Human Performance Assessment: Evaluation of Wearable Sensors for Monitoring Brain Activity

2019 ◽  
pp. 163-180 ◽  
Author(s):  
Kurtulus Izzetoglu ◽  
Dale Richards
Keyword(s):  
Performance Assessment ◽  
Human Performance ◽  
Brain Activity ◽  
Wearable Sensors

scholarly journals Beyond the low frequency fluctuations morning and evening differences in human brain

2019 ◽  
Author(s):  
Magdalena Fafrowicz ◽  
Bartosz Bohaterewicz ◽  
Anna Ceglarek ◽  
Monika Cichocka ◽  
Koryna Lewandowska ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Human Performance ◽  
Brain Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Basic Mechanism ◽  
Time Of Day ◽  
Resting State Functional Connectivity ◽  
Circadian Typology

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

scholarly journals Application of wearable EEG sensors for indoor thermal comfort measurements

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 214
Author(s):  
Silvia Angela Mansi ◽  
Ilaria Pigliautile ◽  
Camillo Porcaro ◽  
Anna Laura Pisello ◽  
Marco Arnesano
Keyword(s):  
Thermal Comfort ◽  
Brain Activity ◽  
Low Cost ◽  
Wearable Sensors ◽  
Real Life ◽  
Thermal Conditions ◽  
Ambient Temperatures ◽  
Human Thermal Comfort ◽  
Power Spectral ◽  
Wearable Eeg

Multidomain comfort theories have been demonstrated to interpret human thermal comfort in buildings by employing human-centered physiological measurements coupled with environmental sensing techniques. Thermal comfort has been correlated with brain activity through electroencephalographic (EEG) measurements. However, the application of low-cost wearable EEG sensors for measuring thermal comfort has not been thoroughly investigated. Wearable EEG devices provide several advantages in terms of reduced intrusiveness and application in real-life contexts. However, they are prone to measurement uncertainties. This study presents results from the application of an EEG wearable device to investigate changes in the EEG frequency domain at different indoor temperatures. Twenty-three participants were enrolled, and the EEG signals were recorded at three ambient temperatures: cold (16 °C), neutral (24 °C), and warm (31 °C). Then, the analysis of brain Power Spectral Densities (PSDs) was performed, to investigate features correlated with thermal sensations. Statistically significant differences of several EEG features, measured on both frontal and temporal electrodes, were found between the three thermal conditions. Results bring to the conclusion that wearable sensors could be used for EEG acquisition applied to thermal comfort measurement, but only after a dedicated signal processing to remove the uncertainty due to artifacts.

A Theory of Human Performance Assessment

1987 ◽  
Vol 31 (6) ◽  
pp. 629-633
Author(s):  
Edward M. Connelly
Keyword(s):  
Performance Assessment ◽  
Human Performance ◽  
Mathematical Function ◽  
Rank Ordering ◽  
Experimental Trials ◽  
Performance Demonstration ◽  
Selection Of

Selection of a measure of effectiveness (MOE) (a mathematical function) and using that measure to evaluate performance demonstrations (or exercises, or experimental trials) without first testing the measure, typically results in a disagreement between two ways of assigning effectiveness scores to each performance demonstration. The two ways of assigning effectiveness scores to each performance demonstration are: effectiveness scores assigned directly by the investigator and effectiveness scores assigned by the MOE selected by the investigator. The disagreement often exists even when comparing the rank ordering of the two sets of scored performance demonstrations. A disagreement between the two methods means that one method, possibly both, are not correct. The direct assignment of effectiveness scores to each performance demonstration constitutes a test of the MOE. In this paper, we argue that test is typically not conducted and if it were, the MOE (existing untested MOE's) would likely fail the test. We also argue that the investigator should not select an MOE but rather should have an authority (SME) score performance demonstrations and then synthesize an MOE that will pass the test. A method for synthesizing the MOE is presented.

The Criterion Task Set: Validation and Application

1986 ◽  
Vol 30 (1) ◽  
pp. 57-57
Author(s):  
Clark A Shingledecker
Keyword(s):  
Performance Assessment ◽  
Large Scale ◽  
Human Performance ◽  
Scale Validation ◽  
Relative Sensitivity ◽  
Assessment System ◽  
Assessment Instrument ◽  
Performance Tasks ◽  
Task Set ◽  
Criterion Task

The Criterion Task Set (CTS) is a battery of performance tasks which was developed at the Air Force Armstrong Aerospace Medical Research Laboratory. Based on an information processing stage/resource model of human performance, the CTS was designed to evaluate the relative sensitivity, diagnosticity and intrusiveness of available measures of operator workload. It has also been employed as a performance assessment instrument to evaluate the effects of stressors on hypothesized independent sources of performance capability. Since the completion of original developmental research and the implementation of the CTS in a standard hardware/software system, a number of researchers have employed the battery in applied human performance studies and in efforts which have contributed to its further refinement. The objectives of this symposium are to present accounts of six of these research projects and to provide a forum for individuals who are currently using the CTS or who are interested in potential applications of this performance assessment system. The papers presented in the symposium include a report of a large-scale validation project which has formed the basis for a CTS data base (Schlegel, Gilliland and Schlegel), as well as a study aimed at improvement of one of the tasks comprising the battery (Eggemeier and Amell). The remaining four papers describe applications of the CTS to the investigation of physiological (Wilson and McCloskey) and subjective (Acton, Reid and Perez) workload metrics, and to the study of individual differences (Gilliland, Schlegel and Dannels) and subjective arousal states (Kimball and Pond).

scholarly journals Bridging the gap between perception and action: the case for neuroimaging, AI and video games

2019 ◽  
Author(s):  
Pierre Bellec ◽  
Julie A. Boyle
Keyword(s):  
Neural Networks ◽  
Video Games ◽  
Cognitive Processes ◽  
Video Game ◽  
Large Scale ◽  
Human Performance ◽  
Brain Activity ◽  
Challenges And Opportunities ◽  
Neuroimaging Data ◽  
Planning Decision

A fundamental goal of computational neuroscience is to account for the implementation of cognitive processes in the brain, yet current models tend to focus on elementary cognitive processes. By contrast, video games have been designed to fully engage players, and require to constantly monitor the state of the game, in parallel to integrating strategic planning, decision making and taking action. While playing video games is hard, recent advances in artificial intelligence (AI) have made it possible to train deep neural networks that reach or even surpass human performance. We discuss challenges and opportunities in training artificial neural networks that could account jointly for human brain activity and behaviour during video game play. We argue that large-scale neuroimaging data may help to constrain the training of artificial networks and open new avenues for research at the intersection of neuroscience and AI.

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