Pub Date : 2022-08-30DOI: 10.1080/1463922X.2022.2114033
Jackie D. Zehr, J. Callaghan
Abstract This study aimed to mathematically characterize the ultimate compression tolerance (UCT) as a function of spinal joint posture, loading variation, and loading duration. One hundred and fourteen porcine cervical spinal units were tested. Spinal units were randomly assigned to subthreshold cyclic loading groups that differed by joint posture (neutral, flexed), peak loading variation (10%, 20%, 40%), and loading duration (1000, 3000, 5000 cycles). After the assigned conditioning test, UCT testing was performed. Force and actuator position were sampled at 100 Hz. A three-dimensional relationship between UCT, loading variation, and loading duration was most accurately characterized by a second order polynomial surface (R2 = 0.644, RMSE = 1.246 kN). However, distinct UCT responses were observed for flexed and neutral postures. A single second-order polynomial most accurately characterized the UCT – loading duration relationship (R2 = 0.905, RMSE = 0.718 kN) for flexed postures. For neutral joint postures, separate second-order polynomial equations were developed to characterize the UCT – loading duration relationship for each variation group (R2 = 0.618–0.906, RMSE = 0.617 kN–0.746 kN). These findings suggest that UCT responses are influenced by joint posture and these data may be used to inform ergonomic tools for the assessment of low back injury risk during occupational lifting.
{"title":"Towards the estimation of ultimate compression tolerance as a function of cyclic compression loading history: implications for lifting-related low back injury risk assessment","authors":"Jackie D. Zehr, J. Callaghan","doi":"10.1080/1463922X.2022.2114033","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2114033","url":null,"abstract":"Abstract This study aimed to mathematically characterize the ultimate compression tolerance (UCT) as a function of spinal joint posture, loading variation, and loading duration. One hundred and fourteen porcine cervical spinal units were tested. Spinal units were randomly assigned to subthreshold cyclic loading groups that differed by joint posture (neutral, flexed), peak loading variation (10%, 20%, 40%), and loading duration (1000, 3000, 5000 cycles). After the assigned conditioning test, UCT testing was performed. Force and actuator position were sampled at 100 Hz. A three-dimensional relationship between UCT, loading variation, and loading duration was most accurately characterized by a second order polynomial surface (R2 = 0.644, RMSE = 1.246 kN). However, distinct UCT responses were observed for flexed and neutral postures. A single second-order polynomial most accurately characterized the UCT – loading duration relationship (R2 = 0.905, RMSE = 0.718 kN) for flexed postures. For neutral joint postures, separate second-order polynomial equations were developed to characterize the UCT – loading duration relationship for each variation group (R2 = 0.618–0.906, RMSE = 0.617 kN–0.746 kN). These findings suggest that UCT responses are influenced by joint posture and these data may be used to inform ergonomic tools for the assessment of low back injury risk during occupational lifting.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"547 - 563"},"PeriodicalIF":1.6,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46345682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1080/1463922X.2022.2114034
P. Chakraborty, Savita Yadav
Abstract Fitts’ law models human psychomotor behaviour and can be used to predict the time required to complete a movement task. Although originally proposed for physical apparatus, Fitts’ law has been adopted to study how human beings use various computer input devices to perform onscreen pointing tasks. Touchscreens are now used in smartphones, tablets and other digital devices. The applicability of Fitts’ law to the interaction with touchscreen has been studied for both stationary computers and mobile devices. Researchers have been studying this problem for about forty years, but the body of work remains small and there is no consensus on whether Fitts’ law is valid for touch-based interaction. This paper reviews studies reporting positive-, null- and negative results on the applicability of Fitts’ law to interaction with touchscreen and proposing modifications to Fitts’ law especially for modelling interaction with touchscreen.
