Grigory Adamovsky

Glenn Research Center, Cleveland, Ohio

Jeffrey Mackey

Vantage Partners, LLC, Brook Park, Ohio

Angela Harrivel and Tristan Hearn

Glenn Research Center, Cleveland, Ohio

Bertram Floyd

Sierra Lobo, Inc., Fremont, Ohio

Toward Adaptation of fNIRS Instrumentation to

Airborne Environments

NASA/TM—2014-216576

December 2014
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NASA Langley Research Center

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Grigory Adamovsky

Glenn Research Center, Cleveland, Ohio

Jeffrey Mackey

Vantage Partners, LLC, Brook Park, Ohio

Angela Harrivel and Tristan Hearn

Glenn Research Center, Cleveland, Ohio

Bertram Floyd

Sierra Lobo, Inc., Fremont, Ohio

Toward Adaptation of fNIRS Instrumentation to

Airborne Environments

NASA/TM—2014-216576

December 2014

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Prepared for the

Infotech@Aerospace 2013 Conference

sponsored by American Institute of Aeronautics and Astronautics

Boston, Massachusetts, August 19–22, 2013
Acknowledgments

The work has been supported by the Vehicle System Safety Technologies (VSST) Project of NASA Aviation Safety Program. The 

authors wish to express gratitude to Mr. Christopher Blasio, NASA GRC Radiation and Laser Safety Of¿ cer for useful advice, and 

Mr. Daniel Gotti of National Center for Space Exploration Research for assistance with design and construction of the headgear.

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Level of Review: This material has been technically reviewed by technical management. 
NASA/TM—2014-216576 1 

Toward Adaptation of fNIRS Instrumentation to 

Airborne Environments 

Grigory Adamovsky 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Jeffrey Mackey 

Vantage Partners, LLC 

Brook Park, Ohio 44142 

Angela Harrivel and Tristan Hearn 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Bertram Floyd 

Sierra Lobo, Inc. 

Fremont, Ohio 43420 

Abstract 

The paper reviews potential applications of functional Near-Infrared Spectroscopy (fNIRS), a 

well-known medical diagnostic technique, to monitoring the cognitive state of pilots with a focus on 

identifying ways to adopt this technique to airborne environments. We also discuss various fNIRS 

techniques and the direction of technology maturation of associated hardware in view of their potential 

for miniaturization, maximization of data collection capabilities, and user friendliness. 

Introduction 

The reduction of accident rates is of great importance in the face of increasing commercial aviation 

traffic. Even the most expert and conscientious pilots are susceptible to making errors in stressful 

situations. Intelligent cockpits of the future will interact with operators in ways designed to reduce error 

prone states and mitigate dangerous situations at the edges of human performance. 

NASA’s Aviation Safety Program has recognized the role of pilots and their ability to respond in 

critical flight situations as one of the major elements in its continuing effort to improve the safety of 

commercial flight. It has also established, as a part of the Vehicle System Safety Technologies (VSST) 

Project, a theme of technical challenges to deal with crew decision making and responses in complex 

situations. The crew decision making (CDM) technical area includes a broad range of technologies 

dealing with safe operation of piloted airspace vehicles. It has been formulated in response to safety 

concerns coupled with the historical trends and the forecasted changes ushered in by advances in global 

air transportation. CDM is aimed at developing data and technologies that enable new capabilities for 

pilots to better understand and respond safely to complex situations, thereby increasing the pilots’ ability 

to avoid, detect, and recover from adverse events that could otherwise result in accidents/incidents. 

One important aspect of this is the development of reliable, sensitive and operationally-relevant 

metrics for the state of the “human in the loop” by noninvasive, portable, safe, and inexpensive means. 

The overall goal is to reduce the effects of performance decrement and improve safety by informing 

intelligent systems of the state of the operator. Appropriate injections of mitigations and operator support 

by an intelligent cockpit may then be made before cognitive decision-making abilities are compromised. 
NASA/TM—2014-216576 2 

Monitoring of the aviation pilot’s situational awareness has become a subject of intensive studies over 

the past several years (Refs. 1 to 4). In the process of these studies, such diverse techniques as eye and 

gaze tracking and blood oxygen level monitoring have been considered. 

