Assessment Of Human Performance Research Articles

Achilles Tendon Loading during Running Estimated Via Shear Wave Tensiometry: A Step Toward Wearable Kinetic Analysis.

Understanding muscle-tendon forces (e.g., triceps surae and Achilles tendon) during locomotion may aid in the assessment of human performance, injury risk, and rehabilitation progress. Shear wave tensiometry is a noninvasive technique for assessing in vivo tendon forces that has been recently adapted to a wearable technology. However, previous laboratory-based and outdoor tensiometry studies have not evaluated running. This study was undertaken to assess the capacity for shear wave tensiometry to produce valid measures of Achilles tendon loading during running at a range of speeds. Participants walked (1.34 m·s -1 ) and ran (2.68, 3.35, and 4.47 m·s -1 ) on an instrumented treadmill while shear wave tensiometers recorded Achilles tendon wave speeds simultaneously with whole-body kinematic and ground reaction force data. A simple isometric task allowed for the participant-specific conversion of Achilles tendon wave speeds to forces. Achilles tendon forces were compared with ankle torque measures obtained independently via inverse dynamics analyses. Differences in Achilles tendon wave speed, Achilles tendon force, and ankle torque across walking and running speeds were analyzed with linear mixed-effects models. Achilles tendon wave speed, Achilles tendon force, and ankle torque exhibited similar temporal patterns across the stance phase of walking and running. Significant monotonic increases in peak Achilles tendon wave speed (56.0-83.8 m·s -1 ), Achilles tendon force (44.0-98.7 N·kg -1 ), and ankle torque (1.72-3.68 N·m·(kg -1 )) were observed with increasing locomotion speed (1.34-4.47 m·s -1 ). Tensiometry estimates of peak Achilles tendon force during running (8.2-10.1 body weights) were within the range of those estimated previously via indirect methods. These results set the stage for using tensiometry to evaluate Achilles tendon loading during unobstructed athletic movements, such as running, performed in the field.

Human Resource Management Performance Assessment and Enhancement in Public Community Governance

Abstract Human resource management is a more important part of public sector internal management. Based on the principles of objectivity, comprehensiveness, and significance of indicator construction, this paper constructs a human resource management performance assessment model in public community governance. It introduces the entropy weight method and TOPSIS method to comprehensively and objectively calculate the degree of influence of each evaluation indicator on public human resource management performance. Meanwhile, taking the data of public community governance in County S as an example, the vertical and horizontal comparisons of public human resource management performance are carried out to explore the corresponding public human resource management performance improvement strategies. The results of the study show that in the public human resource management of County S city, the weight of the character factor indicator is the largest (0.3801), and that of the diligence element is the smallest (0.0936), indicating that the character factor has the greatest influence on the human resource management performance of public community governance in County S city. In order to improve performance, it is recommended to promote the optimization of the management system by combining the performance management experience, as well as to continuously innovate the human resource incentive methods through multiple research.

External and Internal Loads in Sports Science: Time to Rethink?

The current paper discusses the concepts and definitions of external and internal loads in sports science and the quantification of athletes’ performance and psychobiological responses. We provide practical solutions for improving human performance assessment by suggesting related terms and consistent terminology that align with biomechanical standards. This will help to avoid discrepancies in the meaning of terms across various subdisciplines of sport and exercise science and medicine. Where possible, exercise performance should be characterized and quantified according to physical quantities such as time, distance, displacement, speed, velocity, acceleration, force, torque, work, power, and the International System of Units. These quantifications can be performed for exercises, sessions, microcycles, and mesocycles. Standardization of these terms and measurements would enable consistent communication among scientists of all knowledge areas.

A structured approach for resilience-oriented human performance assessment and prediction in offshore safety-critical operations

Resilience engineering is in the ascendant across diverse disciplines and research fields. Researchers and engineers work to create resilient systems and emphasize human elements for providing resilience. It prompts a new paradigm for viewing human performance in socio-technical systems, where variability is regarded as a measure of the potential for resilient human performance. This paper proposes a structured approach for resilience-oriented human performance assessment and prediction in offshore safety-critical operations. In the structured framework, a context-based Bayesian network model is developed to evaluate the internal and external variability of operator functions. For this purpose, a taxonomy of variability shaping factors is developed for operations at sea involving human-automation collaboration. Further , this study proposes integrating the functional resonance analysis method (FRAM) and fuzzy cognitive maps (FCM) to model the dynamic interaction of operator functions and simulate the coupling of operator variability in performing safety-critical operations. The integration augments both methods to tackle human performance modeling from both qualitative and quantitative aspects. A case study is presented in the context of offshore dynamic positioning operations to demonstrate the applicability of the approach. The results confirm that it provides a useful tool for managing operator variability and resilient performance to improve human-related safety.

