Technical note: Using Johnson distributions to model trunk kinematics.
As we seek to develop high fidelity human simulation models for ergonomic applications, the characterisation of the variability in human performance is needed. This technical note describes a method for generating probability density functions (PDFs) for one performance characteristic: trunk kinemat...
| Published in: | Theoretical Issues in Ergonomics Science Vol. 22; no. 5; pp. 555 - 567 |
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| Main Authors: | , , |
| Format: | equations & formulas research tables/charts Journal Article |
| Published: |
Taylor & Francis Ltd
Sep2021
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=152273924&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 152273924 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1463922X BDX jtl: Theoretical Issues in Ergonomics Science issn: 1463922X maglogo: Y pubinfo: dt: Sep2021 vid: 22 iid: 5 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 152273924 152273924 152991579 152273924 10.1080/1463922X.2020.1836285 152273924 ppf: 555 ppct: 12 formats: tig: atl: Technical note: Using Johnson distributions to model trunk kinematics. aug: au: Koenig, Jordyn Norasi, Hamid Mirka, Gary affil: The Physical Ergonomics and Biomechanics Laboratory, Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA, USA sug: subj: Torso Probability Kinematics Task Performance and Analysis Human Biomechanics Lifting Low Back Pain Muscle, Skeletal Muscle Fatigue Ergonomics Male Female Young Adult Adult Anthropometry Descriptive Statistics Data Analysis Software Adult: 19-44 years Male Female ab: As we seek to develop high fidelity human simulation models for ergonomic applications, the characterisation of the variability in human performance is needed. This technical note describes a method for generating probability density functions (PDFs) for one performance characteristic: trunk kinematics. A PDF from the Johnson family of distributions is defined by four parameters (γ, ξ, δ and λ) and can represent a variety of distributions. In this study, previously published trunk kinematic data were fit to Johnson distributions and regression equations for each of the four parameters were created as a function of starting lift height. Using regression coefficients and Monte Carlo simulation, PDFs for novel lifting conditions were generated. These predicted PDFs were compared with histograms of empirical data collected from a new group of ten lifters performing lifts in these novel conditions. A Kolmogorov–Smirnov goodness of fit test was performed to assess the quality of the fit. Seven of the predicted distributions of these kinematic variables were found to be a good fit with the novel empirical data. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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