WearLight: Towards a Wearable, Configurable Functional NIR Spectroscopy System for Noninvasive Neuroimaging

Functional near-infrared spectroscopy (fNIRS) has emerged as an effective brain monitoring technique to measure the hemodynamic response of the cortical surface. Its wide popularity and adoption in recent time attribute to its portability, ease of use, and flexibility in multimodal studies involving electroencephalography. While fNIRS is still emerging on various fronts including hardware, software, algorithm, and applications, it still requires overcoming several scientific challenges associated with brain monitoring in naturalistic environments where the human participants are allowed to move and required to perform various tasks stimulating brain behaviors. In response to these challenges and demands, we have developed a wearable fNIRS system, WearLight that was built upon an Internet-of-Things embedded architecture for onboard intelligence, configurability, and data transmission. In addition, we have pursued detailed research and comparative analysis on the design of the optodes encapsulating an near-infrared light source and a detector into 3-D printed material. We performed rigorous experimental studies on human participants to test reliability, signal-to-noise ratio, and configurability. Most importantly, we observed that WearLight has a capacity to measure hemodynamic responses in various setups including arterial occlusion on the forearm and frontal lobe brain activity during breathing exercises in a naturalistic environment. Our promising experimental results provide an evidence of preliminary clinical validation of WearLight. This encourages us to move toward intensive studies involving brain monitoring

The Validation of a Portable Functional NIRS System for Assessing Mental Workload

Portable functional near-infrared spectroscopy (fNIRS) systems have the potential to image the brain in naturalistic settings. Experimental studies are essential to validate such fNIRS systems. Working memory (WM) is a short-term active memory that is associated with the temporary storage and manipulation of information. The prefrontal cortex (PFC) brain area is involved in the processing of WM. We assessed the PFC brain during n-back WM tasks in a group of 25 college students using our laboratory-developed portable fNIRS system, WearLight. We designed an experimental protocol with 32 n-back WM task blocks with four different pseudo-randomized task difficulty levels. The hemodynamic response of the brain was computed from the experimental data and the evaluated brain responses due to these tasks. We observed the incremental mean hemodynamic activation induced by the increasing WM load. The left-PFC area was more activated in the WM task compared to the right-PFC. The task performance was seen to be related to the hemodynamic responses. The experimental results proved the functioning of the WearLight system in cognitive load imaging. Since the portable fNIRS system was wearable and operated wirelessly, it was possible to measure the cognitive load in the naturalistic environment, which could also lead to the development of a user-friendly brain–computer interface system

A Wireless fNIRS Patch with Short-Channel Regression to Improve Detection of Hemodynamic Response of Brain

The functional near-infrared spectroscopy (fNIRS) utilizes near-infrared (NIR) light sources and light detectors to non-invasively image hemodynamic responses of the brain. The unique advantages of fNIRS over the other existing brain imaging technologies led to widespread adoption of fNIRS in various brain research studies including neurology, neuroscience, clinical psychology, and psychiatry. The fNIRS systems are portable, inexpensive and provide higher temporal resolution for scanning a brain. In this paper, we present a wireless wearable fNIRS patch that has the capability of short channel regression to improve the detection of hemodynamic responses of the brain. The patch has two targeted fNIRS channels and a short-channel. The short-channel measures the background hemodynamic responses explicitly from the extracerebral region. Then it performs a regression process to eliminate background interferences from the targeted fNIRS channels to reduce the influence of the interferences. We have interfaced the patch with our laboratory-developed portable fNIRS controller. The patch and the controller are wearable. The controller is wirelessly connected to a host computer to receive commands from it and to wirelessly transmit measurement data to the host computer for the data processing and visualization. The graphical user interface (GUI) in the host computer helps the user to record and visualize fNIRS data. The experimental results of imaging prefrontal cortex of the brain using the fNIRS patch show that the patch has the potential to reduce unrelated hemodynamic activity from the targeted fNIRS channels

Region-of-interest diffuse optical tomography system

Diffuse optical tomography (DOT) using near-infrared light is a promising tool for non-invasive imaging of deep tissue. This technique is capable of quantitative reconstruction of absorption (mu(a)) and scattering coefficient (mu(s)) inhomogeneities in the tissue. The rationale for reconstructing the optical property map is that the absorption coefficient variation provides diagnostic information about metabolic and disease states of the tissue. The aim of DOT is to reconstruct the internal tissue cross section with good spatial resolution and contrast from noisy measurements non-invasively. We develop a region-of-interest scanning system based on DOT principles. Modulated light is injected into the phantom/tissue through one of the four light emitting diode sources. The light traversing through the tissue gets partially absorbed and scattered multiple times. The intensity and phase of the exiting light are measured using a set of photodetectors. The light transport through a tissue is diffusive in nature and is modeled using radiative transfer equation. However, a simplified model based on diffusion equation (DE) can be used if the system satisfies following conditions: (a) the optical parameter of the inhomogeneity is close to the optical property of the background, and (b) mu(s) of the medium is much greater than mu(a) (mu(s) >> mu(a)). The light transport through a highly scattering tissue satisfies both of these conditions. A discrete version of DE based on finite element method is used for solving the inverse problem. The depth of probing light inside the tissue depends on the wavelength of light, absorption, and scattering coefficients of the medium and the separation between the source and detector locations. Extensive simulation studies have been carried out and the results are validated using two sets of experimental measurements. The utility of the system can be further improved by using multiple wavelength light sources. In such a scheme, the spectroscopic variation of absorption coefficient in the tissue can be used to arrive at the oxygenation changes in the tissue. (C) 2016 AIP Publishing LLC

