scholarly journals Assessment of fNIRS Signal Processing Pipelines: Towards Clinical Applications

2021 ◽  
Vol 12 (1) ◽  
pp. 316
Author(s):  
Augusto Bonilauri ◽  
Francesca Sangiuliano Intra ◽  
Giuseppe Baselli ◽  
Francesca Baglio
Keyword(s):  
Signal Processing ◽  
Near Infrared ◽  
Continuous Wave ◽  
Single Channel ◽  
Model Fitting ◽  
Principal Component ◽  
Clinical Applications ◽  
Single Subject ◽  
Hemodynamic Response Function ◽  
Functional Near Infrared Spectroscopy

Functional Near-Infrared Spectroscopy (fNIRS) captures activations and inhibitions of cortical areas and implements a viable approach to neuromonitoring in clinical research. Compared to more advanced methods, continuous wave fNIRS (CW-fNIRS) is currently used in clinics for its simplicity in mapping the whole sub-cranial cortex. Conversely, it often lacks hardware reduction of confounding factors, stressing the importance of a correct signal processing. The proposed pipeline includes movement artifact reduction (MAR), bandpass filtering (BPF), and principal component analysis (PCA). Eight MAR algorithms were compared among 23 young adult volunteers under motor-grasping task. Single-subject examples are shown followed by the percentage in energy reduction (ERD%) statistics by single steps and cumulative values. The block average of the hemodynamic response function was compared with generalized linear model fitting. Maps of significant activation/inhibition were illustrated. The mean ERD% of pre-processed signals concerning the initial raw signal energy reached 4%. A tested multichannel MAR variant showed overcorrection on 4-fold more expansive windows. All of the MAR algorithms found similar activations in the contralateral motor area. In conclusion, single channel MAR algorithms are suggested followed by BPF and PCA. The importance of whole cortex mapping for fNIRS integration in clinical applications was also confirmed by our results.

scholarly journals Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation

2021 ◽  
Vol 11 (6) ◽  
pp. 701
Author(s):  
Cheng-Hsuan Chen ◽  
Kuo-Kai Shyu ◽  
Cheng-Kai Lu ◽  
Chi-Wen Jao ◽  
Po-Lei Lee
Keyword(s):  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Kernel Functions ◽  
Olfactory Stimulation ◽  
Support Vector ◽  
Hemodynamic Response Function ◽  
Functional Near Infrared Spectroscopy ◽  
Data Set

The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.

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.

CLASSIFICATION OF SCHIZOPHRENIA USING SVM VIA fNIRS

2018 ◽  
Vol 30 (02) ◽  
pp. 1850008 ◽  
Author(s):  
Mehrdad Dadgostar ◽  
Seyed Kamaledin Setarehdan ◽  
Sohrab Shahzadi ◽  
Ata Akin
Keyword(s):  
Mental Disorder ◽  
Optical Imaging ◽  
Near Infrared ◽  
Continuous Wave ◽  
Support Vector ◽  
Functional Near Infrared Spectroscopy ◽  
Neural Activities ◽  
Preliminary Examination ◽  
Invasive Method

In the present study, a classification of functional near-infrared spectroscopy (fNIRS) based on support vector machine (SVM) is presented. It is a non-invasive method monitoring human brain function by evaluating the concentration variation of oxy-hemoglobin and deoxy-hemoglobin. fNIRS is a functional optical imaging technology that measures the neural activities and hemodynamic responses in brain. The data were gathered from 11 healthy volunteers and 16 schizophrenia of the same average age by a 16-channel fNIRS (NIROXCOPE 301 system developed at the Neuro-Optical Imaging Laboratory, continuous-wave dual wavelength). Schizophrenia is a mental disorder that is characterized by mental processing collapse and weak emotional responses. This mental disorder is usually accompanied by a serious disturbance in social and occupational activities. The signals were initially preprocessed by DWT to remove any systemic physiological impediment. A preliminary examination by the genetic algorithm (GA) suggested that some channels of the recreated fNIRS signals required further investigation. The energy of these recreated channel signals was computed and utilized for signal arrangement. We used SVM-based classifier to determine the cases of schizophrenia. The result of six channels is higher than 16 channels. The results demonstrated a classification precision of about 87% in the discovery of schizophrenia in the healthy subjects.

