Showing 5 results for Low Back Pain
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Volume 1, Issue 1 (1-2012)
Abstract
Introduction: Many methods exist for evaluating ergonomic risk factors for LBP at workplace, including biomechanical, physiological and psycho-physical methods. Digital Human Modeling (DHM) as a tool based on computer for ergonomic evaluation that Because having advantages such as saving time and costs in assessment and actively evaluation of ergonomic solutions in the digital environment.Aim of this study was evaluation occupational causes of LBP with the use of digital human modeling.
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Method and Materials: This study was a case quasi-experimental study in the engine assembly of the car manufacturing industry was conducted. First, The characteristics of job and risk factors for low back pain In all workstations were documented, then workstations with high risk of low back disorders were selected. Finally, a workstation for simulating and evaluating in the human digital modeling softwares, which includes 3DSSPP and Catia were selected. A total 22 posture of the lifting and lowering moment of the three tasks of workstation selected for simulation. After evaluation in the digital environment, the risk areas identified and solutions were presented.
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Results: The results showed that compressive and shear forces on the L5/S1 disc increased with increase of anthropometric dimensions and Horizontal distance from the body and decrease of height Lowering the site, and the percentage of people capable to perform a task in joint, decreased with increase of anthropometric dimensions. Ligament strain in postures with sever bending trunk were more increasing. RULA scores increased with the Unsuitable conditions of back and arms. High risk areas, were mainly related to the low height of pallets in lifting and lowering and high Horizontal distance from the body.
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Conclusion: According to The results of this study, Biomechanical Causes for LBP, including anthropometric characteristics (height and weight), Horizontal distance of object to the body, height of lifting and lowering location and trunk bending and torsion. This study showed that DHM is an effective tool in the evaluation of job tasks and workplace design, that can be identified risk area in each task and to achieve the ideal design. Using DHM can be implement Desired solution in a virtual environment and With the re-evaluation, Be sure of having effective solutions in the real environment.
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Volume 2, Issue 1 (5-2012)
Abstract
Introduction: Low back pain (LBP) is a common and costly health problem. It has high prevalence in
nursing job and caused shortage of nursing staff. This study was conducted to determine the prevalence of LBP, knowledge level of LBP risk factors and assess relationship between LBP prevalence and nurses’ knowledge level of LBP risk factors among nurses of Shiraz University of Medical Sciences (SUMS).
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Material and Method: In this cross-sectional study, 118 randomly selected registered nurses participated from SUMS hospitals with at least one year of job tenure. In order to assess nurses’ knowledge of LBP risk
factors, a self-administered survey questionnaire consisted of four parts was used as data collecting tool. Statistical
analyses were performed using SPSS (version 11.5). Duncan, T-test and ANOVA tests were used for data analysis.
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Result: LBP prevalence rate was found to be 79.7% (94 nurses) during the previous year from which 12 nurses were male (63.2%) and 82 nurses were female (82.8%). Nurses’ knowledge level of LBP risk factors in different hospitals was not significantly different. The Results showed that nearly half of the nurses had poor knowledge about LBP risk factors and the remaining had good knowledge level. The main source of
information about LBP risk factors among nurses were related to their university education.
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Conclusion: A high prevalence of the LBP was found among nurses working at SUMS hospital. Knowledge level of nurses about LBP risk factors needs improvement. In addition to university education, which is the main source of information of nurses about LBP risk factors, on-the-job training seems essential in this field.
Adel Mazloumi, Zeinab Kazemi, Saeed Abedzadeh, Abbas Rahimi Foroushani,
Volume 11, Issue 1 (3-2021)
Abstract
Introduction: Workers in car manufacturing industry are at risk of a high prevalence of musculoskeletal disorders, especially low back pain. Therefore, in the present study aimed to design and fabricate a portable device to evaluate the low back kinematics and to compare these variables in workers with and without low back pain (LBP) in assembly lines of an automotive industry.
Material and Methods: In the present research workers postures were assessed using OWAS direct observational method. Moreover, simultaneously, prevalence and intensity of low back pain were evaluated by Dutch Musculoskeletal Questionnaire (DMQ) and Visual Analogue Scale (VAS). After fabricating motion analysis device, a field study was conducted using the designed device among 16 volunteers to investigate low back kinematic variables in two groups of workers: LBP and non-LBP.