Assessment of Human Hazard and Performance in the Oxygen Supply System in Bu Ali Hospital in Qazvin in 2022

Assessment of Human Hazard and Performance in the Oxygen Supply System in Bu Ali Hospital in Qazvin in 2022

Investigating the Operational Complexity of Digital Workflows Based on Human Cognitive Aspects

In recent decades, the everyday working environment has increasingly shifted into the digital realm. Accordingly, the assessment of human working performance has become strongly influenced by the level, frequency, and mode of interaction with the digital environment. This paper presents a system-level comparative analysis of human–computer interactions in 2D versus 3D digital environments, focusing on human behavior in different environments and interfaces. For the purposes of this analysis, a new methodology is proposed—inspired by a set of new concepts and metrics—that can be used to evaluate digital interfaces based on the number and complexity of user operations. Beyond the use of objective indicators, the study was supplemented by a user survey of 52 people to map the congruence of digital systems and user requirements. According to the research results, in 3D virtual work environments, users perform at least 30 percent fewer elementary operations. The Information Access Cost is 54 percent less in immersive VR than in classical 2D user interfaces. Based on these figures, we conclude that the development trends behind 3D VR-based working environments coincide with the intention to extend human cognitive capabilities.

The Performance Evaluation Model of Hotel Green Human Resources Based on Internet of Things and Fuzzy Theory

The Internet of Things (IoT) is influencing national centers of excellence as well as businesses’ approaches to development and how they generate and exploit opportunities in day-to-day hotel activities. The IoT is revolutionary and will transform how human resources are created and managed, necessitating a fresh and adaptable strategy for human resource development. The promise of the IoT is that each device will have a unique means of identifying itself and will be addressable, allowing any object to be connected. This will present a new difficulty to how green human resource development in hotels is conducted. Besides, environmental protection has emerged as the most pressing problem in world politics. Green problems are widely acknowledged as a fundamental source of development. Due to increased customer awareness, the hotel service sector has advanced in terms of quality of services as green marketing has evolved into a crucial instrument for sustainable business approaches. Green marketing strategies are being implemented by businesses to improve company success. In order to improve the adaptive performance assessment capacity of hotel green human resources, this research proposes a performance evaluation model of hotel green human resources based on the Internet of Things and fuzzy theory. It develops a large data analysis model of hotel green human resource performance by statistically quantitatively assessing the constraint parameters of hotel green human resource performance assessment. It extracts the entropy characteristic amount of hotel green human resource performance big data to make the best choice and assessment of hotel green human resource performance by green hotel maximum economic benefit evaluation and fuzzy decision technique. Furthermore, it builds an expert system analysis model for evaluating the hotel green human resource performance. Adaptive optimization of hotel green human resource performance evaluation is carried out by the fuzzy theory adaptive learning algorithm, and the optimization strategy of the hotel green human supply performance evaluation model is realized by similarity characteristic parameter estimation and fuzzy multidimensional parameter constraint. The simulation results show that the performance evaluation of hotel green human resources with this method has high accuracy and good confidence level, which improves the performance evaluation efficiency of hotel green human resources.

Open-Loop Naturalistic Driving: An Assessment of Human Behavior, Performance, and Physiology to Support the Development of Shared Control Strategies

Advanced systems that require shared control are becoming increasingly pervasive. One advantage of a shared control approach is that the human and machine work together to accomplish safe operations. However, data about the human is needed to implement successful strategies. The goal of this study was to quantify naturalistic driving by collecting performance and physiological data during manual, open-loop driving. Sixteen participants performed a single drive that included four sudden obstacles of increasing difficulty (road debris, construction, inclement weather, and an animal). Participants were asked to traverse each obstacle using self-employed judgement and strategies. Action selection, lane deviation, speed, and heart rate data were recorded. Results showed two distinct driving strategies for avoiding the moving obstacle/animal (left vs. right lane navigation). Also, maximum speed was affected by obstacle type, but heart rate variability was not. Results can be used to inform shared control algorithms designed to combat poor driving performance.

