The Effect of Industrial Back Belts and Breathing Technique on Trunk and Pelvic Coordination During a Lifting Task

Spine ◽  
1999 ◽  
Vol 24 (11) ◽  
pp. 1124-1130 ◽  
Author(s):  
Raymond W. McGorry ◽  
Simon M. Hsiang
Keyword(s):  
Back Belts ◽  
Lifting Task

Simulate and sense force exertions during virtual patient transfer tasks

2020 ◽  
Vol 64 (1) ◽  
pp. 2092-2096
Author(s):  
Ken Chen ◽  
Rebecca Widmayer ◽  
Karen B. Chen
Keyword(s):  
Muscle Activity ◽  
Fine Tuning ◽  
Activity Levels ◽  
Patient Lifting ◽  
Perceived Workload ◽  
Specific Muscle ◽  
Muscle Groups ◽  
Forceful Exertion ◽  
Lifting Task ◽  
Transfer Tasks

Virtual reality (VR) is commonplace for training, yet simulated physical activities in VR do not require trainees to engage and contract the muscle groups normally engaged in physical lifting. This paper presents a muscle activity-driven interface to elicit the sensation of forceful, physical exertions when lifting virtual objects. Users contracted and attained predefined muscle activity levels that were calibrated to user-specific muscle activity when lifting the physical counterpart. The overarching goal is to engage the appropriate muscles, and thereby encourage and elicit behaviors normally seen in the physical environment. Activities of 12 key muscles were monitored using electromyography (EMG) sensors while they performed a three-part patient lifting task in a Cave Automatic Virtual Environment. Participants reported higher task mental loads and less physical loads for the virtual lift than the physical lift. Findings suggest the potential to elicit sensation of forceful exertion via EMG feedback but needed fine-tuning to offset perceived workload.

scholarly journals Use of Back Belts to Prevent Low Back Injury

AAOHN Journal ◽  
1995 ◽  
Vol 43 (9) ◽  
pp. 489-493 ◽  
Author(s):  
Sally L. Lusk ◽  
Marion Gillen
Keyword(s):  
Back Injury ◽  
Low Back ◽  
Low Back Injury ◽  
Back Belts

Analysis of Muscle Activity Using Surface Electromyography for Muscle Performance in Manual Lifting Task

2014 ◽  
Vol 564 ◽  
pp. 644-649 ◽  
Author(s):  
Halim Isa ◽  
Rawaida ◽  
Seri Rahayu Kamat ◽  
A. Rohana ◽  
Adi Saptari ◽  
...  
Keyword(s):  
Muscle Activity ◽  
Surface Electromyography ◽  
Biceps Brachii ◽  
Twist Angle ◽  
Erector Spinae ◽  
Manual Lifting ◽  
Experienced Fatigue ◽  
Left And Right ◽  
Lifting Task ◽  
Load Mass

In industries, manual lifting is commonly practiced even though mechanized material handling equipment are provided. Manual lifting is used to transport or move products and goods to a desired place.Improper lifting techniquescontribute to muscle fatigue and low back pain that can lead to work efficiency and low productivity.The objective of this study were to analyze muscle activity in the left and right Erector Spinae, and left and right Biceps Brachii of five female subjects while performing manual lifting taskwithdifferent load mass, lifting height and twist angle.The muscle activitywere measured and analyzed using surface electromyography (sEMG).This study found that the right Biceps Brachii, right and left Erector Spinae experienced fatigue while performingasymmetric lifting (twist angle = 90°) at lifting height of 75 cm and 140 cm with load mass of 5 kg and 10 kg. Meanwhile, the left Biceps Brachii experienced fatigue when the lifting task was set at lifting height of 75 cm, load mass of 5 kg and twist angle of 90°.The load mass and lifting height has a significant influence to Mean Power Frequency (MPF) for left Biceps Brachii, left and right Erector Spinae. This study concluded that reducing the load mass can increase the muscles performance which can extend the transition-to-fatigue stage in the left and right Biceps Brachii and Erector Spinae.