{"title":"Applicability of Fitts’ law to interaction with touchscreen: review of experimental results","authors":"P. Chakraborty, Savita Yadav","doi":"10.1080/1463922X.2022.2114034","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2114034","url":null,"abstract":"Abstract Fitts’ law models human psychomotor behaviour and can be used to predict the time required to complete a movement task. Although originally proposed for physical apparatus, Fitts’ law has been adopted to study how human beings use various computer input devices to perform onscreen pointing tasks. Touchscreens are now used in smartphones, tablets and other digital devices. The applicability of Fitts’ law to the interaction with touchscreen has been studied for both stationary computers and mobile devices. Researchers have been studying this problem for about forty years, but the body of work remains small and there is no consensus on whether Fitts’ law is valid for touch-based interaction. This paper reviews studies reporting positive-, null- and negative results on the applicability of Fitts’ law to interaction with touchscreen and proposing modifications to Fitts’ law especially for modelling interaction with touchscreen.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"532 - 546"},"PeriodicalIF":1.6,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47757461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1080/1463922X.2022.2114032
Brendan L. Pinto, K. Fewster, J. Callaghan
Abstract Prolonged driving has been linked to the development of low back pain. Methods to examine time varying postural changes of the lumbar spine during driving have been scarcely investigated. Distinguishing postural variation as movement patterns such as lumbar shifts and fidgets may provide novel insight, which may otherwise be lost with analyses that parameterize variation as a single value. This investigation aimed to identify if lumbar spine shifts or fidgets typically occur in automotive sitting and if differences occur across sex or time. An additional objective was to investigate the extent these movement patterns can capture variation across time. Forty participants (18 F, 22 M) performed a one hour driving simulation. Number, duration and amplitude of shifts and fidgets as well as the mean and standard deviation (SD) of lumbar angle were calculated. Reported discomfort and pain were also recorded. Shifts and fidgets occurred in the absence of discomfort or pain and did not vary on average across time or sex (p > 0.05). Movement patterns characterized variation with a higher resolution compared to lumbar angle SD. Identifying lumbar shifts and fidgets provide an increased potential to understand individual time varying postural responses during driving, including the development of low back discomfort or pain.
{"title":"Lumbar spine movement profiles uniquely characterize postural variation during simulated prolonged driving","authors":"Brendan L. Pinto, K. Fewster, J. Callaghan","doi":"10.1080/1463922X.2022.2114032","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2114032","url":null,"abstract":"Abstract Prolonged driving has been linked to the development of low back pain. Methods to examine time varying postural changes of the lumbar spine during driving have been scarcely investigated. Distinguishing postural variation as movement patterns such as lumbar shifts and fidgets may provide novel insight, which may otherwise be lost with analyses that parameterize variation as a single value. This investigation aimed to identify if lumbar spine shifts or fidgets typically occur in automotive sitting and if differences occur across sex or time. An additional objective was to investigate the extent these movement patterns can capture variation across time. Forty participants (18 F, 22 M) performed a one hour driving simulation. Number, duration and amplitude of shifts and fidgets as well as the mean and standard deviation (SD) of lumbar angle were calculated. Reported discomfort and pain were also recorded. Shifts and fidgets occurred in the absence of discomfort or pain and did not vary on average across time or sex (p > 0.05). Movement patterns characterized variation with a higher resolution compared to lumbar angle SD. Identifying lumbar shifts and fidgets provide an increased potential to understand individual time varying postural responses during driving, including the development of low back discomfort or pain.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"520 - 531"},"PeriodicalIF":1.6,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45843861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-08DOI: 10.1080/1463922X.2022.2107725
M. Mahdinia, I. Mohammadfam, Hamed Aghaei, M. Aliabadi, H. Fallah, A. Soltanzadeh
Abstract The present study aimed to create a Bayesian network (BN) model to manage and improve workers’ situation awareness. The 12 important variables affecting workers’ situation awareness were determined using the Fuzzy Delphi method and experts’ opinions. The data were collected using a self-administered questionnaire. The BN model was created using the Dempster-Shafer theory. The expectation-maximization algorithm was employed to determine the conditional probability tables. Belief updating was utilized to determine the variables with the strongest effects on situation awareness. Based on performance evaluation criteria of the BN model, the model performance was acceptable. Environmental distraction, safety knowledge, and fatigue were the best predictors of situation awareness. Furthermore, it was found that decreasing environmental distraction and work pressure, and improving safety knowledge were the best intervention strategies to improve workers’ situation awareness. Overall, we can conclude that the BN model is a powerful tool to create a causal model. Moreover, using belief updating as an exclusive characteristic of BN enables managers to select the best intervention strategies. The results of this study provide a basis for managers’ decision-making to improve employee safety performance in the workplaces and the proposed model can potentially be used for employee safety performance.
