Human Performance Factors Research Articles

Functional Resonance Analysis Method and Human Performance Factors Identifying Critical Functions in Chemical Process Safety

Functional Resonance Analysis Method and Human Performance Factors Identifying Critical Functions in Chemical Process Safety

Single port robotic radical prostatectomy versus multi-port robotic radical prostatectomy: A human factor analysis during the initial learning curve.

Studies have thus far neglected to evaluate the impact of the da Vinci single port (SP) robotic platform on surgeon experience and operating room efficiency. We sought to assess the effect of the SP platform on surgeon cognitive load measures during robotic assisted laparoscopic prostatectomy (RALP). We prospectively compared the first 20 SP-RALPs performed at our institution to 20 multi-port (MP)-RALPs performed by a single experienced robotic surgeon. Three multi-dimensional assessment tools were used to evaluate mental and surgical workload, teamwork and workflow disruptions. No statistically significant differences were found between the MP-RALP and SP-RALP cohorts when evaluated by NASA Task Load Index, Surgery Task Load Index and Observational Teamwork Assessments. The SP robotic platform did not adversely affect human factor performance of the surgeon during RALP. Multi-institutional validation will be necessary to confirm these initial findings.

The Intersection of Advancing Technology and Human Performance

Abstract Today's sensory and processing technologies are perceptive and precise. They can discern the environment, solve complicated problems, make assessments, and learn from experience. Although they do not think the way humans do, they can replicate many human intellectual aptitudes. Throughout the last several decades, companies have implemented advanced technology and increasingly removed the human from many aspects of nuclear operation. There are many advantages to this transition, but, like any system modification, failures inevitably manifest. In the instance of this article, human errors have resulted and have accounted for several accidents at nuclear facilities in the United States due to this transition. The accidents at these facilities due to human error often result in plant shutdowns, unnecessary expenses, and have the capacity to be problematic for people, the facilities, and environments. This article explores the context surrounding the complexity of changing technologies at the nuclear facilities and the potential exacerbation of problems caused by human error when technology advancements concerning operator interaction with control systems are implemented. To understand the complexity surrounding the human interaction with advancing technologies, the concepts of human performance and human factors are examined and then the impact of these concepts within the framework of advancing technology are applied to the operation of nuclear facilities. This review draws attention to the vulnerabilities due to human error at nuclear facilities within the context of continually advancing technology and sheds insight on the role human performance and human factors have on system design and the resulting outcome.

Effect of Human Factor Performance on the Productivity of a Manual Assembly Line

Effect of Human Factor Performance on the Productivity of a Manual Assembly Line

Are divergence point analyses suitable for response time data?

Estimating the time course of the influence of different factors in human performance is one of the major topics of research in cognitive psychology/neuroscience. Over the past decades, researchers have proposed several methods to tackle this question using latency data. Here we examine a recently proposed procedure that employs survival analyses on latency data to provide precise estimates of the timing of the first discernible influence of a given factor (e.g., word frequency on lexical access) on performance (e.g., fixation durations or response times). A number of articles have used this method in recent years, and hence an exploration of its strengths and its potential weaknesses is in order. Unfortunately, our analysis revealed that the technique has conceptual flaws, and it might lead researchers into believing that they are obtaining a measurement of processing components when, in fact, they are obtaining an uninterpretable measurement.

KLASTERISASI KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN INDIKATOR KINERJA PEMBANGUNAN

The problem of inequality in development between regencies/cities in Central Java still occurs even though economic development in the province is quite successful. To overcome this, a regional-based policy is needed. This study aims to cluster regions based on development performance indicators of human, infrastructure, and economy to support regional-based policy making. Principal component analysis (PCA) and factor analysis are used to reduce development performance variables that are correlated, while cluster analysis is used to cluster regencies/cities based on development performance indicators. From PCA and factor analysis formed 3 factors of human development performance, 3 factors of infrastructure development performance, and 2 factors of economic development performance, while cluster analysis produced 5 regencies/cities clusters. Development performance of human is high, infrastructure is very high, and economy is high owned by Cluster 1, which consists of 4 cities. Cluster 2 characterized by development performance of human is very high, infrastructure is high, and economy is very high, consisting of 1 city. Cluster 3 characterized by development performance of human is very low, infrastructure is medium, and economy is medium, consists of 7 regencies. Cluster 4 characterized by development performance of human is medium, infrastructure is low, and economy is low, consists of 12 regencies. Ten other regencies and one city are located in Cluster 5 with the characteristics development performance of human is high, infrastructure is high, and economy is low.

