# Recent Developments in Instrumentation of Functional Near-Infrared Spectroscopy Systems
## 3 Continuous Wave fNIRS Instrumentation  
The simplest form of tissue spectroscopy methods is the continuous wave technique. It is based on the steady light illumination of tissue and the detection of the transmitted light intensity through the tissue as depicted in Figure 5. In turn, it gives an idea about the relative light attenuation without differentiating the impacts of scattering and absorption. The strongest absorbers present in the blood are the hemoglobin molecules. Hence, valuable information is accessible such as relative changes in blood volume and oxygenation can be obtained. Hence, the relative concentration level can be evaluated with high reliability and contrast from the background. So, it is not a surprise to know that it is currently the most widely used fNIRS technique. The CW technique is very useful as it is very sensitive. Moreover, the sampling rate of less than a second is doable. Furthermore, CW systems can be made to be quite affordable for spectroscopy and imaging as well. In CW systems, the source emits light at the same intensity and the changes in the intensity are measured then by a detector. The light penetration depth increases as the source-detector separation increases, but the measured intensity is less, which leads to a low SNR as illustrated in Figure 5.  
Figure 4: Eight channels montage with one source and eight detectors. fNIRS systems can be miniaturized quite easily by employing commercially available light sources and detectors. However, achieving wearable fNIRS systems is quite challenging for the fact that high requirements for signal quality and system reliability are required. Most fNIRS systems employ two wavelengths where laser diodes are used as emitters and PMTs or APDs are used as detectors. Figure 6 depicts a block diagram of such a multiwavelength system [55]. Digital gain control is used to equalize all the channels over a 20 dB range. Next, a multiplexer can be used to sample one wavelength at a time. Then, to avoid aliasing at 250 samples/s, the storage capacitor is oversampled by an analog-to-digital converter (ADC) and this gives a temporal resolution of oxygenation measurement of >0.3 s. A modified Beer-Lambert principle is used here and it should be noted that the scattering is considered both homogenous and fixed [24; 53; 56]. Utilizing all eight sources during data collection provides a sampling frequency of 6.25 Hz when the sources are lit sequentially (standard mode). It can be increased by reducing the number of sources used during data collection. Employing only half of the eight sources, for example, results in a sampling frequency of 10.42 Hz-an increase of more than 4 Hz. Detectors are connected to the main unit by optical fibers. Optical fibers consist of a core for transmitting light and a covering to both keep internal light from escaping and external light from entering. A multiwavelength approach has also been considered via selecting optimum wavelengths over the complete NIR spectrum to find the concentration changes [57]. Although development is being  
Figure 5: The source emits light at the same intensity and the changes in the intensity are measured then by the detector. The figure illustrates two detected signals successively along with the possible photon paths “banana shape” in different layers with various absorption coefficient and reduced scattering coefficient. Figure 6: The assembly of a multiwavelength, multisource, multidetector fNIRS system. made on devices and methods using this fNIRS multi-spectral approach, they have two drawbacks [58]. It features an increased computational complexity. Moreover, there is a need to reduce the incident power as light with a multiwavelength has higher total power than light with a limited number of wavelengths. Instead, one can sample at the two optimal wavelengths as many times as possible in order to achieve a higher SNR. In a pioneering work that started in 2015, [PERSON] et al. suggested a wireless fNIRS for mobile neuroergonomics and Brain-Computer Interface (BCI) Applications [59].