BODYinTRANSIT: Motion Capture and Physiological Data from 103 Participants

Data from 103 participants, curated into a version with 84 subjects grouped by Eating Disorder Examination Questionnaire (EDE-Q) and International Physical Activity Questionnaire (IPAQ) scores. Participants wore a Rokoko motion capture suit and a BITalino PLUX while listening to manipulated footstep sounds under three audio conditions. The dataset was authored by D'Adamo, Amar and last updated on 2025-10-14.

Use Cases

• Analyze the relationship between body image and physical activity levels based on EDE-Q and IPAQ score groupings.
• Study the effects of auditory feedback manipulation on gait and movement based on the three sound conditions (Control, High Frequency, Low Frequency).
• Correlate physiological signals with motion capture data based on the simultaneous use of the BITalino PLUX and Rokoko suit.
• Investigate sensory-driven body transformation experiences based on the described experimental setup.

Strengths

• Data from 103 participants, with a curated subset of 84 subjects.
• Participants are grouped into four distinct sets based on validated questionnaire scores (EDE-Q and IPAQ).
• Multimodal data collection includes motion capture, physiological signals, and controlled auditory stimuli.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

e-cienciaDatos Harvested Dataverse

Collection Method

Data collected from participants equipped with a Rokoko motion capture suit, a BITalino PLUX, and headphones playing modified footstep sounds.

Time Range

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Freshness

Last updated 2025-10-14 21:30:48; freshness should be verified.

Geography

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