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Record W6925369791 · doi:10.17632/cyhchpxwps

ECG & EEG features for mental workload and multilevel stress classification in different sexes

2024· dataset· en· W6925369791 on OpenAlexaboutno aff

Bibliographic record

VenueMendeley Data · 2024
Typedataset
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsMental arithmeticElectroencephalographyBrain–computer interfaceWorkloadTask (project management)Mental stress

Abstract

fetched live from OpenAlex

The data were collected from 66 healthy university students (21 males, 24 females in the follicular phase of the menstrual cycle, and 21 females in the luteal phase of the menstrual cycle) . The Montreal Imaging Stress Task (MIST) was modified and used in this study. A series of computer-based mental arithmetic tasks is designed to evaluate responses in control and stressful conditions. The experiments thus conducted in two separate sessions for the two conditions, which were two weeks apart. Each of the 2 sessions consisted of 7 periods: training, eyes open (EO), mental arithmetic task (MAT) on 4 consecutive levels of difficulty (arithmetic calculation level 1, AC1–arithmetic calculation level 4, AC4), and recovery. The control condition started with a training period to familiarize the subject with the experimental procedure, during which ECG and EEG signals were not recorded. During this period, the subject was presented with a series of computerized sampled questions at 4 difficulty levels of mental arithmetic tasks. Answer choices for every question were displayed on a computer screen in a sequence of integers between 0 and 9. The subject was requested to use a wireless computer mouse to click on the correct answer. Following the training period, the recordings started, and the subjects were asked to sit in a relaxed position with no movement and to focus on a black dot displayed on a computer screen for 5 minutes (the eye-open, EO, period). These requirements were critical to constructing a reliable EEG baseline with the minimum amount of artifacts caused by eye and body movements. After that, an instruction to perform mental arithmetic calculations was shown on the computer screen. The mental arithmetic task is composed of 4 levels of difficulty. Each level lasted 5 minutes. Level 1 (Arithmetic Calculation Level 1 – AC1): addition (+) and subtraction (-) of 3 single-digit numbers, e.g., 7-4+1. Level 2 (Arithmetic Calculation Level 2 – AC2): addition (+), subtraction (-), and multiplication (x) of 3 single- and double-digit numbers, e.g., 6x8-30. Level 3 (Arithmetic Calculation Level 3 – AC3): addition (+), subtraction (-), and multiplication (x) of 4 single- and double-digit numbers, e.g., 35+10-4*8. Level 4 (Arithmetic Calculation Level 4 – AC): addition (+), subtraction (-), multiplication (x), and division (/) of 4 single- and double-digit numbers, e.g., 96/4x2-11. No time limit or negative feedback messages were given to the subjects. After each question, the correct/incorrect message was displayed. After the AC4 period, the subjects relaxed and sat still for 5 minutes (the recovery period). ECG and EEG signals were recorded from the beginning of the EO period until the end of the recovery period. The protocol for the mental-stress condition was the same as it was for the control condition, but with a time limit and social evaluative threat components introduced. Several negative feedbacks were introduced to actively induce stress.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.048
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.112
GPT teacher head0.329
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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