Determining 3D Positions

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Flow users may wish to determine the 3D positions of the Flow headset as worn by participants. Several approaches exist, but one method is summarized below. Please refer to the detailed guide (pdf document attached at the bottom of this page) for more detailed instructions.

Mount AprilTags to the Headset
Print and affix AprilTags to the outer surface of the Flow headset. The precise location of the tags is not critical—they serve to improve the accuracy of 3D model generation.  Printed AprilTags may be mounted to the headset on cardboard pieces with adhesive (such as double-sided tape).

Capture the Participant Wearing the Headset
Fit the headset to the participant, ensuring good signal quality. Then, capture a video of the participant wearing the headset using a standard smartphone camera.

  • Use landscape orientation.
  • Enable high frame rate capture.
  • Ensure plentiful lighting.
  • Move the camera slowly, performing a 360 degree scan.

Generate a 3D Model
Import the video into RealityCapture (or a similar photogrammetry software) to generate a 3D model. Settings may need to be adjusted for the AprilTags.

Assemble in CAD
Using SolidWorks (recommended) or a software of your choice, create a base assembly that includes:

  • A head surface from an MRI scan (or, if unavailable, an atlas scalp or generic headform).
  • The 3D model generated from the video.
  • A CAD model of the Flow headset. Solidworks SLDPRT files as well as STEP files are included in the zip files below. See the pdf attached for detailed instructions on working with these files.

Align and Extract Coordinates

See the attached guide for more details.

  • Align the photogrammetric 3D model to the MRI or atlas scalp.

  • Align the Flow headset CAD model to the 3D scan.

  • Extract coordinates where light pipes from the Flow2 model intersect with the scalp of the MRI.

  • Use the scripts provided below to extract and visualize optode locations.


Below is a detailed, step-by-step guide to extracting optode locations for the Kernel Flow2 wearable TD-fNIRS headset using SolidWorks, the SolidWorks API, and photogrammetric methods.