{"title":"Developing a Bayesian network model for improving chemical plant workers’ situation awareness","authors":"M. Mahdinia, I. Mohammadfam, Hamed Aghaei, M. Aliabadi, H. Fallah, A. Soltanzadeh","doi":"10.1080/1463922X.2022.2107725","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2107725","url":null,"abstract":"Abstract The present study aimed to create a Bayesian network (BN) model to manage and improve workers’ situation awareness. The 12 important variables affecting workers’ situation awareness were determined using the Fuzzy Delphi method and experts’ opinions. The data were collected using a self-administered questionnaire. The BN model was created using the Dempster-Shafer theory. The expectation-maximization algorithm was employed to determine the conditional probability tables. Belief updating was utilized to determine the variables with the strongest effects on situation awareness. Based on performance evaluation criteria of the BN model, the model performance was acceptable. Environmental distraction, safety knowledge, and fatigue were the best predictors of situation awareness. Furthermore, it was found that decreasing environmental distraction and work pressure, and improving safety knowledge were the best intervention strategies to improve workers’ situation awareness. Overall, we can conclude that the BN model is a powerful tool to create a causal model. Moreover, using belief updating as an exclusive characteristic of BN enables managers to select the best intervention strategies. The results of this study provide a basis for managers’ decision-making to improve employee safety performance in the workplaces and the proposed model can potentially be used for employee safety performance.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"505 - 519"},"PeriodicalIF":1.6,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49529786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-27DOI: 10.1080/1463922X.2022.2103201
Guy Cohen-Lazry, A. Degani, T. Oron-Gilad, P. Hancock
Abstract Interaction with and dependency on intelligent autonomous systems, may bring about feelings such as discomfort or fear. Users’ willingness to accept new technologies can be hampered by unwanted emotions like discomfort, making the study of the onset of discomfort essential for future technology design and implementation. Interest in discomfort has been growing but agreed-upon definitions or models are still wanted. Here, we present a theoretical model of discomfort predicated upon existing models and definitions. Our model emphasizes internal mental processes that guide the formation of discomfort. Specifically, we specify how environmental stimuli are linked to personal needs and expectations, and how that gap between internal and external factors contributes to discomfort. We conclude with a practical example of how our model can apply to the design of autonomous vehicles.
{"title":"Discomfort: an assessment and a model","authors":"Guy Cohen-Lazry, A. Degani, T. Oron-Gilad, P. Hancock","doi":"10.1080/1463922X.2022.2103201","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2103201","url":null,"abstract":"Abstract Interaction with and dependency on intelligent autonomous systems, may bring about feelings such as discomfort or fear. Users’ willingness to accept new technologies can be hampered by unwanted emotions like discomfort, making the study of the onset of discomfort essential for future technology design and implementation. Interest in discomfort has been growing but agreed-upon definitions or models are still wanted. Here, we present a theoretical model of discomfort predicated upon existing models and definitions. Our model emphasizes internal mental processes that guide the formation of discomfort. Specifically, we specify how environmental stimuli are linked to personal needs and expectations, and how that gap between internal and external factors contributes to discomfort. We conclude with a practical example of how our model can apply to the design of autonomous vehicles.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"480 - 503"},"PeriodicalIF":1.6,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45553689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-23DOI: 10.1080/1463922X.2022.2099033
S. Datta, Satyajit Chakrabarti
Abstract The main goal of this article is to develop and propose a novel ABSA method using enhanced ensemble learning (EEL) with optimal feature selection. Initially, the data from multiple applications is gathered and subjected to the preprocessing by ‘stop word removal and punctuation removal, lower case conversion and stemming’. Then, the aspect extraction is done by separating ‘noun and adjective and verb and adverb combination’. From this, the ‘Vader sentiment intensity analyzer’ is used to capture the weighted polarity feature, and then, the word2vector and ‘term frequency-inverse document frequency’ are extracted as features. The optimal feature selection using best and worst fitness-based galactic swarm optimization (BWF-GSO) is used for selecting the most significant features. With these features, ensemble learning with different classifiers like ‘recurrent neural network, support vector machine and deep belief network’ performs for handling the sentiment analysis with parameter optimization. The suggested models are helpful and generate better than the existing outcomes, according to experimental data. Through the performance analysis, the accuracy of BWF-GSO-EEL was 1.16%, 1.58%, 2.01% and 1.37% better than FF-MVO-EEL, FF-EEL, MVO-EEL and PSO-EEL, respectively. Thus, the promising performance has been observed while comparing with other algorithms.