The Effect of Tablet Computer Configurations and Touchscreen Gestures on Human Biomechanics, Performance, and Subjective Assessment

As the increasing usage scenarios of tablet computers led to more non-neutral postures, optimizing the touchscreen gesture input became imminent to improve system performance and users’ well-being. Therefore, we conducted a study to investigate the influence of four tablet configurations and seven touchscreen gestures on electromyography, performance, and subjective assessment. Our results indicated that muscular loads of shoulder decreased under the Stand-Hand configuration while it increased under the Sit-Table during gesture interaction. We also found that Drag-Up and Drag-Left tended to possess higher muscular loads of shoulder while Drag-Down caused greater muscular loads of index finger. Besides, two-touch gestures spent longer duration when performing long-distance movements. Dragging in the inner direction was supposed to be more efficient than that in the outer direction. Our findings could provide a scientific basis for guiding the appropriate selection and the use of touchscreen interaction in the future HCI field.

EEG power spectral measures of cognitive workload: A meta-analysis.

Cognitive workload (CWL) is a fundamental concept in the assessment and monitoring of human performance during cognitive tasks. Numerous studies have attempted to objectively and continuously measure the CWL using neuroimaging techniques. Although the electroencephalogram (EEG) is a widely used technique, the impact of CWL on the spectral power of brain frequencies has shown inconsistent results. The present review aimed to synthesize the results of the literature and quantitatively assess which brain frequency is the most sensitive to CWL. A systematic literature search following PRISMA recommendations highlighted three main frequency bands used to measure CWL: theta (4-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz). Three meta-analyses were conducted to quantitatively examine the effect of CWL on these frequencies. A total of 45 effect sizes from 24 studies involving 723 participants were computed. CWL was associated with significant effects on theta (g = 0.68, CI [0.41, 0.95]), alpha (g = -0.25, CI [-0.45, 0.04]), and beta (g = 0.50, CI [0.21, 0.79]) power. Our results suggests that theta, especially the frontal theta, is the best index of CWL. Alpha and beta power were also significantly impacted by CWL; however, their association seemed less straightforward. These results are critically analyzed considering the literature on cerebral oscillations. We conclude by emphasizing the need to investigate the interaction between CWL and other factors that may influence spectral power (e.g., emotional load), and to combine this measure with other methods of analysis of the central and peripheral nervous system (e.g., functional connectivity, heart rate).

Development of a Test Battery for Fatigue Assessment of Agriculture Seating Systems: A Laboratory and Field Study

ABSTRACT The objective of this project was to evaluate a battery of tests that could be used to assess fatigue development in the long-duration, seated operation of farming machinery. A battery of eight tests that had been previously used to assess aspects of human fatigue were assembled and human subject testing procedures (six participants in a laboratory study, eight in a field study) were employed to identify those tests that were sensitive to fatigue development in this context. In the laboratory study, participants maintained a seated posture for a period of 2 hours and experienced a controlled seat motion profile consistent with that of farm machinery working in a moderately rough field, while the field study participants experienced an 8–10 h ground preparation (heavy tillage with chisel plow) workday. The battery of tests considered included physiological assessments, human performance assessments, and subjective assessments. TIME was the independent variable. The non-parametric Kruskal–Wallis test was performed to assess the effects of TIME. Subjective assessments (Swedish Occupational Fatigue Inventory and Body Part Discomfort) had the strongest relationship with TIME, while two physiological assessments (heart rate and heart rate variability) were also shown to be affected by TIME. Subjective assessments were the strongest measures and objective measures heart rate and heart rate variability were effective at showing fatigue of the seated machinery operators. Human performance assessment approaches were not found to be predictors of fatigue of the seated operator.

Human Driver Performance Assessment based on HiLCPS Concept

The paper presents an approach for human driver performance assessment from the view of his/her abilities or limitations. The idea is based on the Human-in-the-loop Cyber-Physical Systems (HiLCPS) concept which is briefly described in the initial part of this paper. A cybernetic approach describing a human driver as a controller in cooperation with a controlled system represented by a simulated driving task is there used. In this context, a car-driving simulator based on Unreal Engine 4 was developed. A human driver controls a simulated drive via an input HCI (Human-Computer Interface) device, i.e., a joystick or a steering wheel with pedals, exploiting the perception of the current situation in the visualized scene. That simple HiLCPS system provides data representing human behavior during a specific task under defined conditions. Based on the acquired data we are able to identify the behavioral model as well as other quantities characterizing the attitude to control. These parameters then serve for describing a current state of a human driver and his/her performance which is demonstrated in the last section.

