DOI: 10.15125/bath-01489
title: Dataset for "RetroSketch: A Retrospective Method for Measuring Emotions and Presence in Virtual Reality"

description: The aggregated data file containing 140 participants' data collected and analysed in the CHI 2025 paper "RetroSketch: A Retrospective Method for Measuring Emotions and Presence in Virtual Reality". 

Each participant completed two half-hour sessions and continuous measures for both sessions were aggregated in 60-second intervals, resulting in 31 rows per session and 62 rows per participant. The measures used in this study fall into three groups:

- Pre-measures include demographic information, gaming experience and preferences, personality and gamer traits, baseline emotions and physiology.
- Exposure measures include Retrospective method emotion and keypoint measures, experience sampling method (ESM) measures, and various physiological measures.
- Post-measures include measures of flow state, intrinsic motivation, multimodal presence, and simulator sickness, and participants' qualitative evaluations of RetroSketch and ESM measures.
description: For the methodology and apparatus of the data collection, please refer to the associated paper.
description: The study required participants to play one of five VR games (Assetto Corsa Competizione, Garden of the Sea, Half-Life Alyx, I Expect You To Die, and Red Matter) over two 30 minute sessions using a Vive Pro Eye VR headset and controllers. 

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 data collection application over serial and Bluetooth (BLE protocol), which recorded all measures at a sample rate of approximately 40-50 Hz using the EmoSense SDK.

R (v4.4.1) was used to analyse the data.
description: The main aggregate data file consists of the following measures:

Meta Data: Participant ID, session number, condition (Retro or Retro_ESM), and game played.

Pre-measures: Demographics, baseline emotions, big 5 personality traits (B5), immersive tendencies (ITQ), game genre preference, Brain Hex gamer types, tondello gamer traits, baseline simulator sickness (SSQ), and baseline physiology (calibration).

Exposure measures: Retro emotion measures (aggregated for every 60-second interval for both the 'Prior' 60s from the interval and over a 'Window' of 30s before and after the interval), Retro keypoint measures, experience sampling method (ESM) measures, and physiological measures aggregated for the same 60-second intervals (both 'Prior' and 'Window')

Post measures: PPL flow state (PPL-FSQ), flow state short (FSS), intrinsic motivation (IMI), multimodal presence (MPS), simulator sickness (SSQ), and qualitative questions comparing RetroSketch and ESM.

For further details about the measures, please refer to the associated paper.
description: Further relevant documentation may be found in the following resources.

   Potts, D., Gada, M., Gupta, A., Goel, K., Krzok, K. P., Pate, G., Hartley, J., Weston-Arnold, M., Aylott, J., Clarke, C., Jicol, C., and Lutteroth, C.,  2025.   RetroSketch: A Retrospective Method for Measuring Emotions and Presence in Virtual Reality.     In:  Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems.      ACM, 1-25.  Available from: https://doi.org/10.1145/3706598.3713957.