{"title":"Enhanced ensemble learning for aspect-based sentiment analysis on multiple application oriented datasets","authors":"S. Datta, Satyajit Chakrabarti","doi":"10.1080/1463922X.2022.2099033","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2099033","url":null,"abstract":"Abstract The main goal of this article is to develop and propose a novel ABSA method using enhanced ensemble learning (EEL) with optimal feature selection. Initially, the data from multiple applications is gathered and subjected to the preprocessing by ‘stop word removal and punctuation removal, lower case conversion and stemming’. Then, the aspect extraction is done by separating ‘noun and adjective and verb and adverb combination’. From this, the ‘Vader sentiment intensity analyzer’ is used to capture the weighted polarity feature, and then, the word2vector and ‘term frequency-inverse document frequency’ are extracted as features. The optimal feature selection using best and worst fitness-based galactic swarm optimization (BWF-GSO) is used for selecting the most significant features. With these features, ensemble learning with different classifiers like ‘recurrent neural network, support vector machine and deep belief network’ performs for handling the sentiment analysis with parameter optimization. The suggested models are helpful and generate better than the existing outcomes, according to experimental data. Through the performance analysis, the accuracy of BWF-GSO-EEL was 1.16%, 1.58%, 2.01% and 1.37% better than FF-MVO-EEL, FF-EEL, MVO-EEL and PSO-EEL, respectively. Thus, the promising performance has been observed while comparing with other algorithms.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"429 - 460"},"PeriodicalIF":1.6,"publicationDate":"2022-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49597088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-07DOI: 10.1080/1463922X.2022.2095457
Vitor Rodrigues, Raoni Rocha
Abstract Participatory ergonomics relies on the involvement of people to constitute or improve their work environments. The present study aims to answer through a literature review how ergonomic interventions are performed in these environments. The research focussed on workspace design and processes related to participative ergonomics. The search in Scopus was performed for the period 2016 to 2020. From 200 articles, 28 were tabulated for content analysis encompassing the themes of ergonomic approach modes, use of intermediate objects and technological solutions adopted. The majority of the studies found were inserted in hospital, office and maritime/port environments. The results show that ergonomics approaches face diverse challenges: financial and time constraints, power asymmetries, experience levels, social, cultural and individual issues. Nevertheless, it sets out to develop skills, activities, competencies, and to organise these in a global and structured way. Further studies in a wide diversity of databases are needed to follow up the analysis of such approaches and conceptions of work activity. PRACTITIONER SUMMARY This study conducted a review of the literature on ergonomic approaches in a variety of workspaces, whether they are being transformed or designed. Attention was sought for commonalities of approaches that resulted in the topics regarding intermediate objects and the technological impact on recent ergonomic interventions. The main finding denotes a greater need to consolidate virtual and physical tools and methods and to investigate an intervention framework that is applicable to most interventions, in addition to responding to the major challenges pointed out by the articles.