Evaluation of a next generation oxygen system – assessment of usability, comfort and human performance

The use of an oxygen system has many crucial aspects regarding usability, comfort, and its effects on human performance. To overcome shortcomings of common systems, a new oxygen mask was developed. It was aimed at enhancing the devices’ comfort and ease of use and at enabling the interoperability of the oxygen system within the cockpit environment. The project was a cooperation between the German Aerospace Center (DLR) and Safran Aerosystems (Clean Sky 2 Joint Undertaking framework).Our aim was to evaluate the new oxygen system with the parts oxygen mask and human-machine interface and to compare it to a customary system. Experiments using 20 pilots were conducted in two demonstrators providing the two oxygen systems. The procedure included normal cruise flight operation and emergency scenarios. Data were assessed by use of computerized questionnaires and cognitive performance tasks.Results showed that subjects were more satisfied with the usability and the comfort of the new mask at all three measurement time points. Cognitive performance with the new mask was not significantly impaired compared to the customary (legacy) mask. Differential effects and conclusions for the further development process are discussed.

An Evidence-Based Review of e-HRM and Its Impact on Strategic Human Resource Management

Evidence-based review of e-HRM on strategic human resource management plays a crucial role for HR managers. The review of the literature reveals that numerous studies have been conducted to comprehend how modern HR management teams in several organizations have successfully developed a set of interrelated internal delivery and professional service strategies to meet the external challenges posed by modern organizations’ business strategies and the longer-term brand recognition and company’s reputation drivers. The aim of this research is to establish whether or not enhancing strategic human resource management is heavily dependent on evidence-based e-HRM in accordance with the adoption of the Saudi Arabia e-HRM system, which enhanced the effectiveness of enhancing strategic human resource management. This study has been conducted at the management level of the private and government sectors in Saudi Arabia. The total number of respondents in this study is 150, and the data analysis tool used in this study is SPSS-22. The study highlighted the significant impact of evidence-based E-HRM on strategic human resource management. E-HRM plays a significant role in improving decision making, enhancing human capital, training, and performance assessment of employees, leading to the strategic advantage. The regression analysis showed a significant positive impact of E-HRM on strategic human resource management.

Eye-Tracking for Human Performance Assessment in Industry 5.0 Research

Eye-Tracking for Human Performance Assessment in Industry 5.0 Research

The Pransky interview: Dr Gary Guthart, chief executive officer, Intuitive

Purpose The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry turned successful business leader, regarding the commercialization and challenges of bringing technological inventions to market while overseeing a company. This paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Gary Guthart, Chief Executive Officer (CEO) at Intuitive Surgical, Inc., and a member of the Board of Directors, both roles he has held since 2010. Guthart discusses his journey to becoming the CEO and also shares some of his lessons learned and challenges faced. Findings Guthart received a bachelor’s degree in engineering physics from California, Berkeley. He earned an MS and a PhD in engineering from the California Institute of Technology. Guthart’s first scientific experience came early in his career in a Human Factors Lab at NASA, supporting a team studying human performance assessment of pilots. Guthart was then part of the core team developing foundational technology for computer-enhanced surgery at SRI International. While at SRI, he also developed algorithms for vibration and acoustic control of large-scale systems. Guthart joined Intuitive Surgical as part of the first engineering team in 1996 as a Control Systems Analyst. He was promoted to Vice President of Engineering in 2002 and was appointed President and Chief Operating Officer in 2008. Originality/value Under Dr Gary Guthart’s leadership and his more than 25 years of medical technology, engineering, scientific and management experience, Intuitive Surgical, Inc., the world’s most successful medical robotics company, has grown to: more than 8,000 employees; nearly 6,000 da Vinci systems sold; more than 8.5 million procedures performed and an increase in stock (NASDAQ: ISRG) of more than 600%. Guthart is also on the Board of Directors for Illumina, Inc., and a member of the Board of Directors for the Silicon Leadership Group.

