Inertial Motion Capture Research Articles

Estimation of joint kinetics during manual material handling using inertial motion capture: a follow-up study.

Musculoskeletal models based on inertial motion capture and ground reaction force (GRF) prediction hold great potential for field-based risk assessment of manual material handling. However, previous evaluations have identified inaccuracies in the methodology?s estimation of spinal forces, while the accuracy of other key outcome variables is currently unclear. This study evaluated knee, shoulder, and L5-S1 joint reaction forces (JRFs) derived from a musculoskeletal model based on inertial motion capture and GRF prediction against a model based on simultaneously collected optical motion capture and force plate measurements. Data from 19 healthy subjects performing lifts with various horizontal locations, deposit heights and asymmetry angles were analyzed, and the consistency and absolute agreement of the model estimates statistically compared. Despite varying levels of agreement across tasks and variables, considerable absolute differences were identified for the L5-S1 axial compression (RMSE = 63.0-94.2%BW) and anteroposterior shear forces (RMSE = 40.9-80.6%BW) as well as the bilateral knee JRFs (RMSE = 78.9-117%BW). Glenohumeral JRFs and vertical GRFs exhibited the highest overall consistency (r = 0.33-0.91, median 0.78) and absolute agreement (RMSE = 7.63-34.9%BW), while the L5-S1 axial compression forces also showed decent consistency (r = 0.04-0.89, median 0.80). The findings generally align with prior evaluations, indicating persistent challenges with the accuracy of key outcome variables. While the modelling framework shows promise, further development of the methodology is encouraged to enhance its applicability in ergonomic evaluations.

Real-Time IMU-Based Kinematics in the Presence of Wireless Data Drop.

Wireless inertial motion capture holds promise for real-time human-machine interfaces and home-based rehabilitation applications. However, wireless data drop can cause significant estimation errors deteriorating performance or even making the system unusable. It is currently unclear how to estimate non-periodic kinematics with wearable inertial measurement units (IMUs) in the presence of wireless data drop (packet loss). We thus propose a novel inference encoder-decoder network model for real-time kinematics during dynamic movement. Twenty-four healthy subjects performed yoga, golf, swimming, dance, and badminton movement activities while wearing IMUs and 10-90% of each IMU's data were randomly removed to determine the effects of data drop on estimation accuracy with and without the proposed model. Results demonstrated a reduction in RMSE of 45.2% to 51.5% in the upper limb kinematic estimation of the proposed model compared to the No Prediction strategy, and a reduction of 19.1% to 31.3% of the proposed model compared with an baseline LSTM model. In addition, the proposed model has significantly less error (p<0.05) than the No Prediction strategy and the baseline LSTM model for 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80% data drop. These results could enable wearable, wireless IMU dynamic motion analysis and assessment with reduced kinematic estimation error in the presence of varying amounts of wireless data drop and thus could further facilitate human-machine interaction and home-based medical assessment and treatment.

Study on Static Biomechanical Model of Whole Body Based on Virtual Human.

Material handling tasks often lead to skeletal injury of workers. The whole-body static biomechanical modeling method based on virtual humans is the theoretical basis for analyzing the human factor index in the lifting process. This paper focuses on the study of humans' body static biomechanical model for virtual human ergonomics analysis: First, the whole-body static biomechanical model is constructed, which calculates the biomechanical data such as force and moment, average strength, and maximum hand load at human joints. Secondly, the prototype model test system is developed, and the real experiment environment is set up with the inertial motion capture system. Finally, the model reliability verification experiment and application simulation experiment are designed. The comparison results with the industrial ergonomic software show that the model is consistent with the output of the industrial ergonomic software, which proves the reliability of the model. The simulation results show that under the same load, the maximum joint load and the maximum hand load are strongly related to the working posture, and the working posture should be adjusted to adapt to the load. Upright or bent legs have less influence on the maximum load capacity of the hand. Lower hand load capacity is due to forearm extension, and the upper arm extension greatly reduces the load capacity of the hand. Compared with a one-handed load, the two-handed load has a greater load capacity.