3-D GPU Based Real Time Diffuse Optical Tomographic System

3-Dimensional Diffuse Optical Tomographic (3-D DOT) image reconstruction algorithm is computationally complex and requires excessive matrix computations and thus hampers reconstruction in real time. In this paper, we present near real time 3D DOT image reconstruction that is based on Broyden approach for updating Jacobian matrix. The Broyden method simplifies the algorithm by avoiding re-computation of the Jacobian matrix in each iteration. We have developed CPU and heterogeneous CPU/GPU code for 3D DOT image reconstruction in C and MatLab programming platform. We have used Compute Unified Device Architecture (CUDA) programming framework and CUDA linear algebra library (CULA) to utilize the massively parallel computational power of GPUs (NVIDIA Tesla K20c). The computation time achieved for C program based implementation for a CPU/GPU system for 3 planes measurement and FEM mesh size of 19172 tetrahedral elements is 806 milliseconds for an iteration

A Cost-effective LED and Photodetector Based Fast Direct 3D Diffuse Optical Imaging System

A cost-effective and high-speed 3D diffuse optical tomography system using high power LED light sources and silicon photodetectors has been designed and built, that can continuously scan and reconstruct spectroscopic images at a frame rate of 2 fps. The system is experimentally validated with tissue mimicking cylindrical resin phantom having light absorbing inhomogeneities of different size, shape and contrast, and at different locations

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second

Designing and testing a wearable, wireless fNIRS patch

Optical brain monitoring using near infrared (NIR) light has got a lot of attention in order to study the complexity of the brain due to several advantages as oppose to other methods such as EEG, fMRI and PET. There are a few commercially available functional NIR spectroscopy (fNIRS) brain monitoring systems, but they are still non-wearable and pose difficulties in scanning the brain while the participants are in motion. In this work, we present our endeavors to design and test a low-cost, wireless fNIRS patch using NIR light sources at wavelengths of 770 and 830nm, photodetectors and a microcontroller to trigger the light sources, read photodetector\u27s output and transfer data wirelessly (via Bluetooth) to a smart-phone. The patch is essentially a 3-D printed wearable system, recording and displaying the brain hemodynamic responses on smartphone, also eliminates the need for complicated wiring of the electrodes. We have performed rigorous lab experiments on the presented system for its functionality. In a proof of concept experiment, the patch detected the NIR absorption on the arm. Another experiment revealed that the patch\u27s battery could last up to several hours with continuous fNIRS recording with and without wireless data transfer

A Configurable Wireless Optical Brain Monitor Based on Internet-of-Things Services

There is an increasing interest in understanding the brain in its natural state. This recently led to the wide adoption of portable brain monitors including functional Near-Infrared Spectroscopy (fNIRS) which uses near-infrared (NIR) light to capture the brain\u27s hemodynamic responses, also known as cerebral oxygenation. Nowadays, fNIRS is used in clinical settings of various medical fields including neurology, neuroscience, clinical psychology, and psychiatry. Compared to its counterpart, functional Magnetic Resonance Imaging (fMRI), fNIRS is portable and provides higher temporal resolution for scanning the hemodynamic response of the cortical layer of the brain. fNIRS has the potential to work as a smart wearable device to monitor a brain in an unconstrained setting. However, wearable implementation is challenging as the fNIRS system demands a complex circuit to drive NIR light sources and detect low intensity reflected light from the scalp. Also, the algorithm for the real-Time controlling, configuration, data acquisition, and signal processing are complex for a wearable smart fNIRS. Currently available fNIRS systems are not intelligent, completely wearable or designed as a smart body sensor network (BSN) node. In this paper, we present our recent design of a configurable fNIRS system that acts as a BSN node controlled by a remote Graphical User Interface (GUI). The presented fNIRS system is based on an embedded board where we deployed a internet-of-Things (IoT) based service-oriented architecture providing the functionality of montage configuration, fNIRS signal testing, calibration, channel selection, data collection and wireless data transmission to the GUI. This development can improve the flexibility of the fNIRS system regarding its use in natural environments where the brain functions of moving human subjects are monitored. We have experimentally evaluated working of the hardware, software, GUI and wireless data transmission, and capability of detecting hemodynamic responses