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.

scholarly journals Signal Processing for Digital Beamforming FMCW SAR

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Qin Xin ◽  
Zhihong Jiang ◽  
Pu Cheng ◽  
Mi He
Keyword(s):  
Signal Processing ◽  
Continuous Wave ◽  
Single Channel ◽  
Pulse Repetition Frequency ◽  
Sampling Frequency ◽  
Synthetic Aperture ◽  
Signal Model ◽  
Digital Beamforming ◽  
Processing Gain ◽  
Detailed Imaging

According to the limitations of single channel Frequency Modulation Continuous Wave (FMCW) Synthetic Aperture Radar (SAR), Digital Beamforming (DBF) technology is introduced to improve system performance. Combined with multiple receive apertures, DBF FMCW SAR can obtain high resolution in low pulse repetition frequency, which can increase the processing gain and decrease the sampling frequency. The received signal model of DBF FMCW SAR is derived. The continuous antenna motion which is the main characteristic of FMCW SAR received signal is taken into account in the whole signal processing. The detailed imaging diagram of DBF FMCW SAR is given. A reference system is also demonstrated in the paper by comparing with a single channel FMCW SAR. The validity of the presented diagram is demonstrated with a point target simulation results.

scholarly journals 36 Altered Prefrontal Cortex Responses in Older Adults with Subjective Memory Complaints and Dementia During Dual-Task Gait: An Fnirs Study

2019 ◽  
Vol 48 (Supplement_4) ◽  
pp. iv9-iv12
Author(s):  
Wei-Peng Teo ◽  
Timo Rantalainen ◽  
Helen Macpherson
Keyword(s):  
Older Adults ◽  
Prefrontal Cortex ◽  
Dual Task ◽  
Near Infrared ◽  
Single Channel ◽  
Subjective Memory Complaints ◽  
Medical Systems ◽  
Subjective Memory ◽  
Functional Near Infrared Spectroscopy ◽  
Memory Complaints

Abstract In this study, we investigated the effects of walking during single-task and dual-task gait (STG and DTG) conditions, on left prefrontal cortex (LPFC) activation in older adults with subjective memory complaints (SMC) and Dementia. A total of 72 older adults (aged 65-94 yrs; 33 Healthy; 28 SMC; 11 Dementia) were recruited from the community and assisted living facilities. A portable 7m zeno walkway gait analysis mat was used to measure stride, velocity, length and duration during 4 passes of STG and DTG each. A portable single-channel functional near-infrared spectroscopy (fNIRS) device (Portalite, Artinis Medical Systems) was placed over the LPFC to measure changes in oxyhaemoglobin response (O2Hb) during STG and DTG. One-way analysis of variance (ANOVA) with bonferroni post-hoc t-test for multiple comparisons was used to determine differences between groups. Our results showed that stride velocity, duration and length during STG (all p&lt;0.05) and DTG (all p&lt;0.000) were significantly impaired in the Dementia group compared to Healthy and SMC groups, while no significant differences were observed between Healthy and SMC groups. For STG, a greater increase in O2Hb (p&lt;0.05) was observed in the Dementia group compared to the Healthy and SMC groups, while no differences were observed between Healthy and SMC. However, a significant increase and decline in O2Hb was observed during DTG in the SMC and Dementia groups respectively, compared to Healthy. Our findings indicate an altered pattern of cerebral haemodynamic response of the PFC in people with SMC and Dementia that may be indicative of cognitive demands of gait. Our findings may have implications for the use of DTG and fNIRS as a potential early biomarker for cognitive declines in older adults.

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.

Design and Development of Two Channel Portable Near Infrared Spectroscopy System for Studies of Cerebral Oxygenation in Prefrontal Cortex of Human Brain

2014 ◽  
Vol 573 ◽  
pp. 814-818
Author(s):  
S. Bagyaraj ◽  
G. Ravindran ◽  
S. Shenbaga Devi
Keyword(s):  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Human Brain ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Continuous Wave ◽  
Cerebral Oxygenation ◽  
Wave Length ◽  
Spatial Task ◽  
Functional Near Infrared Spectroscopy

Functional near infrared spectroscopy is a noninvasive, non harmful, low cost and safe optical technique that can be used to study the functional activities in the human brain. This paper describes the development of two channel Near InfraRed Spectroscopy (NIRS) system and the results of the cerebral oxygenation changes during the different cognitive tasks. The objective of the study is to design, develop a portable non-invasive continuous wave NIRS system with dual wave length for determining the hemoglobin content of the blood chromophores during different activities of the prefrontal cortex of the brain. The two channel NIRS system designed and it was tested with 20 healthy, ie.,15 males and 5 females with an average age group of 21±2.25, they were given a 2 different mental tasks such as sequential subtraction (mathematical task) and spot the difference (Visuo-spatial task) and their Oxy & de-Oxy hemoglobin concentration was measured which showed more changes during the task period when compared to relaxation in both left and right part of pre-frontal cortex.

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