Comparison of joint kinematics from optical marker-based and inertial sensor-based motion capture during change-of-direction movements

The development of inertial measurement units (IMUs) has opened up possibilities to test kinematics of sports movements in natural environments (Di Paolo et al., 2023). This advantage over lab-based optical motion capture (OMC) comes at the cost of inherent inaccuracies. Especially, fast multidirectional movements including de- and accelerations pose a challenge for inertial-based movement reconstruction with limited task-specific validation research available (Heuvelmans et al., 2022). Therefore, we aimed to test the validity of IMU-based kinematics in a 180° change of direction (COD) task to provide insight into the applicability for future on-field ACL injury risk research. Twenty-six sports science students were equipped with eight IMU sensors of the Noraxon Ultium Motion System and an adaption of the Plug-in-Gait markerset (53 markers) recorded by a VICON OMC system. They performed five 180° anti-clockwise CODs at their maximum speed. As an example for sagittal and frontal plane angles relevant for ACL injury risk, the knee flexion and abduction angle at the initial contact of the cutting step (right leg) were calculated using the Noraxon MyoMotion software for IMU-recorded data and OpenSim for marker-based OMC data. At the time of abstract submission, the data of five (randomly chosen) participants had been analysed. More participants and more joint angle outcomes will be included in follow-up analyses. Deviations between IMU-generated and OMC-generated joint angles are depicted in Figure 1. Within subjects, deviations below 1.5 standard deviations were observed. Between subjects, deviations ranged from 0° and 22° in knee flexion angles and 0° and 11° in knee abduction angles. A general trend towards higher joint angles measured by the IMU system is noticeable, suggesting a possible off-set error. For four out of five participants, the knee flexion deviation was below 10°, which can be considered an accuracy which is tolerable but requires consideration in the interpretation (&lt; 2°: good accuracy, 2-5°: acceptable accuracy, 5-10°: tolerable accuracy, &gt; 10° unbearable accuracy; Bessone et al., 2022). Deviations in knee abduction angles appear too large given the small physiological joint range and motion in this plane. This preliminary analysis of individual deviations suggests acceptable deviations between IMU and OMC measurements regarding knee flexion but problematic deviations for knee abduction. Prospectively, we aim to investigate possible off-set corrections, e.g. through a better alignment of the underlying biomechanical models, and alternative approaches for IMU-based movement reconstruction, e.g. through optimal control simulations (Nitschke et al., 2024).

Accuracy Validation of a Sensor-Based Inertial Measurement Unit and Motion Capture System for Assessment of Lower Limb Muscle Strength in Older Adults-A Novel and Convenient Measurement Approach.

(1) Background: The aim of this study was to assess lower limb muscle strength in older adults during the transfer from sitting to standing (STS) using an inertial measurement unit (IMU). Muscle weakness in this population can severely impact function and independence in daily living and increase the risk of falls. By using an IMU, we quantified lower limb joint moments in the STS test to support health management and individualized rehabilitation program development for older adults. (2) Methods: This study involved 28 healthy older adults (13 males and 15 females) aged 60-70 years. The lower limb joint angles and moments estimated using the IMU were compared with a motion capture system (Mocap) (pair t-test, ICC, Spearman correlations, Bland-Altman plots) to verify the accuracy of the IMU in estimating lower limb muscle strength in the elderly. (3) Results: There was no significant difference in the lower limb joint angles and moments calculated by the two systems. Joint angles and moments were not significantly different (p > 0.05), and the accuracy and consistency of the IMU system was comparable to that of the Mocap system. For the hip, knee, and ankle joints, the ICCs for joint angles were 0.990, 0.989, and 0.885, and the ICCs for joint moments were 0.94, 0.92, and 0.89, respectively. In addition, the results of the two systems were highly correlated with each other: the r-values for hip, knee, and ankle joint angles were 0.99, 0.99, and 0.96, and the r-values for joint moments were 0.92, 0.96, and 0.85. In the present study, there was no significant difference (p > 0.05) between the IMU system and the Mocap system in calculating lower limb joint angles and moments. (4) Conclusions: This study confirms the accuracy of the IMU in assessing lower limb muscle strength in the elderly. It provides a portable and accurate alternative for the assessment of lower limb muscle strength in the elderly.

Inertial Motion Capture-Driven Digital Human for Ergonomic Validation: A Case Study of Core Drilling.