Results: The results showed that 62.1 percent of all working postures were high risk with corrective action levels of 3 and 4. On average, 86.1 percent of workers experienced LBP in the previous 12 months. Regarding comparison of kinematic variable in the two groups of LBP and non-LBP, workers without LBP had higher degree and duration (in second) of movements (forward flexion, lateral bending, extension, and twisting), as compared to those with LBP. However, only movement range of forward flexion in non-LBP group (mean: 64.29 and SD: 8.41), was significantly higher than those with LBP (mean: 58.97 and SD: 11.34).
Conclusion: The device can be used as an effective tool in the ergonomics studies in the field of back pain, due to its potential to record the kinematics of the trunk, as well as its lightweight and non-interference with the task. Device’s validity was acceptable based on the comparison of the results of this device with those obtained from inclinometer.
Zeinab Kazemi, Adel Mazloumi, Navid Arjmand, Zanyar Karimi, Ahmadreza Keihani, Mohammad Sadegh Ghasemi,
Volume 13, Issue 2 (6-2023)
Abstract
Introduction: Given the high prevalence of low back pain in manual handling activities, its known relationship with spinal loads, and the role of muscular fatigue and the body’s adaptive mechanisms to counteract fatigue, this study investigated the effect of repetitive lifting tasks on trunk muscular fatigue and the kinematics of the spine and load-in-hand.
Material and Methods: Eighteen male volunteers lifted a box from the floor to their waist height at a pace of ten lifts per minute until they could no longer continue the task and reported the highest level of exhaustion. Kinematic data and muscle electromyographic activity were simultaneously recorded using a motion capture system and an electromyography device. In this study, average trunk flexion angle and trunk angular velocity were calculated as trunk kinematic variables, while average box vertical travel distance, average box horizontal displacement from L5-S1, and average box vertical displacement velocity were considered as box kinematic variables. The median frequency of electromyographic signals from selected muscles was quantified as a muscle fatigue indicator. Since subjects performed different lifting cycles, the total number of cycles was divided into five distinct blocks for data analysis.
Results: The results showed significant effects of lifting trial blocks on trunk angle (p=0.004) and vertical box displacement (p<0.001). Median frequency was significantly affected by lifting blocks for right (p=0.016) and left erector spinae (p=0.014), right (p=0.021) and left multifidus (p<0.001), right latissimus dorsi (p=0.001), and left rectus abdominis (p=0.039).
Conclusion: Overall, the results highlight variations in most kinematic parameters and a reduction in the frequency content of EMG signal spectra. These changes serve as indices of the central nervous system’s control over lifting behavior under dynamic conditions. A better understanding of these central nervous system adaptations could have practical applications in interventions such as workstation design, exoskeleton development, and worker training to manage musculoskeletal disorders.
Hassan Mehridiz, Mohamad Sadegh Ghasemi Ghasemi, Hassan Saeedi, Mahsa Varmazyar, Ehsan Garosi,
Volume 14, Issue 2 (6-2024)
Abstract
Introduction: Lifting loads in awkward postures is a main cause of low back musculoskeletal disorders. In this context, researchers have used various indicators to determine the relationship between biomechanical variables and the risk of these disorders. This study aimed to investigate the correlation between plantar pressure distribution and the values of UTAH back-compressive forces (BCF) and lifting index (LI) during symmetrical load-lifting tasks.
Material and Methods: Thirteen healthy men, aged 25 to 35, took part in this study. The participants were instructed to symmetrically lift loads weighing 7.5 kg and 15 kg in 15 different postures, considering three horizontal distances (A, B, C) and five different heights (1-5). Pressure on the foot soles was recorded using 16 force-sensitive resistors (FSR) corresponding to eight anatomical areas on each foot. The BCF and LI were also calculated using the UTAH method and the NIOSH equation, respectively. Statistical analysis was performed using SPSS (version 21) software.
Results: Based on the results, when the load was closest to the body (A1-A5), the highest pressure was recorded in the heel and the 4th and 5th metatarsal of both feet. In lifting a load of 15 kg in the A2, B1, B2, C1, C2 postures and lifting a load of 7.5 kg in the C2 posture, the average BCF exceeded 700 pounds. The LI was greater than 1 for specific postures (B1, B2, B4, B5, C1-C5) at 15 kg and (C1, C2, C4, C5) at 7.5 kg load-lifting. During the 7.5 kg and 15 kg load-lifting, there was a significant correlation between the plantar pressure and the values of LI and UTAH (p-values < 0.05) in most postures.
Conclusion: The results showed a significant correlation between plantar pressure distribution and load-lifting postures. The study findings, which identify risk levels associated with lifting postures, lay the groundwork for future research aimed at categorizing safe and unsafe plantar pressure patterns.
