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opennirscap-build

Build an OpenNIRScap 24-channel fNIRS brain cap from open-source hardware — Altium conversion, BOM sourcing, PCB fab, assembly, firmware flash

Stars
23
Source
plurigrid/asi
Updated
2026-04-26
Slug
plurigrid--asi--opennirscap-build
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/plurigrid/asi/HEAD/plugins/asi/skills/opennirscap-build/SKILL.md -o .claude/skills/opennirscap-build.md

Drops the SKILL.md into .claude/skills/opennirscap-build.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

OpenNIRScap Build

Open-source 24-channel fNIRS wearable brain cap. Kim et al. 2025, University of Toronto.

Source

Architecture

  • 24 detector modules (VBPW34S photodiode + AD8618 TIA, 25mm circular PCB)
  • 8 dual-wavelength source emitters (VSMD66694: 660nm + 940nm)
  • 1 ECU (STM32L476 + 8x TMUX1104 analog MUX + PCA9685 PWM, 112x112mm PCB)
  • 35mm source-detector separation (cortical depth sensitivity)
  • 1 kHz effective sampling, 52.3 dB SNR, 12-bit ADC
  • USB isolated (ADUM4160), LiPo powered (1100mAh, >5hr)

Blocker: Altium to Gerber Conversion

Repo has Altium .PcbDoc source files, no exported gerbers or CSV BOMs.

PCBs to convert

Project File Description
fNIRS_sensor_module SensorModulePCB.PcbDoc 25mm circular, combined emitter+detector
fNIRS_ECU fNIRS_PCB.PcbDoc 112x112mm main control board
DetectorOptode DetectorOptode.PcbDoc Detector-only variant
SourceOptode SourceOptode.PcbDoc Source-only variant
STLINK_Breakout STLINK_Breakout.PcbDoc Programming adapter

Conversion approaches (in order of preference)

  1. KiCad 8 built-in importer — File > Import > Altium .PcbDoc. Best fidelity. Needs KiCad installed.
  2. altium2kicad (Perl, 933 stars) — perl convertpcb.pl file.PcbDoc. Repo: thesourcerer8/altium2kicad. Needs unpack.pl first.
  3. Altium 365 Viewer (free web) — View online, manual export. No CLI.
  4. GitHub Issue — Ask authors to export gerbers. Repo is active (last push 2026-03).

Attempted and failed

  • altium-cli (Rust, akiselev) — broken workspace deps, won't build
  • pyaltium — crashes on Python 3.14 (missing dateutil dep)
  • altium2kicad unpack.pl worked but convertpcb.pl couldn't find unpacked files

Next step

Install KiCad 8 (brew install --cask kicad or nix shell nixpkgs#kicad), import PcbDoc, export gerbers + BOM + CPL from KiCad.

BOM — Semiconductors (DigiKey)

Part MPN Qty DigiKey URL
Photodiode VBPW34S 24 https://www.digikey.com/en/products/detail/vishay-semiconductor-opto-division/VBPW34S/4073399
Quad op-amp AD8618ARUZ 12 https://www.digikey.com/en/products/detail/analog-devices-inc/AD8618ARUZ/1993937
Dual LED 660/940nm VSMD66694 8 https://www.digikey.com/en/products/detail/vishay-semiconductor-opto-division/VSMD66694/7681025
N-ch MOSFET BSD840NH6327XTSA1 16 https://www.digikey.com/en/products/detail/infineon-technologies/BSD840NH6327XTSA1/5409567
MCU STM32L476RET6 1 https://www.digikey.com/en/products/detail/stmicroelectronics/STM32L476RET6/5177041
Analog MUX TMUX1104DBVR 8 https://www.digikey.com/en/products/detail/texas-instruments/TMUX1104DBVR/9685876
PWM/IO PCA9685PW,118 3 https://www.digikey.com/en/products/detail/nxp-usa-inc/PCA9685PW-118/2034325
USB isolator ADUM4160BRWZ 1 https://www.digikey.com/en/products/detail/analog-devices-inc/ADUM4160BRWZ/1861340

BOM — Passives (0603 SMD, from schematic)

Core known values (exact values need Altium schematic export):

  • 60.4k 1% x24 (TIA feedback)
  • 200pF x24 (TIA bandwidth, fc~13kHz)
  • 100nF x60 (bypass, 2 per board + ECU)
  • 4.7k x4 (I2C pullups)
  • LED current limit resistors x16

BOM — Amazon

Item URL
3.7V 1100mAh LiPo JST https://www.amazon.com/Qimoo-Battery-Rechargeable-Connector-Electronic/dp/B0CNLNGBT4
ST-LINK V2 programmer https://www.amazon.com/ST-Link-Programming-Emulator-Downloader-Random/dp/B08YZ4K3Z5
8-pin ribbon cable IDC https://www.amazon.com/DMiotech-Ribbon-Digital-Cameras-Computers/dp/B0CJYV768J
PLA filament 1.75mm https://www.amazon.com/ELEGOO-PLA-Filament-1-75mm-Printers/dp/B0C14PXRZH
Velcro strips https://www.amazon.com/VELCRO-Brand-Sticky-Fasteners-Perfect/dp/B00006IC2L
3M Micropore tape https://www.amazon.com/Micropore-Medical-Dispenser-Friendly-NonSterile/dp/B00PZ2F1Q6
Neoprene headband https://www.amazon.com/Headband-Neoprene-Hairband-Non-Slip-Snorkeling/dp/B0FB8Y968R

