The Revised Strain Index: an improved upper extremity exposure assessment model

Abstract

The Revised Strain Index (RSI) is a distal upper extremity (DUE) physical exposure assessment model based on: intensity of exertion, frequency of exertion, duration per exertion, hand/wrist posture and duration of task per day. The RSI improves upon the 1995 Strain Index (SI) by using continuous rather than categorical multipliers, and replacing duty cycle with duration per exertion. In a simulation of 13,944 tasks, the RSI and 1995 SI showed good agreement in risk predictions for 1995 SI scores ≤3 (safe) and >13.5 (hazardous). For tasks with 1995 SI scores of >3 and ≤13.5, the two models showed marked disagreement, with the RSI providing much greater discriminations between ‘safe’ and ‘hazardous’ tasks for various combinations of force, repetition and duty cycle. We believe the RSI is a substantially improved model that will be useful for DUE task analysis, intervention and design.

Practitioner Summary: RSI is a substantial improvement over the 1995 SI. It should be a valuable tool for designing and analysing tasks to determine risk of musculoskeletal injuries. RSI is applicable to a wide variety of tasks including very low force and very high repetition tasks such as keyboard use.     

Feature-based assessment of visuo-spatial neglect patients using hand-drawing tasks

Visuo-spatial neglect (VSN) is a post-stroke condition in which a patient fails to respond to stimuli on one side of the visual field. Using an established pencil-and-paper-based method for the assessment of VSN (the Rivermead Behavioural Inattention Test) as a reference, a battery of computer-based hand-drawing tests is developed and shown to be effective in distinguishing between stroke subjects with and without neglect. The novel approach adopts measurements both of the outcome and the process by which the drawing tasks are executed. This approach provides a novel diagnostic capability which results in increased test sensitivity, a more objective assessment and a reduction in overall evaluation time. The paper describes the development of a binary assessment system using the computer-based acquisition and analysis of task data alongside feature selection techniques to maximise performance.

考虑漏洞间相关作用的风险评估方法

信息安全问题随着时代的变迁日益复杂,而科学、合理的风险评估为信息安全提供了一种比较根本、有效的解决途径。运用可靠性分析的方法,提出了在计算机网络空间下,基于相关性漏洞的风险评估模型,对系统的攻击建模的研究提供了一个新的思路。     

Measuring the physical demands of work in hospital settings: design and implementation of an ergonomics assessment

BACKGROUND: Assessing the physical demands of the heterogeneous jobs in hospitals requires appropriate and validated assessment methodologies. METHODS: As part of an integrated assessment, we adapted Rapid Entire Body Assessment (REBA), using it in a work sampling mode facilitated by a hand-held personal digital assistant, expanding it with selected items from the UC Computer Use Checklist, and developed a scoring algorithm for ergonomics risk factors for the upper (UB) and lower body (LB). RESULTS: The inter-rater reliability kappa was 0.54 for UB and 0.66 for LB. The scoring algorithm demonstrated significant variation (ANOVA p<0.05) by occupation in anticipated directions (administrators ranked lowest; support staff ranked highest on both scores). A supplemental self-assessment measure of spinal loading correlated with high strain LB scores (r=0.30; p<0.001). CONCLUSION: We developed and validated a scoring algorithm incorporating a revised REBA schema adding computer use items, appropriate for ergonomics assessment across a range of hospital jobs.     

Predictive validity of the Hand Arm Risk assessment Method (HARM)

The Hand Arm Risk assessment Method (HARM) is a simplified risk assessment method for determining musculoskeletal symptoms to the arm, neck and/or shoulder posed by hand-arm tasks of the upper body. The purpose of this study was to evaluate the predictive validity of HARM using data collected from a three year prospective cohort Study on Musculoskeletal disorders, Absenteeism and Health (SMASH). Structured observations of video recordings using HARM were made of 88 participants performing hand-arm tasks. These video recordings were made at baseline of the SMASH study, whereas self-reported musculoskeletal symptoms were assessed both at baseline and during a three year follow-up. The receiver operating characteristic (ROC) curves showed an area under the curve (AUC) of 0.75 (CI: 0.65–0.86) for symptoms at baseline and 0.70 (CI: 0.58–0.83) for symptoms during follow-up. For a HARM score of 50, the sensitivity and specificity were 64% and 79% at baseline and 53% and 82% during follow up. Participants with a HARM score of 50 or more (considered a high risk) had a significantly higher risk of upper limb symptoms than those with a HARM score of less than 50 at baseline (OR = 5.31; 95%CI: 2.10–13.39) and 3 year follow-up (OR = 5.11; (95%CI: 1.61–16.27). This study has shown that HARM can be used to assess work tasks of the hands and arms and discriminate between tasks that pose a high or low risk of neck or upper limb symptoms.     

