Empathic Computing and Collaborative Immersive Analytics
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This document discusses empathic computing and collaborative immersive analytics. It notes that while fields like scientific and information visualization are well established, little research has looked at collaborative visualization specifically. Collaborative immersive analytics combines mixed reality, visual analytics and computer-supported cooperative work. Empathic computing aims to develop systems that allow sharing experiences, emotions and perspectives using technologies like virtual and augmented reality with physiological sensors. Applying these concepts could enhance communication and understanding for collaborative immersive analytics tasks.
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Empathic Computing and Collaborative Immersive Analytics
- 1. EMPATHIC COMPUTING AND COLLABORATIVE IMMERSIVE ANALYTICS Mark Billinghurst mark.billinghurst@unisa.edu.au July 2022
- 4. Need for More Research •Collaborative Visualisation related to: • Scientific Visualisation • Information Visualisation • Visual Analytics •All well established fields over last 20 years • But little existing research in Collaborative Visualisation • E.g. from 1990 – 2010, over 1600 papers in main Viz conferences • Only 34 papers published in Collaborative Visualisation, ~2%
- 5. Collaborative Immersive Analytics • Intersection between Mixed Reality, Visual Analytics, CSCW
- 6. CIA Example: EVL CAVE2
- 7. Modern Communication Technology Trends 1. Improved Content Capture • Move from sharing faces to sharing places 2. Increased Network Bandwidth • Sharing natural communication cues 3. Implicit Understanding • Recognizing behaviour and emotion
- 10. Empathic Computing Research Focus Can we develop systems that allow us to share what we are seeing, hearing and feeling with others?
- 11. Key Elements of Empathic Systems •Understanding • Emotion Recognition, physiological sensors •Experiencing • Content/Environment capture, VR •Sharing • Communication cues, AR
- 12. Sharing Virtual Communication Cues • AR/VR displays • Gesture input (Leap Motion) • Room scale tracking • Conditions • Baseline, FoV, Head-gaze, Eye-gaze
- 13. Piumsomboon, T., Dey, A., Ens, B., Lee, G., & Billinghurst, M. (2019). The effects of sharing awareness cues in collaborative mixed reality. Frontiers in Robotics and AI, 6, 5.
- 14. Sensor Enhanced HMDs Eye tracking, heart rate, pupillometry, and face camera HP Omnicept Project Galea EEG, EMG, EDA, PPG, EOG, eye gaze, etc.
- 15. GALEA: Multiple Physiological Sensors into HMD • Incorporate range of sensors on HMD faceplate and over head • EMG – muscle movement • EOG – Eye movement • EEG – Brain activity • EDA, PPG – Heart rate
- 18. Pre-training (Finger Pointing) Session Start
- 19. Post-Training (Finger Pointing) Session End
- 20. Brain Synchronization in VR Gumilar, I., Sareen, E., Bell, R., Stone, A., Hayati, A., Mao, J., ... & Billinghurst, M. (2021). A comparative study on inter-brain synchrony in real and virtual environments using hyperscanning. Computers & Graphics, 94, 62-75.
- 23. asfd
- 25. Applying Empathic Computing to CIA • Providing communication cues in immersive visualization • Gaze, gesture, body motion, avatar representation • Measuring cognitive load and stress • Adapting interface and visualization • Exploring communication measures • Brain synchronization, non-verbal cues, etc. • Sharing perspectives • Same virtual body, joint interaction • Hybrid interfaces • Combining multiple devices AR/VR/MR view
- 26. Conclusions • Need for more research in Collaborative Visualization • Especially Collaborative Immersive Analytics • Empathic Computing • Systems that enhance understanding • Natural collaboration + Experience capture + Implicit understanding • Combining AR, VR, Physiological sensing • Applying Empathic Computing to CIA • Sharing communication cues, brain synchronization, etc.
- 27. More Information.. Billinghurst, M., Cordeil, M., Bezerianos, A., & Margolis, T. (2018). Collaborative immersive analytics. In Immersive Analytics (pp. 221-257). Springer, Cham.