{"title":"Participatory ergonomics approaches to design and intervention in workspaces: a literature review","authors":"Vitor Rodrigues, Raoni Rocha","doi":"10.1080/1463922X.2022.2095457","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2095457","url":null,"abstract":"Abstract Participatory ergonomics relies on the involvement of people to constitute or improve their work environments. The present study aims to answer through a literature review how ergonomic interventions are performed in these environments. The research focussed on workspace design and processes related to participative ergonomics. The search in Scopus was performed for the period 2016 to 2020. From 200 articles, 28 were tabulated for content analysis encompassing the themes of ergonomic approach modes, use of intermediate objects and technological solutions adopted. The majority of the studies found were inserted in hospital, office and maritime/port environments. The results show that ergonomics approaches face diverse challenges: financial and time constraints, power asymmetries, experience levels, social, cultural and individual issues. Nevertheless, it sets out to develop skills, activities, competencies, and to organise these in a global and structured way. Further studies in a wide diversity of databases are needed to follow up the analysis of such approaches and conceptions of work activity. PRACTITIONER SUMMARY This study conducted a review of the literature on ergonomic approaches in a variety of workspaces, whether they are being transformed or designed. Attention was sought for commonalities of approaches that resulted in the topics regarding intermediate objects and the technological impact on recent ergonomic interventions. The main finding denotes a greater need to consolidate virtual and physical tools and methods and to investigate an intervention framework that is applicable to most interventions, in addition to responding to the major challenges pointed out by the articles.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"413 - 428"},"PeriodicalIF":1.6,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46220940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-07DOI: 10.1080/1463922X.2022.2095458
Nina R. Ferreri, C. Mayhorn
Abstract Individual differences in user responses to malfunctions with technology are of primary interest, as this influences how a product can be improved and has not been examined extensively. Previously, individual differences in responses to technology failures have been examined in self-reported studies, but not in an experimental design. The current study expanded the findings from previous research with a mixed factorial design. Seventy-two (N = 72) undergraduate students were recruited to participate in this online study. They were asked to complete a shopping task and complete a survey about their experience. To examine individual differences in responses to technology failures, several repeated measures ANOVAs, multiple regressions, and hierarchical regressions were conducted to assess the effects of expectation and malfunction on frustration and performance. Results revealed individuals with a greater tendency to be neurotic or extraverted also tended to be more frustrated by a technology malfunction. Additionally, openness was the strongest predictor of less frustration with technology failures, while extraversion was the strongest predictor of more frustration with technology failures.
{"title":"Identifying and understanding individual differences in frustration with technology","authors":"Nina R. Ferreri, C. Mayhorn","doi":"10.1080/1463922X.2022.2095458","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2095458","url":null,"abstract":"Abstract Individual differences in user responses to malfunctions with technology are of primary interest, as this influences how a product can be improved and has not been examined extensively. Previously, individual differences in responses to technology failures have been examined in self-reported studies, but not in an experimental design. The current study expanded the findings from previous research with a mixed factorial design. Seventy-two (N = 72) undergraduate students were recruited to participate in this online study. They were asked to complete a shopping task and complete a survey about their experience. To examine individual differences in responses to technology failures, several repeated measures ANOVAs, multiple regressions, and hierarchical regressions were conducted to assess the effects of expectation and malfunction on frustration and performance. Results revealed individuals with a greater tendency to be neurotic or extraverted also tended to be more frustrated by a technology malfunction. Additionally, openness was the strongest predictor of less frustration with technology failures, while extraversion was the strongest predictor of more frustration with technology failures.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"461 - 479"},"PeriodicalIF":1.6,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43257423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-30DOI: 10.1080/1463922X.2022.2086645
Nikolay Alekseevich Korenevskiy, R. Al-kasasbeh, Fawaz Shawawreh, T. Ahram, S. Rodionova, Mahdi Salman, S. Filist, Manafaddin Namazov, A. Shaqadan, Maksim Ilyash
Abstract Prediction of cognitive dysfunctions in operators of human–machine systems is a complex process. The cognitive functions of attention and memory are negatively impacted in machine operation workers. Obtaining an accurate prediction of cognitive dysfunctions provides added value to better design machines and improve operator health. This research demonstrates a prediction model utilising hybrid fuzzy decision rules. The models use health indicators that measure energy imbalance of biologically active points, levels of psycho-emotional stress, fatigue and functional reserve (FR). We assess properties of attention as concentration, volume, selectivity, switchability, distribution and stability in operators of information-rich human–machine systems. Expert confidence in the obtained mathematical models exceeds the value of 0.85. The prediction quality was tested on representative control samples for the most vulnerable property of concentration of attention (CA) for this profession, and it was shown that such indicators of decision-making quality as diagnostic sensitivity, diagnostic specificity, diagnostic efficiency, predictive significance of positive and negative results exceed 0.85. The developed model proved useful for various applications in modern psychology, and psychophysiology assessment.
