Workload measurement using physiological and activity measures for validation test: A case study for the main control room of a nuclear power plant

Gan, Yu; Dong, Xiaolu; Zhang, Yijing; Zhang, Xuegang; Liu, Zhaopeng; Li, Zhizhong

doi:10.1016/j.ergon.2020.102974

Cited by 13 publications

(4 citation statements)

References 24 publications

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“…[49], active breathing resulted in a larger breathing wave amplitude when compared to passive breathing. In addition, it has been shown that higher workload reduces Breathing Wave Amplitude (BWA) [28]. Based on those earlier findings, we anticipated that 1) If the device is helpful in reducing the workload and stress, then the BWA will be higher and the BR lower during the sync and seq feedback compared to the control condition and 2) Whenever the participant is aware of their breathing, then active breathing is more likely to be performed and a larger BWA will be observed.…”

Section: Cohort Description and Main Resultsmentioning

confidence: 99%

Design and Evaluation of a Clippable and Personalizable Pneumatic-haptic Feedback Device for Breathing Guidance

Choi

Elhaouij

Lee

et al. 2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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To assist people in practicing mindful breathing and regulate their perceived workload while not disturbing the ongoing foreground task during daily routines, we developed a mobile and personalizable pneumatic-haptic feedback device that provides programmable subtle tactile feedback. The device consists of three soft inflatable actuators embedded with DIY stretchable sensors. We introduce their simple and cost-effective fabrication method. We conducted a technical and user-based evaluation of the device. The user-based evaluation focused on the personalization of the tactile feedback based on users' experience assessed during three pilot studies. Different personalization parameters have been tested, such as two tactile patterns, different levels of intensity and frequency. We collected the participants' self-reports and physiological data. Our results show that the device has the potential of a breathing guide under certain conditions. We provide the main findings and design insights from each study and suggest recommendations for developing an on-body personalizable pneumatic-haptic feedback interface.

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Section: Cohort Description and Main Resultsmentioning

confidence: 99%

Design and Evaluation of a Clippable and Personalizable Pneumatic-haptic Feedback Device for Breathing Guidance

Choi

Elhaouij

Lee

et al. 2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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“…Those sensors could detect human physiological changes as signals resulting in biometrics. Recent studies use biometrics from physiological signals such as electrodermal, cardiac and electroencephalography activities for workload analysis [10,[15][16][17][18][19] . However, most of the studies in manufacturing sectors, were mostly carried out using physical dominated tasks such as assembling and maintenance activities [8,10] .…”

Section: Introductionmentioning

confidence: 99%

Cardiac Biometrics and Perceived Workload Regression Analysis Using Random Forest Regressor in Cognitive Manufacturing Tasks

Harmayanti,

Tama,

Gapsari

et al. 2024

MECHTA

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Workload is crucial in managing and maintaining good performance of human resources and allocations. In an advanced manufacturing industry, human job functions had shifted to cognitive tasks. Thus, cognitive workload evaluation should be used to monitor worker’s workload in optimal condition. Most common tool of cognitive workload tools are perceived measurement, like NASA – TLX questionnaire. Despite of its sensitivity to capture workload felt by the workers, this subjective measurement was prone to bias. Objective measurement utilizing biometrics data of the human body during working state was useful to eliminate bias. Cardiac biometrics were one of the many that were closely related to mental activity changes. The objective of this study was to understand the relationship of cardiac biometrics to perceived workload as an indicator of cognitive workload analysis. The study utilized four biometrics, heart rate, HRV low frequency power, total frequency power and ratio of low and high frequency power, were used to analyzed a one hour long cognitive based study case. The study case was designed in a manufacturing planning context referring to manufacturing aptitude tests, to induce cognition process on 30 participants. The biometrics and NASA – TLX score result of all the participants, were then calculated as effect size standardization before input into random forest regressor model to analyze relationship between cardiac biometrics and perceived workload. The result found a moderate relationship between the two (r2 = 0.576). Features importance also showed the most impactful feature to the model is the effect size of frequency power ratio. However, it is recommended to always consider evaluating multiple cardiac biometrics in workload analysis to ensure good model performance.

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“…Mental workload has been regarded as an essential factor that substantially influences task performance (Young et al, 2015 ; Galy, 2018 ; Longo, 2018a ). As a construct, it has been widely applied in the design and evaluation of complex human-machine systems and environments such as in aircraft operation (Hu and Lodewijks, 2020 ; Yu et al, 2021 ), train and vehicle operation (Li et al, 2020 ; Wang et al, 2021 ), nuclear power plants (Gan et al, 2020 ; Wu et al, 2020 ), various human-computer and brain-computer interfaces (Longo, 2012 ; Asgher et al, 2020 ; Putze et al, 2020 ; Bagheri and Power, 2021 ) and in educational contexts (Moustafa and Longo, 2019 ; Orru and Longo, 2019 ; Longo and Orr, 2020 ; Longo and Rajendran, 2021 ), to name a few. Mental workload research has accumulated momentum over the last two decades, given the fact that numerous technologies have emerged that engage users in multiple cognitive levels and requirements for different task activities operating in diverse environmental conditions.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of the EEG Alpha-to-Theta and Theta-to-Alpha Band Ratios as Indexes of Mental Workload

Raufi

Longo

2022

Front. Neuroinform.

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Many research works indicate that EEG bands, specifically the alpha and theta bands, have been potentially helpful cognitive load indicators. However, minimal research exists to validate this claim. This study aims to assess and analyze the impact of the alpha-to-theta and the theta-to-alpha band ratios on supporting the creation of models capable of discriminating self-reported perceptions of mental workload. A dataset of raw EEG data was utilized in which 48 subjects performed a resting activity and an induced task demanding exercise in the form of a multitasking SIMKAP test. Band ratios were devised from frontal and parietal electrode clusters. Building and model testing was done with high-level independent features from the frequency and temporal domains extracted from the computed ratios over time. Target features for model training were extracted from the subjective ratings collected after resting and task demand activities. Models were built by employing Logistic Regression, Support Vector Machines and Decision Trees and were evaluated with performance measures including accuracy, recall, precision and f1-score. The results indicate high classification accuracy of those models trained with the high-level features extracted from the alpha-to-theta ratios and theta-to-alpha ratios. Preliminary results also show that models trained with logistic regression and support vector machines can accurately classify self-reported perceptions of mental workload. This research contributes to the body of knowledge by demonstrating the richness of the information in the temporal, spectral and statistical domains extracted from the alpha-to-theta and theta-to-alpha EEG band ratios for the discrimination of self-reported perceptions of mental workload.

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Workload measurement using physiological and activity measures for validation test: A case study for the main control room of a nuclear power plant

Cited by 13 publications

References 24 publications

Design and Evaluation of a Clippable and Personalizable Pneumatic-haptic Feedback Device for Breathing Guidance

Design and Evaluation of a Clippable and Personalizable Pneumatic-haptic Feedback Device for Breathing Guidance

Cardiac Biometrics and Perceived Workload Regression Analysis Using Random Forest Regressor in Cognitive Manufacturing Tasks

An Evaluation of the EEG Alpha-to-Theta and Theta-to-Alpha Band Ratios as Indexes of Mental Workload

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