Comparing the results of five lifting analysis tools

The objective of this study was to compare the results of the NIOSH, ACGIH TLV, Snook, 3DSSPP and WA L&I lifting assessment instruments when applied to a uniform task (lifting and lowering milk cases with capacities of 15 and 23l). To enable comparisons between the various lifting assessment instruments, the outputs of each method were converted to an exposure index similar to the NIOSH Lifting Index. All instruments showed higher exposures associated with lifting the 23l cases versus the 15l cases. The NIOSH, ACGIH TLV and Snook methods were similar in their results with respect to the pattern of exposure over various height levels and the differences in exposures associated with lifting 15 and 23l cases. However, the WA L&I and 3DSSPP predicted substantially lower exposures. The reasons for instrument differences are presented so that practitioners can better select the methods they need and interpret the results appropriately.     

Measuring exertion time,duty cycle and hand activity level for industrial tasks using computer vision

Abstract

Two computer vision algorithms were developed to automatically estimate exertion time, duty cycle (DC) and hand activity level (HAL) from videos of workers performing 50 industrial tasks. The average DC difference between manual frame-by-frame analysis and the computer vision DC was ?5.8% for the Decision Tree (DT) algorithm, and 1.4% for the Feature Vector Training (FVT) algorithm. The average HAL difference was 0.5 for the DT algorithm and 0.3 for the FVT algorithm. A sensitivity analysis, conducted to examine the influence that deviations in DC have on HAL, found it remained unaffected when DC error was less than 5%. Thus, a DC error less than 10% will impact HAL less than 0.5 HAL, which is negligible. Automatic computer vision HAL estimates were therefore comparable to manual frame-by-frame estimates.

Practitioner Summary: Computer vision was used to automatically estimate exertion time, duty cycle and hand activity level from videos of workers performing industrial tasks.     

Measuring elemental time and duty cycle using automated video processing

A marker-less 2D video algorithm measured hand kinematics (location, velocity and acceleration) in a paced repetitive laboratory task for varying hand activity levels (HAL). The decision tree (DT) algorithm identified the trajectory of the hand using spatiotemporal relationships during the exertion and rest states. The feature vector training (FVT) method utilised the k-nearest neighbourhood classifier, trained using a set of samples or the first cycle. The average duty cycle (DC) error using the DT algorithm was 2.7%. The FVT algorithm had an average 3.3% error when trained using the first cycle sample of each repetitive task, and had a 2.8% average error when trained using several representative repetitive cycles. Error for HAL was 0.1 for both algorithms, which was considered negligible. Elemental time, stratified by task and subject, were not statistically different from ground truth (p < 0.05). Both algorithms performed well for automatically measuring elapsed time, DC and HAL.

Practitioner Summary: A completely automated approach for measuring elapsed time and DC was developed using marker-less video tracking and the tracked kinematic record. Such an approach is automatic, repeatable, objective and unobtrusive, and is suitable for evaluating repetitive exertions, muscle fatigue and manual tasks.     

A novel wearable system for the online assessment of risk for biomechanical load in repetitive efforts

