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Grant: Discovery Grants Program - Individual

Université de Moncton

$26,000.00

Impact of workstation and wearable technologies on musculoskeletal disorder risk in computer-intensive sedentary environments

EF 2022-23

Résumé
While most modern workplaces use computers, computers were not designed for human well-being. With increasing computer use, the sedentary nature of work rises. Computers and other current communication tools in offices eliminate various physical task requirements. In contrast, ergonomics research shows that regular, large movements are required at least every 30 minutes to maintain good physical and psychological health and well-being. Such movements are `inefficient' but `necessary'. Some existing tools may encourage such desirable movements. Furniture designers are creating chairs and work surface options to support healthier postures. Adjustable office chairs can fit users with seat and backrest height and slope, arm rest location, and flexible supportive components, particularly for the lower back. Rocking-supports or cantilevered systems further encourage movement while seated. Work surfaces may be height-adjustable including variations between sitting and standing heights; furthermore, these allow each person to work at the recommended slightly-below-relaxed-elbow height. Unfortunately, employers are reticent to provide such fully functional elements when workers can work in less-than-optimal conditions. Prevalent significant discomfort amongst office workers is ignored, although it indicates increased Musculoskeletal Disorder (MSD) risk. Notably, MSDs account for longer than average work absences and higher than average workers compensation costs. During a controlled setting study with 3 workstations, postural gestures (including differing degrees and planes of movement) have been associated with changes in back and neck pain and fatigue. How such frequency and type of postural changes affect health indicators (physiology, perception and posture) in real working environments is only partially understood. This program will study this complex question using pattern recognition and big-data analysis techniques, to determine how healthy postural patterns vary with work or equipment interventions. This program will analyse postural variation categories across body regions using non-invasive recording techniques and applying pattern recognition and machine learning methods. Wireless wearable sensors already measure variations in physical parameters which are precursors to Musculoskeletal disorders. This project will explore the ability of these sensors, and new systems supported by intelligent phones that most workers use regularly. Once reliable models are defined, we will measure the effect of 1) varying dynamic workstation elements, 2) regularly using wearable consumer technologies, and 3) using both in combination. The proposed research program will enhance our understanding of how these elements are used in regular work environments accounting for posture, physiology and perception.
Programme
Discovery Grants Program - Individual
Emplacement
New Brunswick, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2020-05591
Name nom
Black, Nancy
Department département
Génie mécanique - Génie mécanique
Organization id
73
Institution établissement
Université de Moncton
Province en
New Brunswick
Province fr
Nouveau-Brunswick
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2020
Award amount
26000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
1600
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Industrial engineering
Research subject fr
Génie industriel
Installment
inst:3
Partie
1
Nb partie
5
Application title
Impact of workstation and wearable technologies on musculoskeletal disorder risk in computer-intensive sedentary environments
Application summary
While most modern workplaces use computers, computers were not designed for human well-being. With increasing computer use, the sedentary nature of work rises. Computers and other current communication tools in offices eliminate various physical task requirements. In contrast, ergonomics research shows that regular, large movements are required at least every 30 minutes to maintain good physical and psychological health and well-being. Such movements are `inefficient' but `necessary'. Some existing tools may encourage such desirable movements. Furniture designers are creating chairs and work surface options to support healthier postures. Adjustable office chairs can fit users with seat and backrest height and slope, arm rest location, and flexible supportive components, particularly for the lower back. Rocking-supports or cantilevered systems further encourage movement while seated. Work surfaces may be height-adjustable including variations between sitting and standing heights; furthermore, these allow each person to work at the recommended slightly-below-relaxed-elbow height. Unfortunately, employers are reticent to provide such fully functional elements when workers can work in less-than-optimal conditions. Prevalent significant discomfort amongst office workers is ignored, although it indicates increased Musculoskeletal Disorder (MSD) risk. Notably, MSDs account for longer than average work absences and higher than average workers compensation costs. During a controlled setting study with 3 workstations, postural gestures (including differing degrees and planes of movement) have been associated with changes in back and neck pain and fatigue. How such frequency and type of postural changes affect health indicators (physiology, perception and posture) in real working environments is only partially understood. This program will study this complex question using pattern recognition and big-data analysis techniques, to determine how healthy postural patterns vary with work or equipment interventions. This program will analyse postural variation categories across body regions using non-invasive recording techniques and applying pattern recognition and machine learning methods. Wireless wearable sensors already measure variations in physical parameters which are precursors to Musculoskeletal disorders. This project will explore the ability of these sensors, and new systems supported by intelligent phones that most workers use regularly. Once reliable models are defined, we will measure the effect of 1) varying dynamic workstation elements, 2) regularly using wearable consumer technologies, and 3) using both in combination. The proposed research program will enhance our understanding of how these elements are used in regular work environments accounting for posture, physiology and perception.