Work Standardization and Anthropometric Workstation Design as an Integrated Approach to Sustainable Workplaces in the Manufacturing Industry

Poor workstation designs represent a risk factor for operators in assembly production lines. Anthropometric design of workstations facilitates the sustainable development of the workplace. This paper proposes a novel integrated approach about work standardization and anthropometric workstation design as a strategy to increase human factor performance as well as the productivity index in manufacturing companies. The integrating approach is presented through a case study in a publishing press company with operators who perform manual and mechanical tasks in production lines in the box assembly department. Currently, the company’s production capacity is below demand, and in order to satisfy customers’ requirements, the company pays a lot of overtime to operators. In order to solve this problem, the integrated approach was applied. The findings indicated that inefficient movements and body postures in operators decreased from 230 to 78, and the standard time was reduced from 244 to 199 s for each assembled box. In addition, the production rate increased by 229 units per assembly line per day, and overtime was eliminated. Therefore, the novel integrated approach allows the increase of sustainability in the company and the operators’ well-being by making a better use of the human factor, eliminating overtime, and increasing production capacity.

Human Factors Contributions to the Development of Standards for Displays of Unmanned Aircraft Systems in Support of Detect-and-Avoid.

The aim is to provide a high-level synthesis of human factors research that contributed to the development of detect-and-avoid display requirements for unmanned aircraft systems (UAS). The integration of UAS into the U.S. National Airspace System is a priority under the Federal Aviation Administration's Modernization and Reform Act. For UAS to have routine access to the National Airspace System, UAS must have detect-and-avoid capabilities. One human factors challenge is to determine how to display information effectively to remote pilots for performing detect-and-avoid tasks. A high-level review of research informing the display requirements for UAS detect-and-avoid is provided. In addition, description of the contributions of human factors researchers in the writing of the requirements is highlighted. Findings from human-in-the-loop simulations are used to illustrate how evidence-based guidelines and requirements were established for the display of information to assist pilots in performing detect-and-avoid. Implications for human factors are discussed. Human factors researchers and engineers made many contributions to generate the data used to justify the detect-and-avoid display requirements. Human factors researchers must continue to be involved in the development of standards to ensure that requirements are evidence-based and take into account human operator performance and human factors principles and guidelines. The research presented in this paper is relevant to the design of UAS, the writing of standards and requirements, and the work in human-systems integration.

Protected Code Stroke: Hyperacute Stroke Management During the Coronavirus Disease 2019 (COVID-19) Pandemic.

Background and Purpose—Hyperacute assessment and management of patients with stroke, termed code stroke, is a time-sensitive and high-stakes clinical scenario. In the context of the current coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-CoV-2 virus, the ability to deliver timely and efficacious care must be balanced with the risk of infectious exposure to the clinical team. Furthermore, rapid and effective stroke care remains paramount to achieve maximal functional recovery for those needing admission and to triage care appropriately for those who may be presenting with neurological symptoms but have an alternative diagnosis.Methods—Available resources, COVID-19-specific infection prevention and control recommendations, and expert consensus were used to identify clinical screening criteria for patients and provide the required nuanced considerations for the healthcare team, thereby modifying the conventional code stroke processes to achieve a protected designation.Results—A protected code stroke algorithm was developed. Features specific to prenotification and clinical status of the patient were used to define precode screening. These include primary infectious symptoms, clinical, and examination features. A focused framework was then developed with regard to a protected code stroke. We outline the specifics of personal protective equipment use and considerations thereof including aspects of crisis resource management impacting team role designation and human performance factors during a protected code stroke.Conclusions—We introduce the concept of a protected code stroke during a pandemic, as in the case of COVID-19, and provide a framework for key considerations including screening, personal protective equipment, and crisis resource management. These considerations and suggested algorithms can be utilized and adapted for local practice.

Applying Psychology to Improve Electrical Safety [Pathways

Discusses the use of psychology to improve safety in the workplace. It is helpful for us to allow expert knowledge from humanistic sciences like psychology to inform our understanding of the linkage between human performance factors and safety in our everyday workplace.

