scholarly journals Update of fNIRS as an Input to Brain–Computer Interfaces: A Review of Research from the Tufts Human–Computer Interaction Laboratory

Photonics ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 90 ◽  
Author(s):  
Bosworth ◽  
Russell ◽  
Jacob
Keyword(s):  
Human Computer Interaction ◽  
Real Time ◽  
Near Infrared ◽  
Brain Computer Interfaces ◽  
Functional Near Infrared Spectroscopy ◽  
The Past ◽  
Computer Interfaces ◽  
Brain States ◽  
Computer Interaction

Over the past decade, the Human–Computer Interaction (HCI) Lab at Tufts University has been developing real-time, implicit Brain–Computer Interfaces (BCIs) using functional near-infrared spectroscopy (fNIRS). This paper reviews the work of the lab; we explore how we have used fNIRS to develop BCIs that are based on a variety of human states, including cognitive workload, multitasking, musical learning applications, and preference detection. Our work indicates that fNIRS is a robust tool for the classification of brain-states in real-time, which can provide programmers with useful information to develop interfaces that are more intuitive and beneficial for the user than are currently possible given today’s human-input (e.g., mouse and keyboard).

A Study of Frontal Signals in Brain Computer Interfaces: Interpretation of EEG & FNIRS

2020 ◽  
pp. 136-142
Author(s):  
S. Srilekha ◽  
B. Vanathi
Keyword(s):  
Infrared Spectroscopy ◽  
Healthy Subject ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Economic Conditions ◽  
Brain Computer Interfaces ◽  
Functional Near Infrared Spectroscopy ◽  
Computer Interfaces ◽  
Rehabilitation Devices

This paper focuses on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) comparison to help the rehabilitation patients. Both methods have unique techniques and placement of electrodes. Usage of signals are different in application based on the economic conditions. This study helps in choosing the signal for the betterment of analysis. Ten healthy subject datasets of EEG & FNIRS are taken and applied to plot topography separately. Accuracy, Sensitivity, peaks, integral areas, etc are compared and plotted. The main advantages of this study are to prompt their necessities in the analysis of rehabilitation devices to manage their life as a typical individual.

scholarly journals Real-Time Precise Human-Computer Interaction System Based on Gaze Estimation and Tracking

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Junhao Huang ◽  
Zhicheng Zhang ◽  
Guoping Xie ◽  
Hui He
Keyword(s):  
Human Computer Interaction ◽  
Real Time ◽  
Binary Classification ◽  
Gaze Estimation ◽  
State Recognition ◽  
Video Source ◽  
Interaction System ◽  
Computer Based ◽  
Computer Interaction

Noncontact human-computer interaction has an important value in wireless sensor networks. This work is aimed at achieving accurate interaction on a computer based on auto eye control, using a cheap webcam as the video source. A real-time accurate human-computer interaction system based on eye state recognition, rough gaze estimation, and tracking is proposed. Firstly, binary classification of the eye states (opening or closed) is carried on using the SVM classification algorithm with HOG features of the input eye image. Second, rough appearance-based gaze estimation is implemented based on a simple CNN model. And the head pose is estimated to judge whether the user is facing the screen or not. Based on these recognition results, noncontact mouse control and character input methods are designed and developed to replace the standard mouse and keyboard hardware. Accuracy and speed of the proposed interaction system are evaluated by four subjects. The experimental results show that users can use only a common monocular camera to achieve gaze estimation and tracking and to achieve most functions of real-time precise human-computer interaction on the basis of auto eye control.

scholarly journals Enrichment of Human-Computer Interaction in Brain-Computer Interfaces via Virtual Environments

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Alonso-Valerdi Luz María ◽  
Mercado-García Víctor Rodrigo
Keyword(s):  
Human Computer Interaction ◽  
Cognitive Processes ◽  
Interactive Systems ◽  
Memory Storage ◽  
Navigation Systems ◽  
Brain Computer Interfaces ◽  
Computer Interfaces ◽  
User Intentions ◽  
The Sixties ◽  
Computer Interaction

Tridimensional representations stimulate cognitive processes that are the core and foundation of human-computer interaction (HCI). Those cognitive processes take place while a user navigates and explores a virtual environment (VE) and are mainly related to spatial memory storage, attention, and perception. VEs have many distinctive features (e.g., involvement, immersion, and presence) that can significantly improve HCI in highly demanding and interactive systems such as brain-computer interfaces (BCI). BCI is as a nonmuscular communication channel that attempts to reestablish the interaction between an individual and his/her environment. Although BCI research started in the sixties, this technology is not efficient or reliable yet for everyone at any time. Over the past few years, researchers have argued that main BCI flaws could be associated with HCI issues. The evidence presented thus far shows that VEs can (1) set out working environmental conditions, (2) maximize the efficiency of BCI control panels, (3) implement navigation systems based not only on user intentions but also on user emotions, and (4) regulate user mental state to increase the differentiation between control and noncontrol modalities.

scholarly journals Shedding light on the prefrontal correlates of mental workload in simulated driving: a functional near-infrared spectroscopy study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Christoph F. Geissler ◽  
Jörn Schneider ◽  
Christian Frings
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Spatial Information ◽  
Mental Workload ◽  
Middle Frontal Gyrus ◽  
Brain Computer Interfaces ◽  
Functional Near Infrared Spectroscopy ◽  
Computer Interfaces ◽  
The Right

AbstractOptimal mental workload plays a key role in driving performance. Thus, driver-assisting systems that automatically adapt to a drivers current mental workload via brain–computer interfacing might greatly contribute to traffic safety. To design economic brain computer interfaces that do not compromise driver comfort, it is necessary to identify brain areas that are most sensitive to mental workload changes. In this study, we used functional near-infrared spectroscopy and subjective ratings to measure mental workload in two virtual driving environments with distinct demands. We found that demanding city environments induced both higher subjective workload ratings as well as higher bilateral middle frontal gyrus activation than less demanding country environments. A further analysis with higher spatial resolution revealed a center of activation in the right anterior dorsolateral prefrontal cortex. The area is highly involved in spatial working memory processing. Thus, a main component of drivers’ mental workload in complex surroundings might stem from the fact that large amounts of spatial information about the course of the road as well as other road users has to constantly be upheld, processed and updated. We propose that the right middle frontal gyrus might be a suitable region for the application of powerful small-area brain computer interfaces.

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