From Stoop to Squat: A Comprehensive Analysis of Lumbar Loading Among Different Lifting Styles

Lifting up objects from the floor has been identified as a risk factor for low back pain, whereby a flexed spine during lifting is often associated with producing higher loads in the lumbar spine. Even though recent biomechanical studies challenge these assumptions, conclusive evidence is still lacking. This study therefore aimed at comparing lumbar loads among different lifting styles using a comprehensive state-of-the-art motion capture-driven musculoskeletal modeling approach. Thirty healthy pain-free individuals were enrolled in this study and asked to repetitively lift a 15 kg-box by applying 1) a freestyle, 2) a squat and 3) a stoop lifting technique. Whole-body kinematics were recorded using a 16-camera optical motion capture system and used to drive a full-body musculoskeletal model including a detailed thoracolumbar spine. Continuous as well as peak compressive, anterior-posterior shear and total loads (resultant load vector of the compressive and shear load vectors) were calculated based on a static optimization approach and expressed as factor body weight (BW). In addition, lumbar lordosis angles and total lifting time were calculated. All parameters were compared among the lifting styles using a repeated measures design. For each lifting style, loads increased towards the caudal end of the lumbar spine. For all lumbar segments, stoop lifting showed significantly lower compressive and total loads (−0.3 to −1.0BW) when compared to freestyle and squat lifting. Stoop lifting produced higher shear loads (+0.1 to +0.8BW) in the segments T12/L1 to L4/L5, but lower loads in L5/S1 (−0.2 to −0.4BW). Peak compressive and total loads during squat lifting occurred approximately 30% earlier in the lifting cycle compared to stoop lifting. Stoop lifting showed larger lumbar lordosis range of motion (35.9 ± 10.1°) than freestyle (24.2 ± 7.3°) and squat (25.1 ± 8.2°) lifting. Lifting time differed significantly with freestyle being executed the fastest (4.6 ± 0.7 s), followed by squat (4.9 ± 0.7 s) and stoop (5.9 ± 1.1 s). Stoop lifting produced lower total and compressive lumbar loads than squat lifting. Shear loads were generally higher during stoop lifting, except for the L5/S1 segment, where anterior shear loads were higher during squat lifting. Lifting time was identified as another important factor, considering that slower speeds seem to result in lower loads.

Body-powered variable impedance: An approach to augmenting humans with a passive device by reshaping lifting posture

The movement patterns appropriate for exercise and manual labor do not always correspond to what people instinctively choose for better comfort. Without expert guidance, people can even increase the risk of injury by choosing a comfortable posture rather than the appropriate one, notably when lifting objects. Even in situations where squatting is accepted as a desirable lifting strategy, people tend to choose the more comfortable strategy of stooping or semisquatting. The common approach to correcting lifting posture, immobilizing vulnerable joints via fixation, is insufficient for preventing back injuries sustained from repetitive lifting. Instead, when lifting small but heavy objects, the entire kinetic chain should cooperate to achieve a series of squat-lifting patterns. Inspired by the observation that force fields affect the coordination of voluntary human motion, we devised a passive exosuit embedded with a body-powered variable-impedance mechanism. The exosuit adds impedance to the human joints according to how far the wearer’s movement is from the squat-lifting trajectories so that it hinders stooping but facilitates squatting. In an experiment that entailed lifting a small 10-kg box, 10 first-time users changed their voluntary lifting motion closer to squatting on average. Simulation results based on recorded kinematic and kinetic data showed that this postural change reduced the compression force, shear force, and moment on the lumbosacral joint. Our work demonstrates the potential of using an exosuit to help people move in a desirable manner without requiring a complicated, bulky mechanical system.