BOM — PCBs (JLCPCB, after gerber export)

  • 24x sensor module (25mm circular)
  • 1x ECU (112x112mm, 4-layer)
  • 1x STLINK breakout

Cost Summary

Category Cost
Semiconductors ~$130
Passives ~$15
PCBs ~$13
Amazon ~$150
Total ~$310-420

Assembly

  1. Export gerbers from KiCad (after Altium import)
  2. Order PCBs from JLCPCB
  3. Order DigiKey + Amazon parts
  4. Solder sensor modules (24x, SMD 0603 + photodiode + LED)
  5. Solder ECU (QFP-64 MCU, SOT-23 MUXes, TSSOP PWM)
  6. Wire cable harnesses (8 groups of 3 sensors)
  7. 3D print sensor capsules (STL from repo or design in OpenSCAD)
  8. Flash firmware via SWD (ST-LINK)
  9. Connect USB, run Python GUI
  10. Calibrate on forehead, verify heart rate waveform first

bci.horse Integration

  • Tree: bcf-0036 in plurigrid/horse
  • Inventory ID: planned, not yet ordered
  • Role: walk-up fNIRS fleet ($419/unit vs $50k NIRSport 2)
  • Calibrate against Artinis Brite Lite (if purchased)

Firmware

Located in firmware/STM32/fNIRS/. STM32CubeIDE project.

  • MCU: STM32L476RET6, ARM Cortex-M4 80MHz
  • ADC: 12-bit, DMA, 5kHz raw sampling, multiplexed to 1kHz effective
  • USB: CDC serial via ADUM4160 isolator
  • PWM: PCA9685 drives LED sources, alternating 660/940nm
  • SD: SDMMC logging

Software

Located in software/. Python 3.

  • Flask-SocketIO backend for real-time streaming
  • Web GUI: Plotly.js + BrainNet Viewer 3D brain mesh
  • Modified Beer-Lambert Law processing (NIRSimple library)
  • Bandpass 0.01-0.5 Hz for cortical hemodynamics
  • Correlation-based signal improvement for HbO/HbR

Related Skills

  • forester — bci.horse forest publishing (bcf-0036 is this device's tree)
  • reverse-engineering — MCP servers for Ghidra/radare2/IDA if binary analysis needed
  • binary-triage — systematic binary survey workflow
  • performing-firmware-extraction-with-binwalk — firmware extraction from embedded devices
  • protocol-reverse-engineering — reverse engineering communication protocols
  • radare2-hatchery — radare2 ecosystem tools

Altium Conversion Tools

Why This Build

The problem

Research-grade fNIRS (NIRx NIRSport 2) costs $50k-150k. PLUX biosignalsplux fNIRS sensor is $789 for 1 channel with short source-detector separation — measures superficial scalp hemodynamics, not cortical activity.

Source-detector separation is everything

Light follows a banana-shaped path through tissue. Separation controls measurement depth:

  • <10mm: scalp blood flow (artifact)
  • 30mm: gray matter (cortical hemodynamics — what we want)

  • 50mm: too much attenuation

Per Strangman et al. (PLOS ONE 2013): every 10mm increase up to ~45mm adds ~4% gray matter sensitivity. Depth sensitivity decays as S = 0.75 * 0.85^depth.

PLUX has emitter+detector in one housing = short path = scalp oximetry. NIRSport 2 uses separate optodes at 30mm = cortical imaging = $50k+. OpenNIRScap uses separate optodes at 35mm = cortical imaging = $419.

Why OpenNIRScap specifically

  • 24 channels (vs PLUX 1ch, vs DIY-fNIRS headband 4ch)
  • 35mm separation (proper cortical depth)
  • 52.3 dB SNR, 1 kHz sampling
  • Validated hemodynamic response during cognitive tasks (paper Fig. 10)
  • $419 total BOM from off-the-shelf parts
  • Fully open source (BSD-3, hardware + firmware + software)
  • Published May 2025, repo active March 2026
  • Comparison from paper (Table II): 24ch/$419/open vs 4ch/$215/open vs 1ch/$789/proprietary

The strategy for bci.horse

Build 3x OpenNIRScap ($1,257) as the walk-up fNIRS fleet. If/when a commercial reference is acquired (Artinis Brite Lite ~$6k or Cortivision Spectrum C23), use it to validate OpenNIRScap signal quality. The AFE4404 in the earlier DIY spec (bcf-0012) uses the same modified Beer-Lambert deconvolution as NIRx's proprietary pipeline — the physics is identical, only the engineering precision differs.

Key references