In this paper we will discuss issues associated with implementation in airborne environments of a 

spectroscopic blood oxygen level monitoring technique called functional Near-Infrared Spectroscopy 

(fNIRS). 

Functional Near-Infrared Spectroscopy (fNIRS) 

Near-Infrared Spectroscopy (NIS) is a medical tomographic technique to analyze structural properties 

of tissues (Refs. 5 and 6) and functional responses of a brain (Refs. 7 and 8) by non-invasively measuring 

concentration changes of oxy- and deoxy-hemoglobin (HbO2 and Hb) and cytochome oxidase (CtOx). 

Monitoring of those parameters also helps evaluating the cognitive state of the patient, for example in 

tracking the development of Alzheimer’s disease, and studying other brain-behavior relationships. The 

monitoring is usually done through utilization of two or more wavelengths of light selected such that the 

light propagation properties at those wavelengths are significantly different for oxygenated and 

deoxygenated tissues. In applications of NIS to detection of damaged or abnormal tissue regions, 

variations in the light absorption of tissue permit, for instance, an early detection of cancer. 

In functional Near-Infrared Spectroscopy (fNIRS), the light propagating at each wavelength through 

the tissue and blood-carrying vessels exhibits different properties, depending not only on the wavelengths 

used but also on the properties of the blood in the vessels. Processing information on the relative changes 

in concentration of HbO2 and Hb in blood vessels at particular locations in the brain indirectly determines 

the state of awareness of the subject or crewmember and his or her ability to make decisions or respond to 

situational changes. 

In general, the effectiveness of fNIRS applications to clinical analysis depends on several factors 

including design of electro-optic instrumentation, stability of human-machine mechanical contacts, 

“client” or subject cooperation, absorption and scattering of light by human tissue, availability of proper 

means to process and interpreted information, and other (Refs. 9 to 11). Adaptation of fNIRS to airborne 

environments adds other factors specific to the aircraft. For instance, while not considered of a significant 

importance in clinical environments, the size and weight of electro-optical instrumentation including 

signal processing will be limited when placing such instrumentation in the cockpit of an aircraft. There 

are three basic types of fNIRS instrumentation: continuous intensity, intensity modulated (or frequency 

domain), and time resolved. The first type, continuous intensity, is based on evaluation of the absorption 

of light passing through tissue. It provides intensity measurements at different wavelengths. The light 

sources in this case emit at constant intensity levels. In intensity modulated instrumentation, the light that 

enters the tissue is modulated and three parameters of the light passing through it are measured: intensity, 

phase, and modulation depth. Finally, the time resolved type employs a short pulse of light which after 

passing through tissue is spread in time. Each of these types has advantages and disadvantages with the 

continuous intensity being the most commonly used. A more detailed description of the fNIRS techniques 

and principles of their operations can be found elsewhere (Refs. 12 to 14). The hardware and hardwarerelated components of any fNIRS system can be loosely grouped as electro-optic instrumentation, 

headgear and fiber interfaces, and associated signal processing and software. In a particular system they 

are highly integrated and in many cases it is impossible to discuss one group of components without 

mentioning others. 

Table 1 outlines major areas of hardware and software related elements of fNIRS techniques. 
NASA/TM—2014-216576 3 

TABLE 1.—MAJOR INSTRUMENTATION AND SOFTWARE RELATED ELEMENTS OF fNIRS TECHNIQUES 

Elements Evaluation matrix Limitations 

Electro-optic Instrumentation Signal-to-noise ratio 

Small size and low weight 

Low power; Cost 

Operating wavelengths 

Sources and detectors 

Growing but limited vendor base 

Human-machine interface 

(headgear) and test subject 

cooperation 

User friendliness and safety 

Interface mechanical stability 

Acceptance by users/clients 

Insufficient usage data base 

Privacy concerns 

Software and signal processing Efficiency and credibility of processed 

information 

Data storage, Processor speed, Flight 

Automation firmware compatibility, 

Artifact removal algorithms 

Figure 1.—Schematic diagram of the fNIRS concept. 

