THE EVOLUTION OF FIELD DEPLOYABLE fNIR SPECTROSCOPY FROM BENCH TO CLINICAL SETTINGS

2011 ◽  
Vol 04 (03) ◽  
pp. 239-250 ◽  
Author(s):  
KURTULUS IZZETOGLU ◽  
HASAN AYAZ ◽  
ANNA MERZAGORA ◽  
MELTEM IZZETOGLU ◽  
PATRICIA A. SHEWOKIS ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Brain Imaging ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Continuous Wave ◽  
Home Monitoring ◽  
Quantitative Information ◽  
Functional Near Infrared Spectroscopy ◽  
Operational Conditions ◽  
Britton Chance

In the late 1980s and early 1990s, Dr. Britton Chance and his colleagues, using picosecond-long laser pulses, spearheaded the development of time-resolved spectroscopy techniques in an effort to obtain quantitative information about the optical characteristics of the tissue. These efforts by Chance and colleagues expedited the translation of near-infrared spectroscopy (NIRS)-based techniques into a neuroimaging modality for various cognitive studies. Beginning in the early 2000s, Dr. Britton Chance guided and steered the collaboration with the Optical Brain Imaging team at Drexel University toward the development and application of a field deployable continuous wave functional near-infrared spectroscopy (fNIR) system as a means to monitor cognitive functions, particularly during attention and working memory tasks as well as for complex tasks such as war games and air traffic control scenarios performed by healthy volunteers under operational conditions. Further, these collaborative efforts led to various clinical applications, including traumatic brain injury, depth of anesthesia monitoring, pediatric pain assessment, and brain–computer interface in neurology. In this paper, we introduce how these collaborative studies have made fNIR an excellent candidate for specified clinical and research applications, including repeated cortical neuroimaging, bedside or home monitoring, the elicitation of a positive effect, and protocols requiring ecological validity. This paper represents a token of our gratitude to Dr. Britton Chance for his influence and leadership. Through this manuscript we show our appreciation by contributing to his commemoration and through our work we will strive to advance the field of optical brain imaging and promote his legacy.

scholarly journals Analysis of Different Classification Techniques for Two-Class Functional Near-Infrared Spectroscopy-Based Brain-Computer Interface

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Noman Naseer ◽  
Nauman Khalid Qureshi ◽  
Farzan Majeed Noori ◽  
Keum-Shik Hong
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Continuous Wave ◽  
Mental Arithmetic ◽  
Statistical Significance ◽  
Support Vector ◽  
Functional Near Infrared Spectroscopy ◽  
Linear Discriminant

We analyse and compare the classification accuracies of six different classifiers for a two-class mental task (mental arithmetic and rest) using functional near-infrared spectroscopy (fNIRS) signals. The signals of the mental arithmetic and rest tasks from the prefrontal cortex region of the brain for seven healthy subjects were acquired using a multichannel continuous-wave imaging system. After removal of the physiological noises, six features were extracted from the oxygenated hemoglobin (HbO) signals. Two- and three-dimensional combinations of those features were used for classification of mental tasks. In the classification, six different modalities, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA),k-nearest neighbour (kNN), the Naïve Bayes approach, support vector machine (SVM), and artificial neural networks (ANN), were utilized. With these classifiers, the average classification accuracies among the seven subjects for the 2- and 3-dimensional combinations of features were 71.6, 90.0, 69.7, 89.8, 89.5, and 91.4% and 79.6, 95.2, 64.5, 94.8, 95.2, and 96.3%, respectively. ANN showed the maximum classification accuracies: 91.4 and 96.3%. In order to validate the results, a statistical significance test was performed, which confirmed that thepvalues were statistically significant relative to all of the other classifiers (p< 0.005) using HbO signals.

scholarly journals Evoked Hemodynamic Response Estimation to Auditory Stimulus Using Recursive Least Squares Adaptive Filtering with Multidistance Measurement of Near-Infrared Spectroscopy

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Zhang ◽  
Xin Liu ◽  
Dan Liu ◽  
Chunling Yang ◽  
Qisong Wang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Auditory Stimulus ◽  
Near Infrared Spectroscopy ◽  
Adaptive Filtering ◽  
Near Infrared ◽  
Continuous Wave ◽  
Hemodynamic Response ◽  
Recursive Least Squares ◽  
Functional Near Infrared Spectroscopy

