A Comprehensive Evaluation of Spine Kinematics, Kinetics, and Trunk Muscle Activities During Fatigue-Induced Repetitive Lifting

Kazemi, Zeinab; Mazloumi, Adel; Arjmand, Navid; Keihani, Ahmadreza; Karimi, Zanyar; Ghasemi, Mohamad Sadegh; Kordi, Ramin

doi:10.1177/0018720820983621

Cited by 16 publications

(8 citation statements)

References 61 publications

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“…Data related to markers' location was visually assessed using Mokka (Version 0.6, Bio-Mechanical Toolkit). The multiple motion time series were low-pass smoothed at 7 Hz using a 4th-order digital Butterworth filter (Kazemi et al, 2021;O'Connor et al, 2007). Mean forward neck flexion and mean lateral bending to the left and right sides were the kinematics measured.…”

Section: Data Processingmentioning

confidence: 99%

Perceived Discomfort, Neck Kinematics, and Muscular Activity During Smartphone Usage: A Comparative Study

et al. 2022

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Objective The present study aims to evaluate the effects of posture, task, and handgrip style on discomfort, neck kinematics, and concomitant muscular activity when using a smartphone (SP). Background Along with the popularity of smartphones, musculoskeletal disorders have become prevalent among smartphone users. However, comprehensive aspects of discomfort, kinematics, and electromyographic responses across various conditions remain to be investigated. Method Twenty-four young smartphone users performed typing, video watching, and reading tasks while holding the smartphone both with one hand and with two hands while either sitting or standing. Neck kinematics and muscular activities were simultaneously recorded. Results Working with SPs led to higher discomfort in the neck ( p = 0.01), lower back ( p = 0.01), and shoulder ( p = 0.04) while sitting as compared to standing. Sitting was associated with greater neck flexion and more minor lateral bending for all tasks and grip styles ( p < 0.05). Electromyographic analysis indicated significant differences between sitting and standing, with alterations being dependent on the test condition. Moreover, neck kinematics and muscular activities significantly differed based on the task nature, handgrip, and interactions. Conclusion This study highlights the risk of using smartphones in increased neck angle flexion and muscular activities fatigue. Thus, posture and handgrip should be considered while using SPs. As each test condition affects a specific dependent variable, a holistic approach is required to evaluate the responses of SP users’ musculoskeletal systems. Application Results can be applied to develop guidelines for musculoskeletal disorders/discomfort prevention among SP users, especially with the rise of smartphone use during the COVID-19 pandemic.

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Section: Data Processingmentioning

confidence: 99%

Perceived Discomfort, Neck Kinematics, and Muscular Activity During Smartphone Usage: A Comparative Study

et al. 2022

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“… Firouzabadi et al (2021) studied gender differences in MMH. Considering several studies, research on muscle fatigue and joint angle range of motion collect baseline data using sEMG, motion capture, and other devices ( Bieleman et al, 2021 ; Kazemi et al, 2022 ). Monitoring human fatigue status relies solely on sEMG for fatigue recognition and classification, leading to unstable results and certain limitations ( Cattarello et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Effect of different postures and loads on joint motion and muscle activity in older adults during overhead retrieval

Zhou,

Xu,

Huang

et al. 2024

Front. Physiol.

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Introduction: Pain is a common health problem among older adults worldwide. Older adults tend to suffer from arm, lumbar, and back pain when using hanging cabinets.Methods: This study used surface electromyography to record muscle activity and a motion capture system to record joint motion to research effects of different loads and retrieval postures on muscle activity and joint range of motion when older adults retrieve objects from a high place, to provide optimised feedback for the design of hanging cabinet furniture.Results: We found that: 1) The activity of BB (Biceps brachii) on the side of the body interacting with the cabinet door was greater than that of UT (Upper trapezius) and BR (Brachial radius) when retrieving objects from a high place, the activity of UT on the side of the body interacting with a heavy object was greater than that of BB and BR. 2) The activity of UT decreases when the shoulder joint angle is greater than 90°, but the activity of BB increases as the angle increases. In contrast, increasing the object’s mass causes the maximum load on the shoulder joint. 3) Among the different postures for overhead retrieval, alternating between the right and left hand is preferable for the overhead retrieval task. 4) Age had the most significant effect on overhead retrieval, followed by height (of person), and load changes were significantly different only at the experiment’s left elbow joint and the L.BR. 5) Older adults took longer and exerted more effort to complete the task than younger adults, and static exercise in older adults may be more demanding on muscle activity in old age than powered exercise.Conclusion: These results help to optimise the design of hanging cabinet furniture. Regarding the height of hanging cabinets, 180 cm or less is required for regular retrieval movements if the human height is less than 150 cm. Concerning the depth of the hanging cabinets, different heights chose different comfort distances, which translated into the depth of the hanging cabinets; the greater the height, the greater the depth of the hanging cabinets to use.

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“…Since during lifting heavy loads, the spine is the most affected body district, the scientific literature shows that the mainly used indexes are based on the trunk behavior in terms of kinematics [13][14][15][16], forces at the L5/S1 level [17][18][19] and surface electromyography [6,[20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Lower Limb Muscle Co-Activation Maps in Single and Team Lifting at Different Risk Levels

Chini,

Varrecchia,

Serrao

et al. 2024

Applied Sciences

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The central nervous system uses muscle co-activation for body coordination, effector movement control, and joint stabilization. However, co-activation increases compression and shear stresses on the joints. Lifting activity is one of the leading causes of work-related musculoskeletal problems worldwide, and it has been shown that when the risk level rises, lifting enhances trunk muscle co-activation at the L5/S1 level. This study aims to investigate the co-activation of lower limb muscles during liftings at various risk levels and lifting types (one-person and vs. two-person team lifting), to understand how the central nervous system governs lower limb rigidity during these tasks. The surface electromyographic signal of thirteen healthy volunteers (seven males and six females, age range: 29–48 years) was obtained over the trunk and right lower limb muscles while lifting in the sagittal plane. Then co-activation was computed according to different approaches: global, full leg, flexor, extensor, and rostro-caudal. The statistical analysis revealed a significant increase in the risk level and a decrease in the two-person on the mean and/or maximum of the co-activation in almost all the approaches. Overall, our findings imply that the central nervous system streamlines the motor regulation of lifting by increasing or reducing whole-limb rigidity within a distinct global, extensor, and rostro-caudal co-activation scheme, depending on the risk level/lifting type.

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A Comprehensive Evaluation of Spine Kinematics, Kinetics, and Trunk Muscle Activities During Fatigue-Induced Repetitive Lifting

Cited by 16 publications

References 61 publications

Perceived Discomfort, Neck Kinematics, and Muscular Activity During Smartphone Usage: A Comparative Study

Perceived Discomfort, Neck Kinematics, and Muscular Activity During Smartphone Usage: A Comparative Study

Effect of different postures and loads on joint motion and muscle activity in older adults during overhead retrieval

Lower Limb Muscle Co-Activation Maps in Single and Team Lifting at Different Risk Levels

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