COMPARING METHODS FOR 3D INVERSE DYNAMICS ANALYSIS OF SQUAT LIFTING USING A FULL BODY LINKED SEGMENT MODEL

Objective: The main objective of this study was to assess the accuracy of bottom-up solution for three-dimensional (3D) inverse dynamics analysis of squat lifting using a 3D full body linked segment model. Least squares solution was used in this study as reference for assessment of the accuracy of bottom-up solution. Findings of this study may clarify how much the bottom-up solution can be reliable for calculating the joint kinetics in 3D inverse dynamics problems. Methods: Ten healthy males volunteered to perform squat lifting of a box with a load of one-tenth of their body weights. The joint moments were calculated using 110 reflective passive markers (46 anatomical markers and 64 tracking markers) and a 3D full body linked segment model. Ground reaction forces and kinematics data were recorded using a Vicon system with two parallel Kistler force plates. Three-dimensional Newton–Euler equations of motion with bottom-up and least squares solutions were applied to calculate joint moments. The peak and mean values of the joint moments were determined to check the quantitative differences as well as the time-to-peak value of the moment curves was determined to check the temporal differences between the two inverse dynamics solutions. Results: Significant differences (all [Formula: see text]-[Formula: see text]) between the two inverse dynamics solutions were detected for the peak values of the hip (right and left sides) and L5–S1 joint moments in the lateral anatomical direction as well significant differences (all [Formula: see text]-[Formula: see text]) were detected for the peak and mean values of the L5–S1 joint moment in all anatomical directions. Moreover, small differences (all [Formula: see text]) were detected between the two inverse dynamic solutions for the calculated lower body joint moments. Conclusions: The findings of this study clarified the disadvantages of the straightforward solutions and demonstrated that the bottom-up solution may not be accurate for more distal measures from the force plate (for hip and S1–L5) but it may be accurate for more proximal joints (ankle and knee) in 3D inverse dynamics analysis.

A Hip Active Assisted Exoskeleton That Assists the Semi-Squat Lifting

(1) Background: In the case of quick picking and heavy lifting, the carrying action results in a much more active myoelectric signal in the lower back than in an upright stationary one, and there is a high risk of back muscle injury without proper handling skills and equipment. (2) Methods: To reduce the risk of LBP during manual handing tasks, a hip active exoskeleton is designed to assist human manual lifting. A power control method is introduced into the control loop in the process of assisting human transportation. The power curve imitates the semi-squat movement of the human body as the output power of the hip joint. (3) Results: According to the test, the torque can be output according to the wearer’s movement. During the semi-squat lifting process, the EMG (electromyogram) signal of the vertical spine at L5/S1 was reduced by 30–48% and the metabolic cost of energy was reduced by 18% compared the situation of without EXO. (4) Conclusion: The exoskeleton joint output torque can change in an adaptive manner according to the angular velocity of the wearer’s joint. The exoskeleton can assist the waist muscles and the hip joint in the case of the reciprocating semi-squat lifting movement.

COMPARING METHODS FOR 3D INVERSE DYNAMICS ANALYSIS OF SQUAT LIFTING USING A FULL BODY LINKED SEGMENT MODEL

Objective: The main objective of this study was to assess the accuracy of bottom-up solution for three-dimensional (3D) inverse dynamics analysis of squat lifting using a 3D full body linked segment model. Least squares solution was used in this study as reference for assessment of the accuracy of bottom-up solution. Findings of this study may clarify how much the bottom-up solution can be reliable for calculating the joint kinetics in 3D inverse dynamics problems. Methods: Ten healthy males volunteered to perform squat lifting of a box with a load of one-tenth of their body weights. The joint moments were calculated using 110 reflective passive markers (46 anatomical markers and 64 tracking markers) and a 3D full body linked segment model. Ground reaction forces and kinematics data were recorded using a Vicon system with two parallel Kistler force plates. Three-dimensional Newton–Euler equations of motion with bottom-up and least squares solutions were applied to calculate joint moments. The peak and mean values of the joint moments were determined to check the quantitative differences as well as the time-to-peak value of the moment curves was determined to check the temporal differences between the two inverse dynamics solutions. Results: Significant differences (all [Formula: see text]-values [Formula: see text]) between the two inverse dynamics solutions were detected for the peak values of the hip (right and left sides) and L5–S1 joint moments in the lateral anatomical direction as well significant differences (all [Formula: see text]-values [Formula: see text]) were detected for the peak and mean values of the L5–S1 joint moment in all anatomical directions. Moreover, small differences (all RMSEs [Formula: see text]%) were detected between the two inverse dynamic solutions for the calculated lower body joint moments. Conclusions: The findings of this study clarified the disadvantages of the straightforward solutions and demonstrated that the bottom-up solution may not be accurate for more distal measures from the force plate (for hip and S1–L5) but it may be accurate for more proximal joints (ankle and knee) in 3D inverse dynamics analysis.

