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Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [ Mood detection application and parameters for the BAN SG application matrix ] Date Submitted: [ November , 2007 ] Source: [Alex Gluhak (1), Mirko Presser (1), Laurent Ouvry (2)]

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Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

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  1. Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [Mood detection application and parameters for the BAN SG application matrix] Date Submitted: [November, 2007] Source: [Alex Gluhak (1), Mirko Presser (1), Laurent Ouvry (2)] Company [University of Surrey (1), CEA-Leti (2)] Address [CCSR, Guildford, Surrey GU2 7XH, United Kingdom (1), 17 rue des Martyrs 38054 Grenoble France (2)] E−Mail [A.Gluhak@surrey.ac.uk (1), laurent.ouvry@cea.fr (2)] Re: [802.15 BAN] Abstract: [This document present the basic technical parameters to fill the application matrix for a BAN based mood detection application ] Purpose: [To promote discussion in 802.15 BAN Study Group] Notice: This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P802.15. Laurent Ouvry

  2. Mood detection application and parameters for the BAN SG application matrix Alex Gluhak, University of Surrey Mirko Presser, University of Surrey Laurent Ouvry, CEA-Leti Acknowledgement : S. Kupschick, Human Factor Consult, GmbH This work has been partly funded under the 6th EU’s Framework Programme for Research and technological Development Laurent Ouvry

  3. Objectives • To provide inputs for the application matrix • A brief overview of applications which would use mood detection • Tentative parameters for the associated BAN Laurent Ouvry

  4. Contents • What do we mean there by mood ? • What kind of services can be triggered by mood detection ? • Why adding such an application into the application matrix ? • An HW platform example used for field trials • The proposed application matrix parameters Laurent Ouvry

  5. Mood model • Russell’s circumplex model of affect as starting point (dimensional model) • Emotions (E1/2/3) can be described by their degrees of valence and arousal • Most of the time they are not pure but mingled Laurent Ouvry

  6. Mood based mobile services • Services allowing the sharing or recording of emotions • Instant messaging, life-blog, counselling • Mood used as trigger for the delivery of adequate service information or content • e.g. mood based messaging, security, happy messaging • Adaptation of content or service behaviour according to the mood of a person • E.g. Night club, Juke box Laurent Ouvry

  7. Rationale to have it in the application matrix • Mood detection is extremely hard, but is a promising BAN application driver • It relies on sensors measuring physiological parameters • Such sensors appear in the application matrix • It is NOT a medical application • QoS requirements are relaxed • Security requirements are not • It is part of CE applications • Such a couple does not clearly appear in the application matrix so far Laurent Ouvry

  8. System Design • Sensors and algorithms to capture mood • Physiological Sensors: • ECG (ElectroCardioGram), EDA (ElectroDermal Activity), Breathing Rate, Skin Temperature • Mood Algorithm • Complex algorithm to extract features and infer mood from physiological parameters • Portable System Platform • Body Sensor Network (e.g. over an 802.15.4 PHY) • Mobile PDA class device • Mood Application • Mood based messaging service Laurent Ouvry

  9. ECG Breathing Rate EDA Skin Temp EDA Probes Temperature Probe ECG Probes Breathing Rate Strap Laurent Ouvry

  10. Sensor parameters Enhancements (for higher grade systems) may require more rate demanding sensors : EMG to monitor facial muscles (~250 Hz sampling rate) Voice tone, frequency, speed (~1 kHz sampling rate) Laurent Ouvry

  11. Proposed application matrix parameters(for a first grade mood detection system) Laurent Ouvry

  12. References • [1] IST FP6 e-SENSE project web site ( http://www.ist-e-sense.org ) • [2]e-SENSE deliverable D1.3.1, “Functional requirements for e-SENSE Show Cases”, July 2006 • [3] “Towards Mood-based Mobile Services and Applications”, A. Gluhak, M. Presser, L. Zhu, S. Esfandiyari and S. Kupschick, Proceedings of EUROSSC’07, 2nd European Conference on Smart Sensing and Context, October 23-25, 2007, Kendal, England Laurent Ouvry

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