Multimodal Micromobility Stress Dataset

This dataset contains participant-level multimodal recordings collected during real-world micromobility experiments across roadway and sidewalk conditions. For each participant, the dataset provides synchronized exports of: (1) mobile accelerometer motion data, (2) eye-tracking signals and events (gaze, fixations, blinks, saccades, IMU, pupil diameter), (3) high-frequency smartwatch physiological and motion streams (accelerometer, electrodermal activity, temperature, blood volume pulse), and (4) video-feedback annotations with frame-level stress labels.Data are organized by participant, modality, and condition to support reproducible analysis workflows. Timestamps are provided for each modality, enabling user-defined temporal alignment and fusion. Video-feedback files include frame number, relative time, and aligned timestamps with associated stress labels. The dataset is intended for research on multimodal stress modeling, human factors in transportation, wearable sensing, and behavior understanding in micromobility contexts.