat faster, while blood pressure may rise. The palms and feet start to sweat and your muscles tense.
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Computer Science

So, how does it work? 
By leveraging four embedded sensors via the wristband, Feel collects these indicators and analyses them using cutting-edge methods of computer science. Heart Rate Variability (HRV) is measured through a photoplethysmogram (PPG) sensor that captures slight differences in heart rate as one lives through emotional experiences.
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Processing & Regulating your Emotions

Feel helps you become more aware of your emotions so you can gain a deeper understanding of their internal and external triggers. Based on information collected by the Feel wristband and your input on the Feel app, you’ll receive tailored guidance on how to better regulate and optimize your emotional experience.
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Lindquist, K. A., Wager, T. D., Kober, H., Bliss-Moreau, E., & Barrett, L. F. (2012).
The brain basis of emotion: a meta-analytic review. Behavioral and brain sciences, 35(03), 121-143.

Russell, J. A., & Barrett, L. F. (1999).
Core affect, prototypical emotional episodes, and other things called emotion: dissecting the elephant. Journal of personality and social psychology, 76(5), 805.

Doré, B. P., Silvers, J. A., & Ochsner, K. N. (2016).
Toward a Personalized Science of Emotion Regulation. Social and Personality Psychology Compass, 10(4), 171-187.

Ekman, P. (1992).
An argument for basic emotions. Cognition & emotion, 6(3-4), 169-200.

Plutchik, R. (1980).
A general psychoevolutionary theory of emotion. Theories of emotion, 1(3-31), 4.

Picard, R. W., Vyzas, E., & Healey, J. (2001).
Toward machine emotional intelligence: Analysis of affective physiological state. IEEE transactions on pattern analysis and machine intelligence, 23(10), 1175-1191.

Quintana, D. S., Guastella, A. J., Outhred, T., Hickie, I. B., & Kemp, A. H. (2012).
Heart rate variability is associated with emotion recognition: direct evidence for a relationship between the autonomic nervous system and social cognition. International Journal of Psychophysiology, 86(2), 168-172.

Lee, C., Yoo, S. K., Park, Y., Kim, N., Jeong, K., & Lee, B. (2006, January).
Using neural network to recognize human emotions from heart rate variability and skin resistance. In Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the, 5523-5525. 

Zhai, J., & Barreto, A. (2006, August).
Stress detection in computer users based on digital signal processing of noninvasive physiological variables. In Engineering in Medicine and Biology Society, 2006. EMBS'06. 28th Annual International Conference of the IEEE, 1355-1358. 

Martinez, H. P., Bengio, Y., & Yannakakis, G. N. (2013).
Learning deep physiological models of affect. IEEE Computational Intelligence Magazine, 8(2), 20-33.

Sun, F. T., Kuo, C., Cheng, H. T., Buthpitiya, S., Collins, P., & Griss, M. L. (2010).
Activity-aware mental stress detection using physiological sensors.

Haag, A., Goronzy, S., Schaich, P., & Williams, J. (2004, June).
Emotion recognition using bio-sensors: First steps towards an automatic system. In Tutorial and research workshop on affective dialogue systems, 36-48. 

Lisetti, C. L., & Nasoz, F. (2004).
Using noninvasive wearable computers to recognize human emotions from physiological signals. EURASIP Journal on Advances in Signal Processing, 2004(11), 929414.

Quazi, M. T., Mukhopadhyay, S. C., Suryadevara, N. K., & Huang, Y. M. (2012, May).
Towards the smart sensors based human emotion recognition. In Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International, 2365-2370.
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Investigational Device.
Limited by Federal (or United States) law to investigational use. Smartphone application & Writsband renderings reflect concepts and images that are subject to change and may not reflect finished commercial soft and/or hardware products