Electro-Optic Instrumentation Element in fNIRS Systems 

The electro-optic instrumentation element is a key part of any fNIRS system. It consists of light 

sources emitting at particular wavelengths, photodetectors, and a system of optical fibers connecting the 

sources and detectors to a human head. Light from the sources reaches the head via optical fibers, gets 

scattered in the tissue, and a portion of the scatted light is coupled back into optical fibers and delivered to 

photodetectors for analysis. Studies have shown that in order to penetrate several centimeters through the 

tissue, the wavelength of the light should be between 600 and 900 nm (Refs. 15 and 16). Furthermore, 

absorption of light at the shorter range of the wavelengths is significantly affected by the presence of 

oxygen in the human tissue. At the same time, light at wavelengths between 800 and 850 nm experiences 

absorption that practically is not affected by the level of oxygenation (Refs. 17 and 18). 

The selection of sources and detectors is directly dependent on the light wavelength selected, and the 

configuration of the fNIRS system itself. 

Design of the instrumentation element of any fNIRS system is driven by the electrical power budget 

and associated with it the signal-to-noise ratio because of the selection of detector type. That is especially 

important in aerospace environments with limited weight and size as well as power availability. A 

schematic diagram representing the fNIRS concept is shown in Figure 1. Light emitted from a light 

source at one of the operating wavelengths is coupled into one or several optical fibers and delivered to a 

light injector placed on a human head. Through the injector, the light is sent through the skull into the 

brain. In the brain, the light experiences significant scattering and some absorption, with the absorption 

especially being dependant on both the wavelength used and the levels of both deoxy- and oxygenated 

hemoglobin in the blood. Overall, just a small portion of light is being collected by the light collector 

placed also on the head centimeters from the injector. 

Light 

Source 

Photodetector

Optical 

Fibers

Light 

Injector Light 

Collecto

Propagation of Light 

Inside Human Head

Schematics of 

Human Head
NASA/TM—2014-216576 4 

In a classical continuous intensity fNIRS configuration, the laser sources emit continuously. 

However, in practice the sources are intensity or pulse-modulated at low frequencies to increase the 

signal-to-noise ratio and to provide multiplexing and demultiplexing (Refs. 19 and 20). While the 

continuous intensity configuration of fNIRS is not suited for absolute characteristics of the tissue optical 

properties (Ref. 21), it is the most common configuration used in brain imaging (Ref. 22). 

In fNIRS systems employing high frequency intensity modulation, the modulation is achieved by 

applying a sinusoidally varying current to a laser diode junction that is under a certain constant voltage 

bias (Refs. 23 to 25). Both the constant bias and sinusoidally varying current generate optical radiation 

with corresponding DC and AC components. In the intensity modulation fNIRS both parts of radiation 

can be measured and their dimensionless ratio used as an additional parameter for data evaluation 

(Ref. 26), Furthermore, an improved signal-to-noise ratio has been reported (Ref. 27). The modulation 

frequency used has varied from 100 to 800 MHz and the modulation depth decreased significantly with 

increase in the modulation frequency. If a primary focus of the fNIRS system design were to increase the 

modulation frequency an external modulation approach could be more appropriate. The external 

frequency modulation is usually provided by an electro-optic modulator incerted directly into the path of 

optical radiation in the fiber. The intensity of that radiation is changed by varying the current or voltage 

applied to the modulator. While such direct modulation increases the modulation depth at high 

frequencies, the capability of using the AC/DC ratio of intensities will be lost. 

fNIRS systems with pulse modulated light sources are capable of providing simultaneous spatial and 

temporal information about light propagation in human tissue (Refs. 28 and 29). Light sources used in 

those systems are usually pulsed laser diodes with pulse durations from 10 ps to 10 fs and repetition rates 

up to 100 MHz. The complexity of fNIRS systems with pulse modulated light sources, is determined by 

their weight, real estate required to accommodate them, and finally the cost which makes them currently 

impractical for airborne applications. 

Headgear 

Various designs of headgear for clinical use have been reported (Refs. 30 to 32) with the main focus 

on the functionality of the entire system. With an increasing interest in the development of an fNIRS 

system capable of operating on a human in motion, the efficiency of the headgear design started to attract 

attention (Ref. 33). 