{"title":"Prediction of operators cognitive degradation and impairment using hybrid fuzzy modelling","authors":"Nikolay Alekseevich Korenevskiy, R. Al-kasasbeh, Fawaz Shawawreh, T. Ahram, S. Rodionova, Mahdi Salman, S. Filist, Manafaddin Namazov, A. Shaqadan, Maksim Ilyash","doi":"10.1080/1463922X.2022.2086645","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2086645","url":null,"abstract":"Abstract Prediction of cognitive dysfunctions in operators of human–machine systems is a complex process. The cognitive functions of attention and memory are negatively impacted in machine operation workers. Obtaining an accurate prediction of cognitive dysfunctions provides added value to better design machines and improve operator health. This research demonstrates a prediction model utilising hybrid fuzzy decision rules. The models use health indicators that measure energy imbalance of biologically active points, levels of psycho-emotional stress, fatigue and functional reserve (FR). We assess properties of attention as concentration, volume, selectivity, switchability, distribution and stability in operators of information-rich human–machine systems. Expert confidence in the obtained mathematical models exceeds the value of 0.85. The prediction quality was tested on representative control samples for the most vulnerable property of concentration of attention (CA) for this profession, and it was shown that such indicators of decision-making quality as diagnostic sensitivity, diagnostic specificity, diagnostic efficiency, predictive significance of positive and negative results exceed 0.85. The developed model proved useful for various applications in modern psychology, and psychophysiology assessment.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"359 - 384"},"PeriodicalIF":1.6,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49634265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-27DOI: 10.1080/1463922X.2022.2090027
R. Kazemi, Andrew Smith
Abstract The present study, an expert review, aimed to discuss the emerging challenges of overcoming COVID-19 from the perspective of human factors and the importance of cognitive ergonomics in helping to cope with the epidemic. Identifying these challenges and the use of cognitive ergonomics to optimize human well-being and system performance can be effective in managing COVID-19. Generally, two main preventive approaches such as social distancing and patient care or treatment approaches are being utilized in response to COVID-19. In this paper, human factors challenges that could emerge from covid-19 preventive approaches were discussed. Social distancing forces presence and increases automated systems that lead to increases in cognitive needs, mental workload, stress, etc. Challenges of treatment and health care include the increased workload of healthcare personnel, stress, changing work systems and task allocation that led to fatigue and stress, threats to patient safety, and disruption of interpersonal interactions from a cognitive ergonomic perspective. It is concluded that the challenges of coping with COVID-19 were numerous and important from the perspective of human factors and the role of cognitive ergonomics is important in controlling the disease; hence, it should be taken into consideration.
{"title":"Overcoming COVID-19 pandemic: emerging challenges of human factors and the role of cognitive ergonomics","authors":"R. Kazemi, Andrew Smith","doi":"10.1080/1463922X.2022.2090027","DOIUrl":"https://doi.org/10.1080/1463922X.2022.2090027","url":null,"abstract":"Abstract The present study, an expert review, aimed to discuss the emerging challenges of overcoming COVID-19 from the perspective of human factors and the importance of cognitive ergonomics in helping to cope with the epidemic. Identifying these challenges and the use of cognitive ergonomics to optimize human well-being and system performance can be effective in managing COVID-19. Generally, two main preventive approaches such as social distancing and patient care or treatment approaches are being utilized in response to COVID-19. In this paper, human factors challenges that could emerge from covid-19 preventive approaches were discussed. Social distancing forces presence and increases automated systems that lead to increases in cognitive needs, mental workload, stress, etc. Challenges of treatment and health care include the increased workload of healthcare personnel, stress, changing work systems and task allocation that led to fatigue and stress, threats to patient safety, and disruption of interpersonal interactions from a cognitive ergonomic perspective. It is concluded that the challenges of coping with COVID-19 were numerous and important from the perspective of human factors and the role of cognitive ergonomics is important in controlling the disease; hence, it should be taken into consideration.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":"24 1","pages":"401 - 412"},"PeriodicalIF":1.6,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47934667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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