Work-related Musculo Skeletal Disorders (WMSD) are considered the third main reason for disability and early retirement in the U.S. and are widespread in many occupations, involving both heavy and light biomechanical loads. In Italy, only taking into account the years 2009–2010, it is estimated an exponential increasing in the number of WMSD reports. In particular a 159.7% increment has been reported compared to the 2006 statistics. In this context, it is clear how important correctly diagnosing this kind of pathology is becoming. Traditional methods for WMDS assessment are based on observational techniques, in which experts manually segment, label and evaluate movements with the help of pro-forma sheets. Since these methods are currently based on visual inspection and subjective judgment, they could benefit from objective measurements in terms of both reliability and repeatability. Moreover an automatic tool for ergonomics assessment would vastly reduce the time that an expert needs to carry out the same assessment manually. In this context a novel wearable wireless system capable of assessing the muscular efforts and postures of the human upper limb for WMSDs diagnosis is proposed. The system, being non-obstructive, can be used to monitor workers in ecologic environment while they are carrying on their everyday tasks. A real-time assessment is obtained according to two of the most common indexes for the analysis of risk factors on workplaces: the Rapid Upper Limb Assessment (RULA) and the Strain Index (SI). The system exploits inertial measurement units (IMUs) to reconstruct the upper limb posture, modeled as a 7 degrees of freedom (DoF) kinematic chain. As far as muscular efforts are concerned, surface EMG sensors are used to assess forearm flexor muscles strain. As an example of the proposed system application the results of a first data collection campaign regarding super-market cashiers during everyday real-life operations is reported.Relevance to industry: The presented system has a high potential impact on industry as a timely intervention on the WMSD factors may reduce pathologies and reduce the recovery of expert workers.     

Reducing the physical work load and strain of personal helpers through clothing redesign

This study assessed the effects of redesigning clients’ clothing on the physical work load and strain of personal helpers. Five women, aged 18–54 years, who helped persons with physical disabilities were measured at their worksites before and after development of the clothes worn by clients. The physical work load and strain of the helpers’ dressing/undressing of clients were determined from their hand and back movements, work time, muscular activity, heart rate (HR), percentage of heart rate range (%HRR), and rating of perceived exertion (RPE). The muscular activity of the right (p=0.05) and left (p=0.02) trapezius muscles, HR (p=0.03), and %HRR (p=0.03) of the helpers were lower when the new outerwear was used in place of traditional outerwear. Four helpers reported lower perceived exertion, and three had shorter work time with the new outerwear. This study showed that redesigning clients’ clothing can help reduce the physical work load and strain of personal helpers.     

Comparative assessment of 3D joint marker sets for the biomechanical analysis of occupational tasks

This study involves the comparative assessment of three joint marker sets to estimate joint centres. One set consists of wide elastic bands for marking the joint centres of the ankle, knee, elbow, and wrist joints (band method), a second set uses two spherical markers on either side of the joint (ball method), and a third set defines the location of a local coordinate system from spherical markers placed near the joint (coordinate method). The three marker sets were compared relative to each other. The ball method and the coordinate method were the most similar (average differences ranged from 6 to 16 mm), which is due in part to the common markers in these sets. The band method and the coordinate method were generally the least similar (average differences ranged from 15 to 31 mm). However, the results support the assumption that the marker set consisting of elastic bands can be used as an alternative to other commonly used sets. It may even be better for certain applications because of the relatively small number of missing points. Since the bands encircle the joint they are less likely to be hidden from the view of the cameras than the two marker sets that use balls to mark the joints. Most movements filmed for ergonomic analysis are complex and the incidence of missing points with traditional marker sets is high. Therefore, the band method is a very practical alternative when studying complex occupational tasks.

Relevance to industry

Manual materials handling is a source of industrial injury. Video systems and cinematography are widely used tools to analyze occupational tasks. The use of adequate markers on the subject is essential to have reliable and accurate results for task evaluation.     

Equal task,equal exposure? Are men and women with the same tasks equally exposed to awkward working postures?

The aim of the study was to determine whether men and woman with equal tasks perform these tasks in the same way. Video recordings of 37 male and 43 female workers in six task groups were observed, from which data regarding frequency and duration of exposure to awkward postures were derived. These data were also compared to self-reported exposures. The results showed that when level, duration and frequency of exposure were analysed at the same time, men and women had slightly different exposure patterns. However, these differences were not found when duration and frequency were analysed separately. From the questionnaires it appeared that men and women generally report similar exposures, but they seemed to over-report their exposure compared to the observed exposures. It is concluded that gender differences in exposure to awkward postures within the same task were small at most and cannot explain the female excess in musculoskeletal symptoms.     

