Abstract
A recent interest in interaction design is towards the development of novel technologies emphasizing the value of mindfulness, monitoring, awareness, and self-regulation for both health and well-being. Whereas existing systems have focused mostly on relaxation and awareness of feelings, there has been little exploration on tools supporting the self-regulation of attention during mindfulness sitting meditation. This paper describes the design and initial evaluation of MeditAid, a wearable system integrating electroencephalography technology with an adaptive aural entrainment for real-time training of mindfulness state. The system identifies different meditative states and provides feedback to support users in deepening their meditation. We report on a study with 16 meditators about the perceived strengths and limitations of the MeditAid system. We demonstrate the benefits of binaural feedback in deepening meditative states, particularly for novice meditators.
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Emotiv. (2014). Electrode Placement. Retrieved 2014, from Emotiv Community: http://www.emotiv.com/forum/forum14/topic25.
Emotiv. (2014). Extracting RAW data and other applications. Retrieved 2014, from Emotiv Community: http://www.emotiv.com/forum/forum4/topic401/.
Emotiv (2014) Sample rate. Retrieved 2014, from Emotiv Community: https://emotiv.com/store/compare/sample rate.
Emotiv (2014). Comparison with other EEG units. Retrieved 2014, from Emotiv Community: http://www.emotiv.com/forum/forum4/topic127/.
Emotiv. (2014). Developer Edition SDK. Retrieved 2014, from Emotiv Store: http://www.emotiv.com/store/sdk/bci/developer-edition-sdk/.
Emotiv. (2014). Extracting RAW data and other applications. Retrieved 2014, from Emotiv Community: http://www.emotiv.com/forum/forum4/topic401/.
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Sas, C., Chopra, R. MeditAid: a wearable adaptive neurofeedback-based system for training mindfulness state. Pers Ubiquit Comput 19, 1169–1182 (2015). https://doi.org/10.1007/s00779-015-0870-z
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DOI: https://doi.org/10.1007/s00779-015-0870-z