The main sources of power losses in the fNIRS system are coupling losses on interfaces. Owing to the 

fact that the human tissue is a highly scattering medium, most of the losses occur during ingress and 

egress of the light and it propagation through the human head. Thus, the signal to noise ratio can also be 

increased by improving the coupling of the injectors to the scalp. This issue has been addressed in a 

number of publications (Refs. 34 to 37). Design of headgear plays an important role in the acceptance of 

fNIRS techniques by the clients including the pilot community and safety regulators. Ease of operation 

and comfort are also criteria used in the design. 

To evaluate the use of gradient index (GRIN) lenses to improve signal injection and collection, we 

considered two configurations. Gray matter phantoms were used to mimic the absorption and scattering 

properties of human brain tissue. Also, the light at two wavelengths, 690 and 830 nm, was brought to the 

injectors via commercially available multimode fiber mode fiber with 50 Pm core diameter. Furthermore, 

the GRIN lenses were used as collectors to gather light scattered in the phantom. 

Figure 2 shows the first two potential designs of optical injectors. In these two cases, as shown in the 

figure, the fibers are placed on the air-phantom interface and GRIN lenses are positioned in the plane 

normal to that interface. In Figure 2(a) the injector is a right angle prism (RA Prism) which couples the light 

into the phantom by changing the direction of the light propagation by 90°. Such configuration permits 

continuing spreading of light after it exists the fiber and penetrates a wider but shallower area of the 

phantom. The injector shown in Figure 2(b) is a combination of a right angle prism and GRIN lens. The 

incorporation of a GRIN lens provides collimation of the light and a deeper penetration within the phantom. 
NASA/TM—2014-216576 5 

Figure 2.—Examples of optical injector configurations: (a) Injector with right angle prism; 

(b) Injector with right angle prism and GRIN lens. 

Figure 3.—Example of the injector—collector configuration with GRIN 

lenses and mutual inclination. 

In the third configuration shown in Figure 3 the injector is a GRIN lens coupled to the fiber and the 

collector is also a GRIN lens and they both are facing the same phantom-air interface. A slight inclination 

of both injector and collector should enhance the directional coupling of light passing through the 

phantom material. However, this must be balanced against the subject’s comfort. 

While other configurations of injectors are potentially available, the GRIN lens approach has shown 

to be the most promising of those considered. Most designs and numerical analyses of the GRIN lensbased probes have been done for a single wavelength operation (Refs. 38 and 39). In fNIRS two 

wavelengths are being used and effects of GRIN lens on optical beams at those wavelengths are different. 

Figure 4 shows calculated spot diagrams of optical beams at two wavelengths, 690 nm (blue dots) and 

830 nm (red dots) after passing through a GRIN lens. The GRIN lens focuses the 690 nm wavelength 

beam at a distance of 7 mm from the exit aperture. The figure also shows clearly spreading of the beam at 

830 nm wavelength. 

Thus, owing to the fact that fNIRS employs two wavelengths, better GRIN lens designs are needed to 

improve the coupling efficiency of the light into the human tissue. Furthemore, tests need to be performed 

on human volunteers in order to assess this light injector design’s effectiveness at penetrating the 

cerebral-spinal fluid barrier and achieving cleaner scattered signals from the brain’s gray matter.

Signal Processing 

Minuaturization of fNIRS instrumentation involves development of compact modulation schemes to 

drive two light sources in a timely prescribed manner. Figure 5 demonstrates a laboratory prototype of 

electronic setup that permits multiplexing of modulated optical signals generated by two lasers at 690 and 

830 nm. 
NASA/TM—2014-216576 6 

Figure 4.—Calculated spot diagrams 

of optical beams at 690 nm (blue 

dots) and 830 nm (red dots) after 

passing through a GRIN lens. 

Figure 5.—Laboratory electronic setup to multiplex two modulated optical signals 

generated by two lasers. 

