1. Emotions from PNS system
Lindsay Brown, R&D Engineer

2. Monitoring your emotions
Measuring peripheral signals

3. Monitoring ANS responses
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4. Arousal Monitoring Real-time arousal monitor
Test subject watching movie
Instantaneous arousal
Arousal profile
Input signals: ECG, respiration, SkT & GSR
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5. Arousal monitoring Use-case: chess players
Bad move!
Can we gauge the arousal of a chess player?
Test game against a computer
Player commenting his game afterwards
Fluctuations during the game
Approaching chessmate
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6. Stress monitoring ANS as a predictor for stress?
Monitoring physiological responses during stressful events shine light on possible physiological markers for stress
Red: Patients Blue: Controls
Red: During stressor Blue: At rest Δ
Comparing patients and healthy subjects may provide new tools for assisting diagnosis of stress disorders
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7. Trapezius EMG as a predictor of stress
Speaker name - Title presentation
Trapezius EMG as a predictor of stress
The proposed protocol successfully induces stress
Visual Analog Scores (stress) are significantly higher for stress than rest periods (p = 6E-5)
EMG features significantly differ between stress and rest periods
RMS EMG values are significantly higher (p = )
The number of EMG gaps is significantly lower (p = )
Mean frequency is significantly lower (p = )
Body Area Networks for Emotion Monitoring
Copyright Holst Centre

8. Emotions from eeg towards real-time valence monitoring
Raw EEG data F3/4 or F7/8
Frequency spectra: alpha power
2 second windows
Real-time Valence
Ratio of alpha power right/left
High ratio = positive emotions
Low ratio = negative emotions
Body Area Networks for Emotion Monitoring

9. Longitudinal recordings in natural environments
Speaker name - Title presentation
Longitudinal recordings in natural environments
Motivation
Measuring and managing stress requires monitoring of trends in bio-signals over large time period (weeks, months, years)
Bring technology from lab to daily-life environments
Challenges
Coping with motion artifact requires an integrated approach
Achieve longer autonomy through the adoption of ultra-low power electronics
Achieve wearability through new integration technologies
Achieve robustness in detecting then compensating motion artifact
Body Area Networks for Emotion Monitoring
Copyright Holst Centre

10. IMEC ECG NECKLACE Wireless, connected, ‘on-the-move’
Wearable | with adjustable electrode leads
Robust | monitoring in every-day life situations
Low-power | 24/7 recording for 1 week
Smart | instantaneous RR and HRV analysis
Imec inside: bio-potential ASIC & algorithms
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11. IMEC connects your health Manage your vitals from your mobile
BAN interface to Android Phone
24/7 connectivity to public network
Instantaneous alert s
Text messages
BAN data available globally over the internet
Real-time check
Link to EPR
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