In the evolving realm of ergonomics, there is a growing demand for enhanced comfortability, visibility, and accessibility in the operation of engineering machinery. This study introduces an innovative approach to assess the ergonomics of a driller's cabin by utilizing a digital human. Through the utilization of inertial motion capture sensors, the method enables the operation of a virtual driller animated by real human movements, thereby producing more precise and realistic human-machine interaction data. Additionally, this study develops a simplified model for the human upper limbs, facilitating the calculation of joint forces and torques. An ergonomic analysis platform, encompassing a virtual driller's cabin and a digital human model, is constructed using Unity 3D. This platform enables the quantitative evaluation of comfortability, visibility, and accessibility. Its versatility extends beyond the current scope, offering substantial support for product development and enhancement.

Improving accuracy and reliability of upper limb inertial motion capture without increasing calibration complexity

Improving accuracy and reliability of upper limb inertial motion capture without increasing calibration complexity

Assessing the accuracy of a wireless sensor system for estimating lumbar moments during manual lifting tasks considering the effects of load weight, asymmetry, and height

This study assessed the accuracy of L5/S1 moment estimates calculated with an Inertial Motion Capture (IMC) system during an asymmetrical and variable height lifting task. The effects of load weight, asymmetry, and lifting height on estimates of lumbar moment have not been comprehensively considered in studies using IMC systems. Thirty-six participants engaged in tasks involving three loads, lifting heights, and trunk rotation angles. Lumbar moments were calculated using bottom-up and top-down biomechanical models. Gold-standard Optical Motion Capture (OMC) and Force Plates (FP) were used as the reference. A randomized block partially confounded design was used to compare the root mean square errors (RMSE) between the IMC and OMC-based reference estimates. The IMC system's estimated peak moments were 12%–13% lower than those estimated using the gold standard OMC-BU inverse dynamics, while the RMSE varied between 19 and 21 Nm. A Load*Height interaction was found; a trend was identified where the RMSE values increased as both the load and height levels increased. The angle did not show a significant effect on any of the tested scenarios. A close correspondence between the IMC and OMC-based moment estimates was established, with the load being the main factor affecting the differences between systems. The IMC system shows potential for use in occupational settings to capture data on the lumbar moments of workers, which could be utilized to assess ergonomic risk.

Measuring the Effect of an Ergonomic Lecture on the Rapid Upper Limb Assessment Scores of Dental Assistant Students Using Inertial Sensor-Based Motion Capture-A Randomized Controlled Study.

Individuals working in the field of dentistry have a high prevalence of musculoskeletal disorders (MSDs) owing to monotonous and one-sided physical exertion. Inertial measurement units (IMU) are increasingly shifting into focus for assessing postural risk at work. Therefore, the present study aimed to evaluate the effects of an ergonomic lecture and training intervention on postural risk and MSDs in dental assistant students using inertial sensor-based motion capture (MoCap). Eighteen female dental assistant students (age: 19.44 ± 6.83 years; height: 164.59 ± 5.32 cm; weight: 64.88 ± 16.52 kg; BMI: 19.70 ± 4.89 kg/m2), randomly divided into intervention (n = 9) and control (n = 9) groups, participated in the present study. The participants completed the Nordic Questionnaire on MSD prevalence, after which a 90 s MoCap with Xsens IMU was performed. A lecture on ergonomics was provided, followed by a five-week intervention for the intervention group. Follow-up assessments were performed, and 5- and 18-week follow-up MSD questionnaires were administered. Mixed analysis of variance (MANOVA) showed a significant difference in the Rapid Upper Limb Assessment (RULA) and part-scores of the upper arm and wrist. Despite a reduction in MSDs, no significant differences in the time of measurement and groups were detected after the five-week training intervention and the 18-week follow-up questionnaire. A targeted ergonomics lecture was effective for dental assistant students, and technologies such as IMU improved workplace ergonomics in dentists. Further studies with a longer measurement periods, follow-up, and larger sample sizes are recommended.

Experimental Comparison between 4D Stereophotogrammetry and Inertial Measurement Unit Systems for Gait Spatiotemporal Parameters and Joint Kinematics.

