1372 52 17762 5 65650 document 17762 EmoSense__2024__RealTimeDataSet.zip application/zip aa82cf1aeb214ada0304dd013a77377a MD5 2066011018 2024-02-07 19:42:46 https://researchdata.bath.ac.uk/1372/1/EmoSense__2024__RealTimeDataSet.zip 1372 1 1 application/zip other All the raw participant data that was used for the EmoSense SDK and the CHI 2024 paper "Sweating the Details: Emotion Recognition and the Influence of Physical Exertion in Virtual Reality Exergaming". There is data for 72 participants. Each participant has 10 csv files (2 aggregated calibration, 2 raw calibration, 3 raw study, 3 affect response files). Questionnaire_Data contains post condition measures. Baseline_Affect_Data is prestudy participant affect states. en staffonly all_rights_reserved

EmoSense__2024__RealTimeDataSet.zip

data 17763 1 65703 document 17763 DMP59_Consent_Form_Confidential.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document abe70e6af7c0d1f70bf3ecab1280c802 MD5 40849 2024-02-12 08:51:07 https://researchdata.bath.ac.uk/1372/2/DMP59_Consent_Form_Confidential.docx 1372 2 2 application/vnd.openxmlformats-officedocument.wordprocessingml.document other en staffonly

DMP59_Consent_Form_Confidential.docx

ethics 17764 1 65705 document 17764 DMP59_Participant_Information_Sheet.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document af513549e2ad3219693e0ce1e49b521f MD5 73712 2024-02-12 08:51:17 https://researchdata.bath.ac.uk/1372/3/DMP59_Participant_Information_Sheet.docx 1372 3 3 application/vnd.openxmlformats-officedocument.wordprocessingml.document other en staffonly

DMP59_Participant_Information_Sheet.docx

ethics 17765 1 65707 document 17765 indexcodes.txt text/plain c0827d596160ad73b73ee31cc509ec7d MD5 1453 2024-02-12 09:01:41 https://researchdata.bath.ac.uk/1372/4/indexcodes.txt 1372 4 4 text/plain other Generate index codes conversion from other to indexcodes en staffonly

indexcodes.txt

http://eprints.org/relation/isVersionOf https://researchdata.bath.ac.uk/id/document/17763 http://eprints.org/relation/isVolatileVersionOf https://researchdata.bath.ac.uk/id/document/17763 http://eprints.org/relation/isIndexCodesVersionOf https://researchdata.bath.ac.uk/id/document/17763 17766 1 65708 document 17766 indexcodes.txt text/plain 81db94f57b2d911d3b3f526f2ed52c33 MD5 3262 2024-02-12 09:01:42 https://researchdata.bath.ac.uk/1372/5/indexcodes.txt 1372 5 5 text/plain other Generate index codes conversion from other to indexcodes en staffonly

indexcodes.txt

http://eprints.org/relation/isVersionOf https://researchdata.bath.ac.uk/id/document/17764 http://eprints.org/relation/isVolatileVersionOf https://researchdata.bath.ac.uk/id/document/17764 http://eprints.org/relation/isIndexCodesVersionOf https://researchdata.bath.ac.uk/id/document/17764 archive 14799 disk0/00/00/13/72 2024-05-13 08:44:29 2024-07-12 14:49:54 2024-05-13 08:44:29 data_collection show Potts Dominic dmp59@bath.ac.uk 0000-0002-4607-289X University of Bath TRUE Hartley Joe jh3968@bath.ac.uk University of Bath FALSE Jicol Crescent C.Jicol@bath.ac.uk 0000-0003-0599-8108 University of Bath FALSE Clarke Christopher cjc234@bath.ac.uk 0000-0003-3916-7708 University of Bath FALSE Lutteroth Christof C.Lutteroth@bath.ac.uk 0000-0003-0634-7569 University of Bath FALSE FB0090 JN0010 dept_compsci virtual reality, exergaming, emotion recognition, affect recognition, physiological sensing, physiological correlates, psychophysiological correlates, high-intensity exercise All the raw participant data that was used for the EmoSense SDK and the CHI 2024 paper "Sweating the Details: Emotion Recognition and the Influence of Physical Exertion in Virtual Reality Exergaming". There is data for 72 participants. Each participant has 10 csv files: 2 aggregated calibration, 2 raw calibration, 3 raw study - These files contain sensor measures under different conditions - and 3 affect response files - participant ground truth measures of affect. Questionnaire_Data contains post exercise-bout measures of intrinsic motivation and flow. Baseline_Affect_Data is prestudy participant ground truth affect measures. Aggregated_Data contains an aggregate file of all participant data that was used for the analysis described in the CHI paper. 2024-05-11 University of Bath restricted https://github.com/RevealBath/EmoSense EmoSense SDK and Virtual Environments RightsHolder University of Bath Horizon Europe Framework Programme https://doi.org/10.13039/100018693 101070533 EMIL – The European Media and Immersion Lab Innovate UK https://doi.org/10.13039/501100006041 10044904 EMIL – The European Media and Immersion Lab bath-marvel For the methodology and apparatus of the data collection, please refer to the paper. The VR exergame developed for this study, required participants to cycle on a stationary Wahoo KICKR exercise bike while wearing a Vive Pro Eye VR headset. Physiological measures were collected using the eye tracker in the VR headset (pupillometry), a Shimmer3 GSR+ tethered to a participant's middle and ring finger (EDA), a Polar H10 HR monitor chest strap (HR and HRV), and a Vive face tracker (facial tracking). All physiological measures were sent to a PC (Intel 13900K, Nvidia GTX 4090 and 64GB of DDR5 RAM) running the Unity VR exergame over Bluetooth (BLE protocol), which recorded all measures at a sample rate of 40-50 Hz using the EmoSense. en 1 10.15125/BATH-01372 https://doi.org/10.1145/3613904.3642611 pub request Access to bona fide researchers only. Dataset