Classification of Cognitive Load based on Neurophysiological Features from Functional Near-Infrared Spectroscopy and Electrocardiography Signals on n-back Task

2020 ◽  
pp. 1-1
Author(s):  
Ivan Kesedzic ◽  
Marko Sarlija ◽  
Jelena Bozek ◽  
Sinisa Popovic ◽  
Kresimir Cosic
Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2362 ◽  
Author(s):  
Alexander E. Hramov ◽  
Vadim Grubov ◽  
Artem Badarin ◽  
Vladimir A. Maksimenko ◽  
Alexander N. Pisarchik

Sensor-level human brain activity is studied during real and imaginary motor execution using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation spatial dynamics exhibit pronounced hemispheric lateralization when performing motor tasks with the left and right hands. This fact allowed us to reveal biomarkers of hemodynamical response of the motor cortex on the motor execution, and use them for designing a sensing method for classification of the type of movement. The recognition accuracy of real movements is close to 100%, while the classification accuracy of imaginary movements is lower but quite high (at the level of 90%). The advantage of the proposed method is its ability to classify real and imaginary movements with sufficiently high efficiency without the need for recalculating parameters. The proposed system can serve as a sensor of motor activity to be used for neurorehabilitation after severe brain injuries, including traumas and strokes.


2020 ◽  
Vol 6 (6) ◽  
pp. 360-364
Author(s):  
Natasha Taylor ◽  
Martyn Wyres ◽  
Martin Bollard ◽  
Rosie Kneafsey

BackgroundThe use of brain imaging techniques in healthcare simulation is relatively rare. However, the use of mobile, wireless technique, such as functional near-infrared spectroscopy (fNIRS), is becoming a useful tool for assessing the unique demands of simulation learning. For this study, this imaging technique was used to evaluate cognitive load during simulation learning events.MethodsThis study took place in relation to six simulation activities, paired for similarity, and evaluated comparative cognitive change between the three task pairs. The three paired tasks were: receiving a (1) face-to-face and (2) video patient handover; observing a simulated scene in (1) two dimensions and (2) 360° field of vision; and on a simulated patient (1) taking a pulse and (2) taking a pulse and respiratory rate simultaneously. The total number of participants was n=12.ResultsIn this study, fNIRS was sensitive to variations in task difficulty in common simulation tools and scenarios, showing an increase in oxygenated haemoglobin concentration and a decrease in deoxygenated haemoglobin concentration, as tasks increased in cognitive load.ConclusionOverall, findings confirmed the usefulness of neurohaemoglobin concentration markers as an evaluation tool of cognitive change in healthcare simulation. Study findings suggested that cognitive load increases in more complex cognitive tasks in simulation learning events. Task performance that increased in complexity therefore affected cognitive markers, with increase in mental effort required.


2021 ◽  
Vol 11 (1) ◽  
pp. 45
Author(s):  
Tamara Galoyan ◽  
Kristen Betts ◽  
Hovag Abramian ◽  
Pratusha Reddy ◽  
Kurtulus Izzetoglu ◽  
...  

The goal of this study was to examine the effects of task-related variables, such as the difficulty level, problem scenario, and experiment week, on performance and mental workload of 27 healthy adult subjects during problem solving within the spatial navigation transfer (SNT) game. The study reports task performance measures such as total time spent on a task (TT) and reaction time (RT); neurophysiological measures involving the use of functional near-infrared spectroscopy (fNIRS); and a subjective rating scale for self-assessment of mental workload (NASA TLX) to test the related hypothesis. Several within-subject repeated-measures factorial ANOVA models were developed to test the main hypothesis. The results revealed a number of interaction effects for the dependent measures of TT, RT, fNIRS, and NASA TLX. The results showed (1) a decrease in TT and RT across the three levels of difficulty from Week 1 to Week 2; (2) an increase in TT and RT for high and medium cognitive load tasks as compared to low cognitive load tasks in both Week 1 and Week 2; (3) an overall increase in oxygenation from Week 1 to Week 2. These findings confirmed that both the behavioral performance and mental workload were sensitive to task manipulations.


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