Evaluating the human performance factors of air traffic control in Thailand using Fuzzy Multi Criteria Decision Making method

The paper aims to identify and evaluate the factors influencing the human performance of Air Traffic Control (ATC) in Thailand. The objective of the study has been operationalized utilizing the extended SHEL model of ergonomics. Fuzzy Graded Mean Integration method has been employed to establish the importance and Fuzzy Additive Ratio Assessment method was utilized to measure actual performance of the factors on the response received from all ten air traffic control centers of Thailand. The finding of study facilitates the insights for improvement of various dimensions and constructs for an effective human performance management for ATC in Thailand. The study fulfills the theoretical gap by employing the Fuzzy Multi Criteria Decision Making (MCDM) method of identifying and measuring human performance in ATC.

A dynamic human reliability model for marine and offshore operations in harsh environments

Human activities, including design, construction, operation, management and maintenance are all a predominant part of the daily tasks in offshore operations. It is not surprising to observe major failures are related to human error, since humans are susceptible to making mistakes. Due to the high level of uncertainty in human activities, predicting all causes of human errors is not an easy process. This may lead to inaccurate results which may affect the overall safety and reliability of marine operations. Evaluation of human endurance during activity on board is a key factor in minimizing risk of human failure. This study aims to examine uncertainties over the time of the marine operation to estimate accurate human reliability assessment. A framework is developed to model the uncertainty of human performance factors by considering a hydrodynamic analysis of the structure along with a subjective analysis of human activities under different weather conditions. Subsequently, a model based on Dynamic Bayesian approach is developed to evaluate the time duration effect on human performance throughout the operation. The developed methodology has been applied to a case study of an offshore vessel storing extracted oil. The framework demonstrates that probability of human failure increases towards the end of its operational days, however the high variation in human reliability is greatly dependent on weather conditions. The present study is able to improve the safety of human life in marine operations by predicting the reliability of performances as a function of time during a specific operation.

On Linking of Task Analysis in the HRA Procedure: The Case of HRA in Offshore Drilling Activities

Human reliability analysis (HRA) has become an increasingly important element in many industries for the purpose of risk management and major accident prevention; for example, recently to perform and maintain probabilistic risk assessments of offshore drilling activities, where human reliability plays a vital role. HRA experience studies, however, continue to warn about potential serious quality assurance issues associated with HRA methods, such as too much variability in comparable analysis results between analysts. A literature review highlights that this lack of HRA consistency can be traced in part to the HRA procedure and a lack of explicit application of task analysis relevant to a wide set of activity task requirements. As such, the need for early identification of and consistent focus on important human performance factors among analysts may suffer, and consequently, so does the ability to achieve continuous enhancements of the safety level related to offshore drilling activities. In this article, we propose a method that clarifies a drilling HRA procedure. More precisely, this article presents a novel method for the explicit integration of a generic task analysis framework into the probabilistic basis of a drilling HRA method. The method is developed and demonstrated under specific considerations of multidisciplinary task and well safety analysis, using well accident data, an HRA causal model, and principles of barrier management in offshore regulations to secure an acceptable risk level in the activities from its application.

The contributions of human factors on human error in Malaysia aviation maintenance industries

Aviation maintenance is a multitasking activity in which individuals perform varied tasks under constant pressure to meet deadlines as well as challenging work conditions. These situational characteristics combined with human factors can lead to various types of human related errors. The primary objective of this research is to develop a structural relationship model that incorporates human factors, organizational factors, and their impact on human errors in aviation maintenance. Towards that end, a questionnaire was developed which was administered to Malaysian aviation maintenance professionals. Structural Equation Modelling (SEM) approach was used in this study utilizing AMOS software. Results showed that there were a significant relationship of human factors on human errors and were tested in the model. Human factors had a partial effect on organizational factors while organizational factors had a direct and positive impact on human errors. It was also revealed that organizational factors contributed to human errors when coupled with human factors construct. This study has contributed to the advancement of knowledge on human factors effecting safety and has provided guidelines for improving human factors performance relating to aviation maintenance activities and could be used as a reference for improving safety performance in the Malaysian aviation maintenance companies.

