Published February 15, 2024 | Version v1
Dataset Open

Dataset of Motion Capture of Cyclists

  • 1. Mirror 3D Lab Ltd
  • 2. CYENS Centre of Excellence
  • 3. ROR icon University of Cyprus

Description

The system used is the  Phasespace Impulse X2E motion capture system, featuring active LEDs. This system uses 24 cameras designed for capturing 3D motion through modulated LEDs. These cameras incorporate pairs of linear scanner arrays operating at high frequencies, enabling the capture of the position of bright spots of light generated by the LEDs. 

Methodology for Mocap Data Collection
Participants received detailed information about the mocap data collection procedure and purpose. Informed consent was obtained, ensuring understanding and agreement and a pre-session questionnaire collected demographic and health information. Next, the participant’s road or time trial (TT) bike was placed on a turbo
trainer and the meticulous marker placement on the cyclist’s body.

Cyclists followed a specific workout plan based on their bike type. The plan included warm-up, cycling positions, and recovery intervals.


Sensors were strategically put mostly on the back side of the torso due to the body position while cycling.


Workout:

- Warm-Up: 1 minute in any position.
- 30 seconds at 60 RPM
- 15 seconds at 75 RPM
- 15 seconds at 90 RPM
- 10 seconds at 100 RPM
- 10 seconds at 110 RPM


Cycling Positions and Cadences

For Road Bikes:

The workout was performed for each of the following positions with 1 minute between each position to allow for recuperation:
- Straight Arms
- Comfortable
- Aggressive
- Aero Position
- Standing (not above 90 RPM)

For TT Bikes:

The workout was performed for each of the following positions with 1 minute between each position to allow for recuperation:
- Comfortable
- Aero Position
- Standing (not above 90 RPM)

Participants were monitored throughout the session to ensure well-being and comfort. They had the option to terminate the procedure if they feel unwell or wish to stop.

The motion capture dataset is organized as follows.
There is a dedicated folder for each participant, labeled according to the following naming convention:

"1_RB_M42_20230719_PK"

  • 1 = Index Number
  • RB = Road Bike (RB) or Time Trial bike (TT) 
  • M42 = Gender (M/F) and age
  • 20230719 = Capture Date (YYYYMMDD)
  • PK = Unique Identifier of participant

In each folder there are three files:

  1. C3D = Motion Capture Raw Data
  2. BVH = BioVision Hierarchy (BVH), data mapped to skeletal data ready for animation (errors may still remain)
  3. GPX = Data from related zwift workout

The Project (Smart Cyclo) is funded by the European Union Recovery and Resilience Facility of the NextGenerationEU instrument, through the Research and Innovation Foundation.

Files

Dataset_cycing_mocap.zip

Files (497.4 MB)

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Additional details

Funding

European Union