 
NASA/TM—2014-216576 7 

The fNIRS systems usually involve headgears with multiple light injectors and collectors. The 

injectors and collectors are connected correspondingly to light sources and detectors via optical fibers. In 

airborne environments, in order to provide optical power to multiple injectors from light sources and 

deliver optical power from multiple collectors to photodetectors efficient optical power delivery 

multiplexing and demultiplexing techniques should be devise. Such techniques, in addition to channeling 

optical signals between the source and detector, should also minimize the number of connectorizing 

fibers. Thus, a properly designed optical signal delivery and collection configuration permits construction 

of a compact and efficient system with the optimum number of sources and detectors and significaltly 

reduced number of connecting fibers. Figures 6 and 7 show examples of pulsed multiplexing techniques 

that deliver light at two operational wavelengths, 690 and 830 nm, to four optical injectors on one single 

headgear unit. 

Figure 6 has two sets of light sources, either light emitting diodes or lasers. Each set has one light 

source emitting light at 690 nm and the other one at 830 nm. Light sources in each set are pulse 

modulated in time with identical duty factor. In this figure the modulating frequencies for the light 

sources with similar wavelengths are shown to be identical. However, different modulating frequencies 

could be used as well to provide additional light source discrimination. The duty factors used in different 

sets may does not have to be identical. 

Figure 6.—Example of a combined frequency-pulse multiplexed optical radiation delivery system. 

 
NASA/TM—2014-216576 8 

Figure 7.—Example of a combined frequency-pulse multiplexed optical radiation delivery system with asynchronous 

modulation of the sources. 

Figure 7 shows another configuration with multiplexed light sources. It differs from the one depicted 

in Figure 6 by having additional asynchronous modulation of the light sources. 

Numerical Analysis 

For continuous wave fNIRS, the relative concentration change in oxy- and deoxy-haemoglobin on a 

single channel are related to the optical intensities at two operating wavelengths measured from the 

corresponding instrument (Ref. 40). Once relative changes in the concentration of the hemoglobin species 

have been determined, this data must be further post-processed to remove artifacts, filter noise, and 

ultimately classify the operator state. The use of fNIRS for state classification in an operational 

environment necessitates identification of data processing procedures which are demonstrably sufficient 

for delimiting between separable operator states, yet fast enough to operate under near real-time 

constraints. Solutions to the modified Beer-Lambert law can be computed by application of a single 

 
NASA/TM—2014-216576 9 

matrix-vector product. However, the filtering and classification procedures used to further process fNIRS 

data may be collectively more computationally expensive, depending on the exact post-processing 

procedures selected. 

The ability to effectively distinguish between operator states using fNIRS is greatly enhanced by 

removing noise and artifacts from the data prior to conducting state classification. Many popular methods 

for filtering signals can be applied to fNIRS data to achieve this. Among them are wavelet filtering, blind 

source separation, and phase-adaptive Kalman filtering. 

Wavelet filtering methods have recently been used to great effect to aid in the processing of fNIRS 

data (Refs. 41 to 44). Among inherent features of discrete wavelet transforms that motivate their use for 

processing of fNIRS data are abilities to compress, denoise, and remove artifacts from single- and 

multidimensional digital signals. For example, the wavelet coefficients of digital signals tends to be 

sparse, allowing for efficient compression of data in wavelet transform domain. Wavelet transforms allow 

for the characterization of features within a signal to be examined at a variety of spatial or temporal 

scales, often referred to as Multi-Resolution Analysis (MRA). The wavelet coefficients of many digital 

signals tend to be uncorrelated in the transform domain, allowing for the de-correlation of independent 

signal features from background noise. And lastly, since each wavelet coefficient represents the content of 

the analyzed signal partially localized in both space (or time) and frequency, wavelet transforms provide 

simultaneous partial spatial and frequency localizations. 

Since applications of fNIRS typically involve the use of multiple channels of input data, denoising 

and artifact removal could also be potentially achieved using blind source separation techniques. Blind 

source separation techniques are algorithms which seek to systematically identify and separate unknown 

signals given a collection of mixed signal and noise data, without a priori knowledge of the underlying 

mixing process. These methods typically operate by iteratively minimizing some mutual measure of 

statistical independence (such as sample correlation) between lists of given data, under the assumption of 

an overall linear mixing process. 