Data collection assessment for the human performance analysis in nuclear installations

Abstract The purpose of this paper is to provide a good knowledge and understanding on the main factors influencing human performance in complex systems operation. Identification and establishment of the necessary data for human factor performance analysis in a socio-technical context based on the analysis of HRA methods are performed. An evaluation of the techniques used for collecting and characterization of necessary data for HRA (observation, questionnaire, interview, task analysis, change analysis, simulator, expert judgement) is achieved also. The necessary data to perform HRA for the TRIGA reactor operation, for activities of the post-irradiation examination laboratory and activities of the radioactive waste plant treatment from RATEN ICN Pitesti were obtained. Recommendations on how to obtain data and knowledge related to development of methodical framework of HRA data collection, characterization and evaluation are also presented in this paper.

CONTROLLING PHYSICAL INTERACTIONS: HUMANS DO NOT MINIMIZE MUSCLE EFFORT.

Physical interaction with tools is ubiquitous in functional activities of daily living. While tool use is considered a hallmark of human behavior, how humans control such physical interactions is still poorly understood. When humans perform a motor task, it is commonly suggested that the central nervous system coordinates the musculo-skeletal system to minimize muscle effort. In this paper, we tested if this notion holds true for motor tasks that involve physical interaction. Specifically, we investigated whether humans minimize muscle forces to control physical interaction with a circular kinematic constraint. Using a simplified arm model, we derived three predictions for how humans should behave if they were minimizing muscular effort to perform the task. First, we predicted that subjects would exert workless, radial forces on the constraint. Second, we predicted that the muscles would be deactivated when they could not contribute to work. Third, we predicted that when moving very slowly along the constraint, the pattern of muscle activity would not differ between clockwise (CW) and counterclockwise (CCW) motions. To test these predictions, we instructed human subjects to move a robot handle around a virtual, circular constraint at a constant tangential velocity. To reduce the effect of forces that might arise from incomplete compensation of neuro-musculoskeletal dynamics, the target tangential speed was set to an extremely slow pace (~1 revolution every 13.3 seconds). Ultimately, the results of human experiment did not support the predictions derived from our model of minimizing muscular effort. While subjects did exert workless forces, they did not deactivate muscles as predicted. Furthermore, muscle activation patterns differed between CW and CCW motions about the constraint. These findings demonstrate that minimizing muscle effort is not a significant factor in human performance of this constrained-motion task. Instead, the central nervous system likely prioritizes reducing other costs, such as computational effort, over muscle effort to control physical interactions.

The Human Systems Integration Framework: Enhanced HSI support for System Acquisition

Ensuring that human performance factors are adequately considered during the system engineering process has proven to be a challenging task for Human Factors and Human Systems Integration (HSI) practitioners. Programs that do not sufficiently include HSI as an integral aspect of planning and execution are at risk of diminished user performance and total system performance, leading to costly and time-consuming re-work. To encourage a greater involvement of HSI in systems engineering, the HSI Framework (HSIF) was developed to explicitly incorporate HSI tasks and products in all stages of system acquisition. The HSIF is a web application that contains general and domain-specific HSI activities, references, and related products. For HSI Practitioners and System Engineers, the HSIF provides technical guidance and best practices, thereby fostering early, explicit, and properly-scoped HSI efforts. In turn, Program Managers and Technical Authorities are provided with the information needed to accurately assess and manage human performance-related risks, leading to relevant, effective, and integrated system performance.

(358) Medication errors associated with intravenous patient controlled analgesia: a descriptive analysis of 2005-2015 MEDMARX database