(1) Background: Traditional gait assessment methods have limitations like time-consuming procedures, the requirement of skilled personnel, soft tissue artifacts, and high costs. Various 3D time scanning techniques are emerging to overcome these issues. This study compares a 3D temporal scanning system (Move4D) with an inertial motion capture system (Xsens) to evaluate their reliability and accuracy in assessing gait spatiotemporal parameters and joint kinematics. (2) Methods: This study included 13 healthy people and one hemiplegic patient, and it examined stance time, swing time, cycle time, and stride length. Statistical analysis included paired samples t-test, Bland-Altman plot, and the intraclass correlation coefficient (ICC). (3) Results: A high degree of agreement and no significant difference (p > 0.05) between the two measurement systems have been found for stance time, swing time, and cycle time. Evaluation of stride length shows a significant difference (p < 0.05) between Xsens and Move4D. The highest root-mean-square error (RMSE) was found in hip flexion/extension (RMSE = 10.99°); (4) Conclusions: The present work demonstrated that the system Move4D can estimate gait spatiotemporal parameters (gait phases duration and cycle time) and joint angles with reliability and accuracy comparable to Xsens. This study allows further innovative research using 4D (3D over time) scanning for quantitative gait assessment in clinical practice.

Validity of the estimated angular information obtained using an inertial motion capture system during standing trunk forward and backward bending

BackgroundBending the trunk forward and backward while standing are common daily activities and can have various patterns. However, any dysfunction in these movements can considerably affect daily living activities. Consequently, a comprehensive evaluation of spinal motion during these activities and precise identification of any movement abnormalities are important to facilitate an effective rehabilitation. In recent years, with the development of measurement technology, the evaluation of movement patterns using an inertial motion capture system (motion sensor) has become easy. However, the accuracy of estimated angular information obtained via motion sensor measurements can be affected by angular velocity. This study aimed to compare the validity of estimated angular information obtained by assessing standing trunk forward and backward bending at different movement speeds using a motion sensor with a three-dimensional motion analysis system.MethodsThe current study included 12 healthy older men. A three-dimensional motion analysis system and a motion sensor were used for measurement. The participants performed standing trunk forward and backward bending at comfortable and maximum speeds, and five sensors were attached to their spine. Statistical analysis was performed using the paired t-test, intraclass correlation coefficient, mean absolute error, and multiple correlation coefficient.ResultsResults showed that the estimated angular information obtained using each motion sensor was not affected by angular velocity and had a high validity.ConclusionsTherefore, the angular velocity in this study can be applied clinically for an objective evaluation in rehabilitation.

Biceps femoris muscle-tendon strain during an entire overground sprint acceleration: a biomechanical explanation for hamstring injuries in the acceleration phase

ABSTRACT The objectives of this study were to analyse the peak muscle-tendon (MT) strain of the hamstring during an entire acceleration sprint overground and examine their relationship with relative joint angles and segment orientation in the sagittal plane, which are the direct causes of MT strain. Kinematic data were recorded using a 3D inertial motion capture system in 21 male semi-professional soccer players during 40-metre overground sprint. Scaled musculoskeletal models were used to estimate peak MT strain in the hamstring over 16 steps. Biceps femoris long head (BFLH) exhibited the largest peaks in MT strain compared to semitendinosus (ST) and semimembranosus (SM) muscles across all the steps, with its overall strain decreased as the number of steps and maximum speed increased. Hip flexion angle was found to be a strong predictor (p < 0.001) of joint angles, being the orientation of the pelvis in the sagittal plane of the segment with the greatest influence (p < 0.001) on the peak MT strain of BFLH during sprinting. The current study provides a biomechanical explanation for the high proportion of hamstring injuries in the acceleration phase of sprinting.

Multimodal Embodiment Research of Oral Music Traditions: Electromyography in Oud Performance and Education Research of Persian Art Music

With the recent advent of research focusing on the body’s significance in music, the integration of physiological sensors in the context of empirical methodologies for music has also gained momentum. Given the recognition of covert muscular activity as a strong indicator of musical intentionality and the previously ascertained link between physical effort and various musical aspects, electromyography (EMG)—signals representing muscle activity—has also experienced a noticeable surge. While EMG technologies appear to hold good promise for sensing, capturing, and interpreting the dynamic properties of movement in music, which are considered innately linked to artistic expressive power, they also come with certain challenges, misconceptions, and predispositions. The paper engages in a critical examination regarding the utilisation of muscle force values from EMG sensors as indicators of physical effort and musical activity, particularly focusing on (the intuitively expected link to) sound levels. For this, it resides upon empirical work, namely practical insights drawn from a case study of music performance (Persian instrumental music) in the context of a music class. The findings indicate that muscle force can be explained by a small set of (six) statistically significant acoustic and movement features, the latter captured by a state-of-the-art (full-body inertial) motion capture system. However, no straightforward link to sound levels is evident.