Ergonomic assessment and workstation design of shipping crane cabin in steel industry

Ergonomics plays vital role to improve health and productivity at workplace and in last two decades it find importance to redesign workplace. All Indian industries had taken initiative to redesign their workplace to overcome various musculoskeletal disorders (MSD) and work related injuries. In this context, the project has been carried out in an integrated steel plant located in central India where most of the crane operator was continuously suffering from muscular pain in different body parts. Risk of MSD was identified by detailed questionnaire from 27 crane operator. It was revealed that almost all crane operators were continuously suffering from some kind of MSD. Based on the anthropometric data of 50 percentile Indian male, ergonomic assessment, redesign and evaluation of crane cabin was carried out in CATIA-V5 software. To check the compatibility of the design, rapid upper limb assessment (RULA) for both existing as well as modified crane cabin was performed. This study shows that intervention of ergonomics in workplace reduces the mismatch between man and machine and makes workplace comfortable for work.     

Establishment of overall workload assessment technique for various tasks and workplaces

A model for assessing workloads called overall workload level (OWL) was developed by introducing linguistic variable sets and applying the analytic hierarchy process (AHP) to estimate the external workload imposed on a human operator in man–machine systems. To do this, a five-point linguistic variable set scale was constructed and their hierarchical prioritization procedures were set up. The task and workplace variables (e.g., physical, environmental, postural, and mental job demand workloads) which can obtain the operator's perception of workload are selected as workload factors and the AHP technique is used to collect different weights. Finally, OWL is calculated using a computer-assisted system to determine the level of overall workload impinged on an operator. The OWL was implemented in an actual industrial environment from a physiological and epidemiological viewpoint to determine the validity of the model. Furthermore, the results obtained by applying OWL were compared to the results obtained by applying the overall workload (OW) of the NASA task load index (TLX). The results show that there is a close linear relationship among the physiological measurements, the severity of injury and illness rates, OW, and OWL. Thus, this approach can be used for problem identification and for solving widespread occupational workloads.

Relevance to industry

The determination of workloads imposed on a human operator plays an important role in designing and evaluating an existing man–machine system. Therefore, a model for assessing workloads was developed to estimate the external workload imposed on a human operator in man–machine systems. This model can be used for problem identification and for solving widespread occupational workload.     

Reliability prediction for evolutionary product in the conceptual design phase using neural network-based fuzzy synthetic assessment

Reliability prediction plays an important role in product lifecycle management. It has been used to assess various reliability indices (such as reliability, availability and mean time to failure) before a new product is physically built and/or put into use. In this article, a novel approach is proposed to facilitate reliability prediction for evolutionary products during their early design stages. Due to the lack of sufficient data in the conceptual design phase, reliability prediction is not a straightforward task. Taking account of the information from existing similar products and knowledge from domain experts, a neural network-based fuzzy synthetic assessment (FSA) approach is proposed to predict the reliability indices that a new evolutionary product could achieve. The proposed approach takes advantage of the capability of the back-propagation neural network in terms of constructing highly non-linear functional relationship and combines both the data sets from existing similar products and subjective knowledge from domain experts. It is able to reach a more accurate prediction than the conventional FSA method reported in the literature. The effectiveness and advantages of the proposed method are demonstrated via a case study of the fuel injection pump and a comparative study.     

Examining kinematics and muscle activity of the upper extremity while performing cleaning tasks: A pre-post shift evaluation

Custodians engage in strenuous manual labour throughout their workday. Uncertainty exists on whether kinematics or muscle activation changes as workers progress through their shift. The purpose of this study was to examine muscle activation and upper extremity kinematics during typical custodial tasks performed at the start and end of the work shift. Electromyography (EMG) of 8 torso and upper extremity muscles and motion capture of the corresponding region were collected for 10 custodial participants while they completed garbage removal, dry mopping, and vacuuming tasks at the start and end of a work shift. The start of shift assessment demonstrated larger anterior deltoid, posterior deltoid and extensor digitorum activation by up to 12.6 %maximal voluntary contraction (%MVC) (p < 0.001–0.023). Task affected mean and peak EMG in all muscles except flexor digitorum (p < 0.001–0.0293), and the greatest activation was found during vacuuming (peak <55%MVC in anterior and middle deltoid) and the heaviest garbage removal task (84% MVC peak in upper trapezius). Mopping created the lowest amounts of activation for almost all muscles. Joint range of motion (p < 0.001–0.031) in the shoulder was highest in vacuuming, while trunk flexion was largest in garbage removal tasks. This work replicated common custodial tasks in a laboratory, using actual custodial workers at times relevant to their typical work shifts. The information presented is useful for ergonomists, work tasks designers and custodial administration staff to develop guidelines for injury prevention.     