Intravenous (IV) patient-controlled opioid analgesia (PCA) is a mainstay of the management of acute post-operative pain. While IV PCA has the benefit of allowing patient to self-titrate opioids to their level of pain and faster delivery of analgesics, their use is also accompanied by number of challenges, including medication errors, analgesic gaps, and proxy dosing. The objective of this study was to characterize medication errors associated with IV PCA therapy in hospital settings. A retrospective, descriptive analysis of 2005-2015 Quantros™ MEDMARX data was conducted and revealed 1,948 unique medication errors associated with opioid IV PCA occurring in hospitals during this time period. Based on the NCC MERP Index, 89.5 % of these errors were classified as non-harmful, 6.7% as harmful, and 3.8% as potential errors, with majority of these errors occurring during drug administration (55%) and dispensing (23%). Over a quarter (26.3%) of the errors were attributed to pump-related causes including improper use of pump and pump malfunction. Of the 130 harmful errors, 65% (84) occurred during drug administration. Major types of harmful errors included: improper dose/quantity (58.4%), omission error (23.1%), prescribing error (15.4%) and wrong administration technique (13.8%). The leading causes of harmful errors included human performance factors (57%), procedure or protocol not followed (43.8%), and improper pump use (33.8%). Of the 1383 errors that reached the patient, 27.8% required interventions to prevent serious/fatal complications. Despite the advantages of IV PCA, patients are still at risk of IV PCA-related errors. These findings indicate certain types of IV PCA-related errors may be preventable. There is an unmet need for novel PCA systems that could potentially circumvent certain medication errors commonly associated with IV PCA while still retaining the advantages of pain management associated with PCA. Supported by a grant from AcelRx Pharmaceuticals, Inc.

Depth Perception Assessment for Stereoscopic 3D Displays Using Layered Random Dot Stereogram

Determining the features of human binocular vision according to given disparity information has gained significant interest with regard to 3-D-relevant fields. However, subjectively distinguishing the features is internally ambiguous owing to personal factors and external susceptibility due to viewing-environmental factors. Moreover, high cost and low reproducibility of the subjective assessment method restricts its usability in numerous practical applications. To alleviate these problems, this paper presents a novel visual stimulus, namely layered random dot stereogram (LRDS), and hierarchical paradigm for vote ratings. Based on the guide depth information in LRDS, viewers could recognize considerably obvious feature points, and our two-step rating strategy enhanced the reliability and efficiency of the viewing tests. The experiments prove that our approach successfully reflects the effects of not only personal factors but also display factors on depth perception. Our approach would be beneficial to the 3-D fields of human factor, viewer-interactive systems, and product performance evaluation.

High-flavonoid intake induces cognitive improvements linked to changes in serum brain-derived neurotrophic factor: Two randomised, controlled trials.

BACKGROUND: Recent clinical studies have indicated the beneficial impact of dietary flavonoid intake on human cognitive performance. Although the mechanisms that mediate such improvements are currently unclear, animal and human trial data suggest that changes in neurotrophin expression, and related signalling apparatus, may be involved.OBJECTIVE: To investigate the link between changes in serum brain-derived neurotrophic factor (BDNF) and changes in human cognitive performance following flavonoid intake.METHODS: The relationship between serum levels of BDNF and age, gender, BMI, waist circumference, blood pressure and cognition at baseline, and following flavonoid intake, was investigated in two distinct randomised, controlled clinical trials. Trial 1 was conducted in men and women (aged 26–70 y; consuming an average of 3 portions of fruit and vegetables per day) and delivered high-flavonoid (>15 mg/100 g) or low-flavonoid (<5 mg/100 g) fruit and vegetables and increased intake by 2 portions every 6 weeks. The control arm was habitual diet over the same time frame. Trial 2 was conducted in an older males and female cohort (aged 62–75 y) intervening with a high-flavanol cocoa drink (494 mg total flavanols) and a low-flavanol cocoa drink (23 mg total flavanols) for 12 weeks.RESULTS: Serum BDNF levels increased linearly to the age of 65, after which BDNF levels were found to decrease markedly. All other physiological and anthropometric measurements proved to not be significantly associated with serum BDNF levels (p > 0.05), although higher levels in males compared to females almost achieved significance (p = 0.056). At baseline, higher serum BDNF levels were associated with significantly better global cognition scores, relative to individuals with lower serum levels. In addition, following intervention for 18 weeks, high-flavonoid, but not low-flavonoid, fruit and vegetable intake induced significant improvements in cognitive performance and increases in serum BDNF levels (p = <0.001). Flavanol intervention for 12 weeks also resulted in significant increases in serum BDNF (p = <0.001), and such increases were correlated with improvements in global cognitive performance.CONCLUSION: Increases in global cognition induced by high flavonoid fruit and vegetables, and cocoa flavanols were paralleled by concurrent changes in serum BDNF levels, suggesting a role for BDNF in flavonoid-induced cognitive improvements. Furthermore, we provide further data suggesting that serum BDNF levels may represent a biomarker of cognitive function.