Ergonomic Analysis of Dental Work in Different Oral Quadrants: A Motion Capture Preliminary Study among Endodontists.

Dentists, including endodontists, frequently experience musculoskeletal disorders due to unfavourable working postures. Several measures are known to reduce the ergonomic risk; however, there are still gaps in the research, particularly in relation to dental work in the different oral regions (Quadrants 1-4). In this study (of a pilot character), a total of 15 dentists (8 male and 7 female) specialising in endodontics were measured while performing root canal treatments on a phantom head. These measurements took place in a laboratory setting using an inertial motion capture system. A slightly modified Rapid Upper Limb Assessment (RULA) coding system was employed for the analysis of kinematic data. The significance level was set at p = 0.05. The ergonomic risk for the entire body was higher in the fourth quadrant than in the first quadrant for 80% of the endodontists and higher than in the second quadrant for 87%. For 87% of the endodontists, the ergonomic risk for the right side of the body was significantly higher in the fourth quadrant compared to the first and second quadrant. The right arm was stressed more in the lower jaw than in the upper jaw, and the neck also showed a greater ergonomic risk in the fourth quadrant compared to the first quadrant. In summary, both the total RULA score and scores for the right- and lefthand sides of the body ranged between 5 and 6 out of a possible 7 points. Considering this considerable burden, heightened attention, especially to the fourth quadrant with a significantly higher ergonomic risk compared to Quadrants 1 and 2, may be warranted.

Determination of dynamic air gap thickness and analysis of its relationship with firefighters’ joint movement

ABSTRACT Objectives. The purpose of this study was to calculate the dynamic air gap thickness between the human body and the turnout gear. Relationships between the air gap thickness and joint range of motion (ROM) were also explored. Methods. The air gap thickness and joint ROM of 12 male firefighters walking in a control condition with no self-contained breathing apparatus (SCBA) and three varying-strapped SCBAs were measured using three-dimensional (3D) body scanning and 3D inertial motion capture. The interpolation technique was employed to predict the air gap thickness curve during walking. The dynamic air gap thickness was compared with the joint ROM to see how they relate to the location and percentage of movement restriction. Results. During the walking, the air gap fluctuated as a sine curve. Carrying SCBA reduced the air gap thickness at the trunk most (F = 11.17, p < 0.001, η 2 = 0.63), and adjusting the shoulder strap length altered the air gap distribution at the trunk. The reduced air gap at the pelvis caused an incremental restriction on pelvis rotation. Conclusions. A compatibility design of the shoulder strap and hip belt in SCBA with the turnout jacket is suggested.

Intelligent robotic arm for human pose recognition based on teleoperation system

With the rapid development of skeleton recognition, machine learning and other technologies, we will find that there are great drawbacks in the control of manipulators. Robot teleoperation refers to the inclusion of human operation in the control loop of robot control. When robots deal with complex perception and a large number of tasks, teleoperation is far superior to intelligent programming when making decisions quickly and dealing with extreme situations. The goal of this paper is to build a robotic arm teleoperation system for human motion capture, so as to solve the problems that the control accuracy of the end of the robotic arm is not high and the motion of the robotic arm is greatly affected by the difference between the human arm in the current related research, the master-slave human motion mapping algorithm is designed and extended with machine learning algorithms. We use inertial motion capture to realize teleoperation, so as to avoid the use of the terminal position and orientation control method of the hand controller to form the control command of the remote robot after tedious calculation, and it is convenient for the operator to complete the attitude tracking task in real time. The obtained attitude information has a larger range, higher sensitivity and better dynamic performance.

Estimating Compressive and Shear Forces at L5-S1: Exploring the Effects of Load Weight, Asymmetry, and Height Using Optical and Inertial Motion Capture Systems.