Development of Assist Suit for Squat Lifting Support Considering Gait and Quantitative Evaluation by Three-Dimensional Motion Analysis

Globally, lower back pain is a serious problem. For workers, it not only causes health problems but also has social and economic influences. Lower back pain could be attributed to burden on people’s waists when they handle heavy objects. Ministry of Health, Labour and Welfare in Japan recommends squat lifting, a method of lifting objects with a smaller burden on waist. On the other hand, squat lifting is not commonly used because it requires deep bending of knees to lift an object, leading to a larger work load. Therefore, a leaf-spring type power assist suit for legs has been developed in order to assist squat lifting. However, if the fixing performance of a preceding machine was enhanced, a leaf spring could impede the bending of knee joints during gait motion. In the present study, we developed a power assist suit for legs using a slide mechanism. A leaf spring was chosen so as to meet a target assist torque determined by a motion analysis for lifting objects. In addition, we made a prototype machine with slide mechanism. EMG measurement of the thigh muscle during lifting actions using the prototype machine showed a decrease of up to 46%. It was also confirmed that a machine with slide mechanism could realize a more natural gait than a machine without it.

The Effects of 10%, 20%, and 30% Velocity Loss Thresholds on Kinetic, Kinematic, and Repetition Characteristics During the Barbell Back Squat

Purpose: Prescribing resistance training using velocity loss thresholds can enhance exercise quality by mitigating neuromuscular fatigue. As little is known regarding performance during these protocols, we aimed to assess the effects of 10%, 20%, and 30% velocity loss thresholds on kinetic, kinematic, and repetition characteristics in the free-weight back squat. Methods: Using a randomized crossover design, 16 resistance-trained men were recruited to complete 5 sets of the barbell back squat. Lifting load corresponded to a mean concentric velocity (MV) of ∼0.70 m·s−1 (115 [22] kg). Repetitions were performed until a 10%, 20%, or 30% MV loss was attained. Results: Set MV and power output were substantially higher in the 10% protocol (0.66 m·s−1 and 1341 W, respectively), followed by the 20% (0.62 m·s−1 and 1246 W) and 30% protocols (0.59 m·s−1 and 1179 W). There were no substantial changes in MV (−0.01 to −0.02 m·s−1) or power output (−14 to −55 W) across the 5 sets for all protocols, and individual differences in these changes were typically trivial to small. Mean set repetitions were substantially higher in the 30% protocol (7.8), followed by the 20% (6.4) and 10% protocols (4.2). There were small to moderate reductions in repetitions across the 5 sets during all protocols (−39%, −31%, −19%, respectively), and individual differences in these changes were small to very large. Conclusions: Velocity training prescription maintains kinetic and kinematic output across multiple sets of the back squat, with repetition ranges being highly variable. Our findings, therefore, challenge traditional resistance training paradigms (repetition based) and add support to a velocity-based approach.

Determination of Joint Load of Human Lower Limb by Using 2D Inverse Dynamics Modelling

The human lower limb is a major part of the human body that is exposed to high joint load during daily activities. Different lifestyles and cultural activities can affect the loading condition generated at the joint during motion. For instance, deep squatting is more frequently performed by Asians compared to Europeans e.g. kneeing on tatami among Japanese and sitting position during prayer among Muslims. The aim of this research is to determine the joint load of the human lower limb during the squat lifting movement by using inverse dynamics of 2-dimensional (2D) human lower limb model. The 2D inverse dynamics modelling was used to describe and compute all the joint force reactions from the known ground reaction and lower limb kinematics. In this study, 2D human lower limb model was analysed during the squat lifting movement. Inverse dynamics computation was performed using MATLAB programming based on Newton-Euler equations to determine the joint forces and moments. The joint loads at ankle, knee and hip joints for every knee flexion angle were obtained and the maximum forces at the ankle, knee and hip were 613.9, 614.1 and 596.1 N, respectively.