Principal component analysis (PCA) and independent component analysis (ICA) are two popular 

methods of blind source separation and their applications to fNIRS for both offline and real time 

processing are well described in the literature (Refs. 45 to 49). 

Phase-adaptive Kalman filtering is another technique that has been recently introduced. It is specific 

to frequency domain fNIRS instrumentation (Ref. 50) and involves the application of an adaptive Kalman 

filter to the computed values of hemoglobin. In the application of the technique the intensity of the 

Kalman filter applied to each channel is tuned according to the variability of the corresponding phase shift 

channel. The principal behind this procedure is that high variation in the phase shift channel is associated 

with poor coupling of the associated optrode to the skin. Such a measure, taken over a short frame of 

time, provides a strong indicator of motion artifacts and an overall poor signal-to-noise ratio within that 

same block of time. The method has a number of advantages over alternative filtering operations that 

have been described. It does not introduce ringing or overshooting artifacts at the endpoints of the data, as 

certain combinations of wavelet filters and boundary conditions may introduce while conducting wavelet 

filtering (Ref. 51). In contrast to PCA or ICA, since this filtering is performed independently for each 

channel, it is applicable for cases where there are limited channels (or even a single channel) of interest. 

Discussion 

Currently used commercial fNIRS instrumentation is designed for hospitals and other clinical or 

laboratory environments. To make the fNIRS technology suitable for airborne applications, the 

conventional approaches should be reevaluated to make the instrumentation small, light, airworthy, and 

pilot-friendly. 

The design of the entire system should be based on the minimum resources availability. That includes 

space and weight limitations as well as low power consumption. While a broad range of optical sources, 

detectors, and fiber optic components is available for operational wavelengths in the communication 

 
NASA/TM—2014-216576 10 

range, the wavelength range from 600 to 900 nm still lacks similar diversity. Thus, with a relatively 

limited vendor’s base, configurations of the optical signal delivery and collection system should be 

designed to achieve the maximum signal-to-noise ratio and maximum efficiency. 

The design of headgear should provide, in addition to functionality, comfort and safety during pilot’s 

involvement in cockpit activities. The issue of comfort and client cooperation should be addressed by 

minimizing the number of fiber optic links connecting the headgear with signal processing units including 

optical sources and detectors. Furthermore, the design of the headgear itself should be user friendly and 

not restrictive. Multiplexing schemes should be developed to minimize the number of fiber optic cables 

connecting the headgear with the signal processing equipment without negative effects on the signal-tonoise ratio. Moreover, development of appropriate wireless configurations should be considered to 

remove any constrains on the movement of pilots in the cockpit. 

Safety issues should also be considered in the process of selection of optical sources. While the 

current safety standards regarding minimum permissible exposure to optical radiation regulate the human 

skin exposure (Ref. 52), no such standards exist when the radiation is applied to human head. Effects of a 

long-term exposure of human scalp and brain tissue to high power highly focused optical radiation in 

600 to 900 nm wavelength range with potentially deep penetration have not been fully studied. 

The software for real time data processing should be developed under an assumption of constrained 

computational resources specific to aviation data systems. Numerical models and software for such 

conditions are being currently developed (Refs. 52 and 53) and their adaptation to cockpit applications of 

fNIRS would further enhance the technology. 

Finally, the cockpit environment requires a strict certification for any equipment brought to it. 

Therefore, the fNIRS instrumentation developed for airborne environments should have low 

electromagnetic emission and minimum electromagnetic interference with the already existing equipment. 

Conclusion 

While the fNIRS has found wide applications in the medical field the use of the technology on human 

subjects in airborne environments is practically nonexistent. One of the issues detrimental to the technology 

incertion into such environments is a lack of suitable instrumentation packages and associated software. 

The paper clearly identifies major areas in the development and implementation of instrumentation 

and software related elements for airborne fNIRS systems. It also suggests a path for the technology 

maturation as articulated in the discussion section. As fNIRS is shown to be useful for detecting cognitive 

state and improving aviation safety, the technical maturation of these elements specifically toward use in 

airborne environments will become more warranted. 

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