The effect of posture category salience on decision times and errors when using observation-based posture assessment methods

Observation-based posture assessment methods (e.g. RULA, 3DMatch) require classification of body postures into categories. This study investigated the effect of improving posture category salience (adding borders, shading and colour to the posture categories) on posture selection error rates and decision times of novice analysts. Ninety university students with normal or corrected normal visual acuity and who were not colourblind, were instructed to select posture categories as quickly and accurately as possible, in five salience conditions (Plain (no border, no shading, no colour); Grey Border; Red Border; Grey Shading (GS) and Red Shading (RS)) for images presented in randomised blocks (240 classifications made by each participant) on a computer interface. Participants responded quickest in the Border conditions, classifying postures about 5% faster than in the Plain condition. Coloured diagrams significantly reduced posture classification errors by approximately 1.5%. Overall, the best performance, based on both error rate and decision time combined, resulted from incorporating a Grey Border to the posture category diagrams; a simple enhancement that could be made to most current observation-based posture assessment tools.

Practitioner Summary: The salience of posture diagrams used in observation-based posture assessment tools was evaluated with respect to analyst error rates and decision times. The best performance resulted from incorporating a grey border to the posture diagrams; a simple enhancement that can be made to most current observation-based posture assessment tools.     

Methodological issues in systems Human Factors and Ergonomics: Perspectives on the research–practice gap,reliability and validity,and prediction

The changing nature of work and society, and a proliferation of complex global challenges, is increasing the need for systems Human Factors and Ergonomics (HFE). The discipline is well equipped to respond, but there remain a number of longstanding issues preventing systems HFE from realizing its full impact. There is a research–practice gap, a lack of reliability and validity evidence associated with systems HFE methods, and a shortage of methods that can predict behavior. In this article we revisit each issue, with each co-author providing their own perspective on the extent and causes of each issue, and their resolution. The perspectives reveal a consensus that the issues exist and are problematic but are challenging, multi-factorial, and require various solutions. The findings are subsequently synthesized to form an agenda for the wider discipline.     

Distraction 'on the buses': a novel framework of ergonomics methods for identifying sources and effects of bus driver distraction

Driver distraction represents a significant problem in the public transport sector. Various methods exist for investigating distraction; however, the majority are difficult to apply within the context of naturalistic bus driving. This article investigates the nature of bus driver distraction at a major Australian public transport company, including the sources of distraction present, and their effects on driver performance, through the application of a novel framework of ergonomics methods. The framework represents a novel approach for assessing distraction in a real world context. The findings suggest that there are a number of sources of distraction that could potentially distract bus drivers while driving, including those that derive from the driving task itself, and those that derive from the additional requirements associated with bus operation, such as passenger and ticketing-related distractions. A taxonomy of the sources of bus driver distraction identified is presented, along with a discussion of proposed countermeasures designed to remove the sources identified or mitigate their effects on driver performance.     

Fatigue and human reliability revisited in the light of ergonomics and work psychopathology

In the process control human-beings are actually information processors, solving many problems, especially covariance-problems which involve various interconnected and interactive factors.

The purpose of this experiment was to investigate the types of cognitive strategy and information-processing procedure used in solving covariance-problems, and to evaluate and determine the best strategy.

Fifty-five subjects participated in the experiment to solve two-factor covariance-problems. Verbal protocols and structural analysis were used to record and analyse the cognitive processes of covariance-problem solving. Verbal protocols were coded and analysed to differentiate the basic operators and thence explore the various strategies.

The results indicated that under two-factor covariant conditions, there were nine kinds of cognitive strategy. The 'biconvex-lens’ strategy was the most effective. All nine strategies can be classified into three categories, trial-and-error, analytic and intuitive.

This experiment research was the first study on cognitive strategies in solving covariance-problems. New topics for further study are put forward.