ArticleBiomedical optics express2017
Detection and classification of three-class initial dips from prefrontal cortex.
Article in Biomedical optics express, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed, 125 citations in OpenAlex.
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- The changes of neuroactivity of Tui Na (Chinese massage) at Hegu acupoint on sensorimotor cortex in stroke patients with upper limb motor dysfunction: a fNIRS study.BMC complementary medicine and therapies · 2023Article
- An Isolated CNN Architecture for Classification of Finger-Tapping Tasks Using Initial Dip Images: A Functional Near-Infrared Spectroscopy Study.Bioengineering (Basel, Switzerland) · 2023Article
- Metaheuristic Optimization-Based Feature Selection for Imagery and Arithmetic Tasks: An fNIRS Study.Sensors (Basel, Switzerland) · 2023Article
- Benchmarking framework for machine learning classification from fNIRS data.Frontiers in neuroergonomics · 2023Article
- Brain-computer interface to predict impulse buying behavior using functional near-infrared spectroscopy.Scientific reports · 2022Article
- Motion artifacts removal and evaluation techniques for functional near-infrared spectroscopy signals: A review.Frontiers in neuroscience · 2022Review
- Most favorable stimulation duration in the sensorimotor cortex for fNIRS-based BCI.Biomedical optics express · 2021Article
- Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements.Brain sciences · 2021Article
- Vector Phase Analysis Approach for Sleep Stage Classification: A Functional Near-Infrared Spectroscopy-Based Passive Brain-Computer Interface.Frontiers in human neuroscience · 2021Article
- Regularized Partial Least Square Regression for Continuous Decoding in Brain-Computer Interfaces.Neuroinformatics · 2020Article
- Enhancing Communication for People in Late-Stage ALS Using an fNIRS-Based BCI System.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2020Article
- [Recognition of three different imagined movement of the right foot based on functional near-infrared spectroscopy].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2020Article
- Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions.Frontiers in neuroscience · 2020Review
- Cortical Activation During Shoulder and Finger Movements in Healthy Adults: A Functional Near-Infrared Spectroscopy (fNIRS) Study.Frontiers in human neuroscience · 2020Article
- Decoding Three Different Preference Levels of Consumers Using Convolutional Neural Network: A Functional Near-Infrared Spectroscopy Study.Frontiers in human neuroscience · 2020Article
- Performance Improvement of Near-Infrared Spectroscopy-Based Brain-Computer Interface Using Regularized Linear Discriminant Analysis Ensemble Classifier Based on Bootstrap Aggregating.Frontiers in neuroscience · 2020Article
- Reduction of Onset Delay in Functional Near-Infrared Spectroscopy: Prediction of HbO/HbR Signals.Frontiers in neurorobotics · 2020Article
- Detection of Mild Cognitive Impairment Using Convolutional Neural Network: Temporal-Feature Maps of Functional Near-Infrared Spectroscopy.Frontiers in aging neuroscience · 2020Article
- Multimodal exploration of non-motor neural functions in ALS patients using simultaneous EEG-fNIRS recording.Journal of neural engineering · 2019Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, the use of initial dips using functional near-infrared spectroscopy (fNIRS) for brain-computer interface (BCI) is investigated. Features and window sizes for detecting initial dips are also discussed. Three mental tasks including mental arithmetic, mental counting, and puzzle solving are performed in obtaining fNIRS signals from the prefrontal cortex. Vector-based phase analysis method combined with a threshold circle, as a decision criterion, are used to detect the initial dips. Eight healthy subjects participate in experiment. Linear discriminant analysis is used as a classifier. To classify initial dips, five features (signal mean, peak value, signal slope, skewness, and kurtosis) of oxy-hemoglobin (HbO) and four different window sizes (0~1, 0~1.5, 0~2, and 0~2.5 sec) are examined. It is shown that a combination of signal mean and peak value and a time period of 0~2.5 sec provide the best average classification accuracy of 57.5% for three classes. To further validate the result, three-class classification using the conventional hemodynamic response (HR) is also performed, in which two features (signal mean and signal slope) and 2~7 sec window size have yielded the average classification accuracy of 65.9%. This reveals that fNIRS-based BCI using initial dip detection can reduce the command generation time from 7 sec to 2.5 sec while the classification accuracy is a bit sacrificed from 65.9% to 57.5% for three mental tasks. Further improvement can be made by using deoxy hemoglobin signals in coping with the slow HR problem.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.