scholarly journals Modelling the Additivity of Perceived Exertion in Symmetric, Mid-Sagittal Lifting

1994 ◽  
Vol 38 (10) ◽  
pp. 621-625 ◽  
Author(s):  
Brian D. Lowe
Keyword(s):  
Perceived Exertion ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Whole Body ◽  
Coefficient Of Determination ◽  
Perceived Effort ◽  
Repetitive Lifting ◽  
The Relationship ◽  
Whole Body Exertion ◽  
Lifting Task

Psychophysical approaches to quantifying perceived effort have been used to evaluate the physical demand of many industrial work activities. An experiment was conducted to examine the relationship between ratings of whole-body perceived exertion and differentiated, regional ratings of exertion. The Borg, CR-10 scale was used by 16 subjects performing a simulated repetitive lifting task. Ratings of perceived exertion were obtained for the arms, legs, torso, and central (cardiorespiratory) effort sensations as well as a rating of overall, whole-body exertion. A multiple linear regression analysis was used to predict the whole-body rating of exertion from the differentiated ratings in lifting tasks using both a squat and stoop posture. In the stoop posture condition the coefficient of determination between whole-body perceived exertion and the model including arm, torso, and central ratings was R2=0.81. In the squat posture condition, the final regression model predicting whole-body exertion contained only the rating from the legs (R2 = 0.62). Differentiated ratings explained the majority of the variance in whole-body perceived exertion for squat and stoop lifting tasks.

scholarly journals Muscle function in glenohumeral joint stability during lifting task

PLoS ONE ◽  
2017 ◽  
Vol 12 (12) ◽  
pp. e0189406 ◽  
Author(s):  
Yoann Blache ◽  
Mickaël Begon ◽  
Benjamin Michaud ◽  
Landry Desmoulins ◽  
Paul Allard ◽  
...  
Keyword(s):  
Muscle Function ◽  
Glenohumeral Joint ◽  
Joint Stability ◽  
Lifting Task

Design Human-Robot Collaborative Lifting Task Using Optimization

2021 ◽  
Author(s):  
Asif Arefeen ◽  
Yujiang Xiang
Keyword(s):  
Degrees Of Freedom ◽  
Joint Angle ◽  
Joint Torque ◽  
Robotic Arm ◽  
Inverse Dynamic ◽  
Floating Base ◽  
Grasping Forces ◽  
Design Variables ◽  
Human Arm ◽  
Lifting Task

Abstract In this paper, an optimization-based dynamic modeling method is used for human-robot lifting motion prediction. The three-dimensional (3D) human arm model has 13 degrees of freedom (DOFs) and the 3D robotic arm (Sawyer robotic arm) has 10 DOFs. The human arm and robotic arm are built in Denavit-Hartenberg (DH) representation. In addition, the 3D box is modeled as a floating-base rigid body with 6 global DOFs. The interactions between human arm and box, and robot and box are modeled as a set of grasping forces which are treated as unknowns (design variables) in the optimization formulation. The inverse dynamic optimization is used to simulate the lifting motion where the summation of joint torque squares of human arm is minimized subjected to physical and task constraints. The design variables are control points of cubic B-splines of joint angle profiles of the human arm, robotic arm, and box, and the box grasping forces at each time point. A numerical example is simulated for huma-robot lifting with a 10 Kg box. The human and robotic arms’ joint angle, joint torque, and grasping force profiles are reported. These optimal outputs can be used as references to control the human-robot collaborative lifting task.

scholarly journals Joint-Action Coordination of Redundant Force Contributions in a Virtual Lifting Task

Motor Control ◽  
2007 ◽  
Vol 11 (3) ◽  
pp. 235-258 ◽  
Author(s):  
Jurjen Bosga ◽  
Ruud G. J. Meulenbroek
Keyword(s):  
Joint Action ◽  
Action Coordination ◽  
Lifting Task
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