CMS-BN: A cognitive modeling and simulation environment for human performance assessment, part 2 — Application

Human operators play a critical role in the operation of complex engineered systems, in particular under abnormal conditions. It is important to assess human performance under conditions of interest and to improve upon the performance by taking effective measures. In this paper we present the application of a previously developed cognitive modeling and simulation environment to address these two problems. The developed environment simulates how a human operator dynamically interacts with the external system, with focus on the operator’s cognitive activities. Based on the Three Mile Island accident, specifically the stuck-open failure of the pilot operated relief valve, we demonstrate how the developed environment can be used for human reliability analysis and human performance improvement. For human reliability analysis, besides providing a single human error probability value the proposed environment allows us to examine in detail how an operator reached a decision or missed an action. For human performance improvement, the proposed environment provides an easy approach for investigating the effects of changes, for example, in operator training and system design, on human performance and therefore identifying the most effective changes to improve human performance.

CMS-BN: A cognitive modeling and simulation environment for human performance assessment, part 1 — methodology

Cognitive modeling and simulation studies how a human dynamically interacts with the external world. Human performance assessment based on this concept has long been researched in both cognitive sciences and engineering disciplines. However, existing methods have difficulties in describing the uncertain relationships in a human’s knowledge and in considering the uncertainties in the cognitive process. To tackle these issues, we propose a novel cognitive modeling and simulation environment (CMS-BN) by introducing Bayesian networks to represent a human’s knowledge and Monte Carlo simulation to account for the uncertainties in the cognitive process. The proposed environment explicitly models information perception, reasoning and response in a human’s cognitive process. Information perception works as a filtering mechanism to downselect signals from the external world. Reasoning and response are modeled as traversing the human knowledge base represented as a Bayesian network to retrieve knowledge and updating human belief and attention distribution accordingly. Uncertainties in the cognitive process are characterized through Monte Carlo simulation. The proposed environment also models the interplay between the cognitive process and two performance shaping factors, stress and fatigue, though additional factors can be further considered. We expect the proposed environment to be useful in human reliability analysis and human performance improvement.

Rate normalization for sweat metabolomics biomarker discovery

As the demand for real-time exercise performance feedback increases, excreted sweat has become a biosource of interest for continuous human performance assessment. For sweat to truly fulfill this requirement, analyte concentrations must be normalized to adequately assess day-to-day differences within and among individuals. In this manuscript, data are presented highlighting the use of accurate localized sweat rate as a means for ion and global metabolomic data normalization. The results illustrate large sweat rate variability among individuals over the course of two distinct exercises protocols. Furthermore, the data show sweat rate is not symmetrical at similar locations among right and left forearms of individuals (p = 0.0007). Sweat ion conductivity analysis suggest overall sweat rate normalization reduces variability collectively among ion values and participants with principal component analysis showing 77.8% of variation in the data set attributable to sweat rate normalization. Global metabolomic analysis of sweat illustrated overall rate normalization increases the variability among test subjects with 72.7% of the variation explained by sweat rate normalization. Finally, overall rate normalized metabolomic features of sweat significantly correlated (ρ ≥ 0.7, ρ ≤ −0.7) with measured performance metrics of the individual, establishing the potential for sweat to be used as a biosource for performance monitoring. Collectively, these data illustrate the importance of accurate localized sweat rate determination, for analyte data normalization, in support for the use of sweat in biomarker discovery efforts to predict human performance.

An Asian-centric human movement database capturing activities of daily living

Assessment of human movement performance in activities of daily living (ADL) is a key component in clinical and rehabilitation settings. Motion capture technology is an effective method for objective assessment of human movement. Existing databases capture human movement and ADL performance primarily in the Western population, and there are no Asian databases to date. This is despite the fact that Asian anthropometrics influence movement kinematics and kinetics. This paper details the protocol in the first phase of the largest Asian normative human movement database. Data collection has commenced, and this paper reports 10 healthy participants. Twelve tasks were performed and data was collected using Qualisys motion capture system, force plates and instrumented table and chair. In phase two, human movement of individuals with stroke and knee osteoarthritis will be captured. This can have great potential for benchmarking with the normative human movement captured in phase one and predicting recovery and progression of movement for patients. With individualised progression, it will offer the development of personalised therapy protocols in rehabilitation.