This study assesses the agreement of compressive and shear force estimates at the L5-S1 joint using inertial motion capture (IMC) within a musculoskeletal simulation model during manual lifting tasks, compared against a top-down optical motion capture (OMC)-based model. Thirty-six participants completed lifting and lowering tasks while wearing a modified Plug-in Gait marker set for the OMC and a full-body IMC set-up consisting of 17 sensors. The study focused on tasks with variable load weights, lifting heights, and trunk rotation angles. It was found that the IMC system consistently underestimated the compressive forces by an average of 34% (975.16 N) and the shear forces by 30% (291.77 N) compared with the OMC system. A critical observation was the discrepancy in joint angle measurements, particularly in trunk flexion, where the IMC-based model underestimated the angles by 10.92-11.19 degrees on average, with the extremes reaching up to 28 degrees. This underestimation was more pronounced in tasks involving greater flexion, notably impacting the force estimates. Additionally, this study highlights significant differences in the distance from the spine to the box during these tasks. On average, the IMC system showed an 8 cm shorter distance on the X axis and a 12-13 cm shorter distance on the Z axis during lifting and lowering, respectively, indicating a consistent underestimation of the segment length compared with the OMC system. These discrepancies in the joint angles and distances suggest potential limitations of the IMC system's sensor placement and model scaling. The load weight emerged as the most significant factor affecting force estimates, particularly at lower lifting heights, which involved more pronounced flexion movements. This study concludes that while the IMC system offers utility in ergonomic assessments, sensor placement and anthropometric modeling accuracy enhancements are imperative for more reliable force and kinematic estimations in occupational settings.

Kinematic analysis of preparation for transferring from wheelchair to bed

ABSTRACT This study aimed to clarify the kinematics, particularly of the shoulder and hip joints, during preparation for manual wheelchair-to-bed transfer (i.e. when flipping up the arm and foot supports). This cross-sectional study included 32 able-bodied individuals. The kinematics of the shoulder and hip joints when the arm and foot supports were flipped up of manual wheelchair, were evaluated using a markerless inertial sensor-based motion capture system. We found that flipping the arm support upwards involved a large amount of abduction, internal and external rotation, flexion, and extension at the shoulder joint, whereas flipping the foot support upwards involved a large amount of flexion at the hip joint. The findings suggest that it is necessary to consider the range of motion required to flip up the arm and foot supports of manual wheelchairs, particularly in those with limited shoulder and hip range of motion such as older people, neuromuscular disorders, and orthopedic disorders.

Can single-use versus standard duodenoscope improve ergonomics in ERCP? A comparative, simulation-based pilot study.

Background and study aims Musculoskeletal disorders (MSDs) and injuries (MSIs) are frequent in gastrointestinal endoscopy. The aim of this study was to assess potential ergonomic advantages of a lighter single-use duodenoscope compared with a standard reusable one for endoscopists performing endoscopic retrograde cholangiopancreatography (ERCP). Methods Three experienced endoscopists performed an ergonomic, preclinical, comparative protocol-guided simulation study of a single-use and a standard reusable duodenoscope using an anatomic bench model. Surface EMG signals from left forearm and arm muscles were recorded. A commercial inertial sensor-based motion capture system was applied to record body posture as well. Results A significant lowering of root mean square amplitude and amplitude distribution of biceps brachii signal (ranging from 13% to 42%) was recorded in all the participants when using a single-use duodenoscope compared with a reusable one. An overall reduction of muscle activation amplitude and duration was also associated with the single-use duodenoscope for forearm muscles, with different behaviors among subjects. Participants spent most of the time in wrist extension (> 80%) and ulnar deviation (> 65%). A consistent pattern of functional range of motion employed for completing all procedures was observed. Conclusions Our study showed that a lighter scope has a promising effect in reducing upper arm muscle activity during ERCP with potential benefit on musculoskeletal health in the ERCP setting.

Understanding Musculoskeletal Loadings among Supermarket Checkout Counter Cashiers: A Biomechanical Analysis

Work-related musculoskeletal disorders (WMSD) are highly prevalent among supermarket cashiers. These disorders are frequently related to the adoption of awkward postures and manual materials handling. This study aimed to analyze musculoskeletal loadings in supermarket cashiers, considering the handling of different products and different checkout conditions. To accomplish this, we employed an inertial motion capture system to measure full-body kinematics while simulating 19 cashier tasks. The study included five female cashiers from a supermarket in Northern Portugal, ranging in age from 19 to 61 years old. Using joint angles, material load, and muscle function as input parameters, we conducted the musculoskeletal loadings assessment using the Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA) methods. Results showed that RULA scores were higher for the microtasks that involved product scanning. Regarding microstasks analyzed by REBA, the replacement of paper rolls for the receipt machine at the checkout counter yields the highest scores. Based on these findings, there is a compelling need to redesign supermarket checkout workstations to alleviate the physical demands placed on cashiers and to ensure organizational sustainability.