The performance of functional near-infrared spectroscopy (fNIRS) is sometimes degraded by the interference caused by the physical or the systemic physiological activities. Several interferences presented during fNIRS recordings are mainly induced by cardiac pulse, breathing, and spontaneous physiological low-frequency oscillations. In previous work, we introduced a multidistance measurement to reduce physiological interference based on recursive least squares (RLS) adaptive filtering. Monte Carlo simulations have been implemented to evaluate the performance of RLS adaptive filtering. However, its suitability and performance on human data still remain to be evaluated. Here, we address the issue of how to detect evoked hemodynamic response to auditory stimulus using RLS adaptive filtering method. A multidistance probe based on continuous wave fNIRS is devised to achieve the fNIRS measurement and further study the brain functional activation. This study verifies our previous findings that RLS adaptive filtering is an effective method to suppress global interference and also provides a practical way for real-time detecting brain activity based on multidistance measurement.

FUNCTIONAL NEAR-INFRARED SPECTROSCOPY–BASED ASSESSMENT OF ATTENTION IMPAIRMENTS AFTER TRAUMATIC BRAIN INJURY

2011 ◽  
Vol 04 (03) ◽  
pp. 251-260 ◽  
Author(s):  
ANNA C. MERZAGORA ◽  
MARIA T. SCHULTHEIS ◽  
BANU ONARAL ◽  
MELTEM IZZETOGLU
Keyword(s):  
Traumatic Brain Injury ◽  
Infrared Spectroscopy ◽  
Brain Injury ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quantitative Information ◽  
Functional Brain Imaging ◽  
Functional Near Infrared Spectroscopy ◽  
Attention Task ◽  
Attention Impairments

A frequent consequence of traumatic brain injury (TBI) is cognitive impairment, which results in significant disruption of an individual's everyday living. To date, most clinical rehabilitation interventions still rely on behavioral observation, with little or no quantitative information about physiological changes produced at the brain level. Functional brain imaging has been extensively used in the study of cognitive impairments following TBI. However, its applications to rehabilitation have been limited. This is due in part to the expensive or invasive nature of these modalities. The objective of this study is to apply functional near-infrared spectroscopy (fNIR) to the assessment of attention impairments following TBI. fNIR provides a localized measure of prefrontal hemodynamic activation, which is susceptible to TBI, and it does so in a noninvasive, affordable and wearable way, thus partially overcoming the limitations of other modalities. Participants included 5 TBI subjects and 11 healthy controls. Brain activation measurements were collected during a target categorization task. Significant differences were found in the hemodynamic response between healthy and TBI subjects. In particular, the elicited responses exhibited reduced amplitude in the TBI group. Overall, the results provide first evidence of the ability of fNIR to reveal differences between TBI and healthy subjects in an attention task. fNIR is therefore a promising neuroimaging technique in the field of neurorehabilitation. The use of fNIR in neurorehabilitation applications would benefit from its noninvasiveness and cost-effectiveness and the neurophysiological information obtained through the evaluation of the hemodynamic activation could provide invaluable information to guide the choice of intervention.

Algorithm Establishment with Model Experiment for Continuous-Wave Functional Near-Infrared Spectroscopy

2011 ◽  
Vol 138-139 ◽  
pp. 553-559
Author(s):  
Ting Li ◽  
Zhi Li Zhang ◽  
Yi Zheng
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Model Experiment ◽  
Near Infrared ◽  
Continuous Wave ◽  
Valsalva Maneuver ◽  
Hemoglobin Concentration ◽  
Functional Near Infrared Spectroscopy ◽  
Concentration Changes

Although functional near-infrared spectroscopy (fNIRS) has been developing as a useful tool for monitoring functional brain activity since the early 1990s, the quantification of hemoglobin concentration changes is still controversial and there are few detailed reports especially for continuous-wave (CW) instruments. By means of a two-layer model experiment mimicking hemodynamic changes in brain and mathematical analysis based on the modified Beer-Lambert law, we established an algorithm for a CW functional near-infrared spectroscopy (CW-fNIRS). The accuracy of this algorithm was validated both in comparison with direct measurements on brain tissue model and in vivo measurement upon human valsalva maneuver. This described method can also be utilized for other CW-fNIRS instruments to establish measuring algorithm.

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