Wearable and ambient sensing for well-being and emotional awareness in the smart workplace

Wearable, sensor-equipped devices -- often referred to as wearables -- became increasingly public accessible during the last years. Health and fitness wearables offer ubiquitous and continuous sensing of various aspects of our lives and help us reflect and learn about ourselves. The rising social acceptance of body-worn technology is also a driver for the increasing adoption of wearables on the consumer level - and especially the fitness and healthcare sector is booming [1]. Consumer surveys discovered that users expect wearables to help them live longer and happier lives [6].

[1]  Juan Carlos Augusto,et al.  Handbook of Ambient Intelligence and Smart Environments , 2009, HAIS 2010.

[2]  R. Cummins Subjective Wellbeing, Homeostatically Protected Mood and Depression: A Synthesis , 2010 .

[3]  Anil K Sood,et al.  Impact of stress on cancer metastasis. , 2010, Future oncology.

[4]  S. C. Mukhopadhyay,et al.  Towards the smart sensors based human emotion recognition , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[5]  Juan Carlos Augusto,et al.  Handbook of Ambient Intelligence and Smart Environments , 2009 .

[6]  Fanglin Chen,et al.  StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones , 2014, UbiComp.

[7]  Yunxin Liu,et al.  MoodScope: building a mood sensor from smartphone usage patterns , 2013, MobiSys '13.

[8]  Rosalind W. Picard,et al.  A Wearable Sensor for Unobtrusive, Long-Term Assessment of Electrodermal Activity , 2010, IEEE Transactions on Biomedical Engineering.

[9]  E. Epel,et al.  Accelerated telomere shortening in response to life stress. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Frédéric Bousefsaf,et al.  Remote detection of mental workload changes using cardiac parameters assessed with a low-cost webcam , 2014, Comput. Biol. Medicine.

[11]  Kristina Höök,et al.  Mind the body!: designing a mobile stress management application encouraging personal reflection , 2010, Conference on Designing Interactive Systems.

[12]  T. Dinan,et al.  Biological and psychological markers of stress in humans: Focus on the Trier Social Stress Test , 2014, Neuroscience & Biobehavioral Reviews.

[13]  Carsten Röcker Acceptance of Future Workplace Systems: How the Social Situation Influences the Usage Intention of Ambient Intelligence Technologies in Work Environments , 2009 .

[14]  Z. Freeman Stress and cardiovascular disease , 1988, The Medical journal of Australia.

[15]  Carsten Röcker,et al.  Services and Applications for Smart Office Environments - A Survey of State-of-the-Art Usage Scenarios , 2010 .

[16]  D. Lam,et al.  Understanding and Managing Stress , 2011 .

[17]  S. K. Nelson,et al.  Stressed and Happy? Investigating the Relationship Between Happiness and Perceived Stress , 2009 .

[18]  J. Russell A circumplex model of affect. , 1980 .

[19]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[20]  Alex Pentland,et al.  Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits , 2014, ACM Multimedia.

[21]  Mary Czerwinski,et al.  MoodWings: a wearable biofeedback device for real-time stress intervention , 2013, PETRA '13.

[22]  Natalia Sidorova,et al.  Smart technologies for long-term stress monitoring at work , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[23]  Martin Pielot,et al.  When attention is not scarce - detecting boredom from mobile phone usage , 2015, UbiComp.

[24]  undefined Eurofound Third European survey on working conditions 2000 , 2011 .

[25]  Mary Czerwinski,et al.  Under pressure: sensing stress of computer users , 2014, CHI.

[26]  Kristina Höök,et al.  Experiencing the Affective Diary , 2009, Personal and Ubiquitous Computing.

[27]  Rosalind W. Picard,et al.  Empatica E3 — A wearable wireless multi-sensor device for real-time computerized biofeedback and data acquisition , 2014, 2014 4th International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH).

[28]  Zhihong Zeng,et al.  A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.