Documentation

Here you can find documentation and technical details for the miniaturized stand alone open Near InfraRed Spectroscopy (NIRS) hardware.

We are aware, that the provided design is far from perfect and can be further optimized in several ways.
However, with the presented version having passed several evaluation and verification steps and proving full functionality, we feel that the presented documentation and materials for this open NIRS instrument can significantly help anybody who is designing his own NIRS hardware from scratch.
This instrument should therefore not be viewed as complete in the sense that simple rebuilding is the first choice (even though this is possible and will result in a running NIRS instrument) but as a guidance for further designs that will then be able to profit from the experience and building blocks of the hardware, software and mechanical concept presented here.

For the most compact, revised and up to date (Jan. 2015) documentation of the openNIRS system, please see and refer to the following publication:

von Lühmann, Herff, Heger and Schultz (2015), „Towards a wireless open source instrument: functional Near-Infrared Spectroscopy in mobile neuroergonomics and BCI applications„, frontiers in Human Neuroscience, doi:10.3389/fnhum.2015.00617

For a next generation hybrid EEG-fNIRS-Accelerometer architecture that is built on top of the openNIRS technology and significantly increases hardware performance, miniaturization and functionality, please see the following new open access M3BA publication. However, if you want to use this commercially, please note that the M3BA design is patented. Feel free to contact us on the M3BA page on this website for questions regarding licensing options.

von Lühmann, Wabnitz, Sander and Müller (2016), „M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition architecture for miniaturized EEG-NIRS based hybrid BCI and monitoring„, IEEE Transactions on Biomedical Engineering, doi:10.1109/TBME.2016.2594127

Both the openNIRS and M3BA architectures are part of the following PhD thesis, where you can also find applications and experiments, and novel multimodal signal processing methods based on machine learning:

von Lühmann, Alexander (2018), „Multimodal instrumentation and methods for neurotechnology out of the lab „, Berlin Institute of Technology, doi:10.14279/depositonce-7445

A far more detailed documentation of the openNIRS hardware that is however less up to date than the openNIRS publication in frontiers can be found here:

1Introduction1
 1.1Motivation1
 1.2Objective2
2State of the Technology3
 2.1Brief Overview of History3
 2.2NIRS Principle and Signals4
 2.3NIRS Interrogation Approaches8
  2.3.1Continuous Wave NIRS8
  2.3.2Frequency Domain NIRS8
  2.3.3Time Division NIRS9
 2.4Theoretical Background10
 2.5Review of existing fNIRS Technology12
  2.5.1NIR Light Emitters13
  2.5.2NIR Light Detectors14
  2.5.3Optical Conduction16
  2.5.4Signal Amplification16
  2.5.5Probe Designs16
 2.6Fields of Application17
3System Design19
 3.1Preliminary Remakrs19
 3.2Noise, Crosstalk and Error Sources20
  3.2.1Noise Errors20
  3.2.2Crosstalk22
  3.2.3Other Error Sources22
 3.3System Concept23
 3.4Hardware Design NIRS Module26
  3.4.1NIR Light Emitter26
  3.4.2NIR Light Sensor28
  3.4.3Amplification, Lock-In Modulation and Demodulation30
  3.4.4Current Regulators34
  3.4.5Microcontroller Unit38
  3.4.6General Remarks on Layout and Design39
 3.5Hardware Design NIRS Mainboard40
  3.5.1Power Supply40
  3.5.2Analog-to-Digital Conversion41
  3.5.3Communication/Bluetooth Transmission42
  3.5.4Microcontroller Unit45
  3.5.5General Remarks on Layout and Design46
 3.6Safety Aspects47
 3.7Software Design48
  3.7.1NIRS Module48
  3.7.2NIRS Mainboard51
  3.7.3Console Userface and Control Commands56
  3.7.4LabView User Interface56
 3.8Mechanical Design61
  3.8.1NIRS Module Attachment61
  3.8.2Mainboard and Batteries64
4Evaluation and Analysis67
 4.1Evaluation of Hardware and Design67
  4.1.1PWM Signal67
  4.1.2Power Supply68
  4.1.3Current Regulators69
  4.1.4Lock-In Detection70
  4.1.5System Drift73
 4.2Physiological Verification of the System74
  4.2.1Qualitative Physiological Signals: Pulse and local Blood Pressure74
  4.2.2BCI Trials: Mental Arithmetics75
5Results and Discussion79
 5.1System Overview79
 5.2Scope and Limitations81
6Summary and Outlook83
AAppendix A87
 List of Figures103
 List of Tables105
 References107