Video based lifting technique coding system

A Simple Method to Optimally Select Upper-Limb Joint Angle Trajectories from Two Kinect Sensors during the Twisting Task for Posture Analysis

A trunk-twisting posture is strongly associated with physical discomfort. Measurement of joint kinematics to assess physical exposure to injuries is important. However, using a single Kinect sensor to track the upper-limb joint angle trajectories during twisting tasks in the workplace is challenging due to sensor view occlusions. This study provides and validates a simple method to optimally select the upper-limb joint angle data from two Kinect sensors at different viewing angles during the twisting task, so the errors of trajectory estimation can be improved. Twelve healthy participants performed a rightward twisting task. The tracking errors of the upper-limb joint angle trajectories of two Kinect sensors during the twisting task were estimated based on concurrent data collected using a conventional motion tracking system. The error values were applied to generate the error trendlines of two Kinect sensors using third-order polynomial regressions. The intersections between two error trendlines were used to define the optimal data selection points for data integration. The finding indicates that integrating the outputs from two Kinect sensor datasets using the proposed method can be more robust than using a single sensor for upper-limb joint angle trajectory estimations during the twisting task.

Support System for the Assessment and Intervention During the Manual Material Handling Training at the Workplace: Contributions From the Systematic Observation

Efficacy of classical manual material handling (MMH) training interventions on back pain prevention at the workplace has been called into question. The way that observation (self-observation or hetero-observation) is used in other areas to create feedback addressed to modify motor activities can justify innovative components for these interventions. However, their implementation and evaluation cannot be done without tackling the methodological challenge of developing a reliable observational instrument to measure manual handling practice during the training process. The aims of this study were: (1) justify and develop an hetero-observation (H-O) instrument to assess changes in the worker behavioral patterns with a level of analysis convenient to derive a parallel version for the systematic self-observation (S-O) during training on MMH; (2) provide evidence on the inter-rater reliability of the H-O instrument; (3) provide evidence on the usability of the S-O instrument and its perceived usefulness; and (4) provide evidence on the benefits that can be derived with the use of the H-O instrument to create feedback based on T-pattern and polar coordinate analysis. A mixed method approach mainly grounded on systematic observation was used. A convenience sample composed by blue-collar workers participated in the study. Based on literature review and expert opinion, the H-O instrument proposed was composed by six dimensions (feet, knee joints, back, elbow joints, load position, and interaction between back tilt and displacement) plus a structural dimension which defined MMH phases. The inter-rater reliability of this instrument was almost perfect for all dimensions using a tolerance level of 2 s (the range of time-unit kappa was from 0.93 to 0.97 and the range of event-based kappa was from 0.82 to 0.9). The usability and usefulness of the S-O instrument was highly valued by workers. Regarding the way to use hetero-observations to create feedback, the paper shows the great potential of T-pattern and polar coordinate analysis. The observational instruments developed combined with these techniques make it possible to characterize the body positions adopted during manual handling performance, and this is crucial to create feedback on performance instead of only feedback on results.

Using a marker-less method for estimating L5/S1 moments during symmetrical lifting

The aim of this study is to analyze the validity of a computer vision-based method to estimate 3D L5/S1 joint moment during symmetrical lifting. An important criterion to identify the non-ergonomic lifting task is the value of net moment at L5/S1 joint. This is usually calculated in a laboratory environment which is not practical for on-site biomechanical analysis. The validity of the proposed method, was assessed externally by comparing the results with a lab-based reference method and internally by comparing the estimated L5/S1 joint moments from top-down model and bottom-up model. It was shown that no significant differences in peak and mean moments between the two methods and intra-class correlation coefficients revealed excellent reliability of the proposed method (>0.91). The proposed method provides a reliable tool for assessment of lower back loads during occupational lifting and can be an alternative when the use of marker-based motion tracking systems is not possible.

Using mutual information to capture major concerns of postural control in a tossing activity

Human body motion for load-tossing activity was partitioned into three phases using four critical events based on the load position viz. lift-off, closest to body, peak and release. For each phase, three objective functions values, viz. mobilization, stabilization and muscular torque utilization, used to control the motion patterns, were then calculated. We hypothesize that the relationships between different objective functions can be extracted using information theory. The kinematic data obtained with 36 treatment combinations (2 tossing distances, 2 tossing heights, 3 weights, and 3 target clearances) was used to estimate the mutual information between each pair of objective functions and construct Chow-Liu trees. Results from this research indicate that there was no dominant concern in the first two phases of the activity; however, torque utilization and mobilization were found to be important factors in the third phase of the load tossing activity.

Effects of age and its interaction with task parameters on lifting biomechanics

This study investigated the age-related differences in lifting biomechanics. Eleven younger and 12 older participants were instructed to perform symmetric lifting tasks defined by different combinations of destination heights and load magnitudes. Lifting biomechanics was assessed. It was found that the trunk flexion in the starting posture was 32% lower and the peak trunk extension velocity was 46% lower in older participants compared with those in younger ones, indicating that older adults tended to use safer lifting strategies than did younger adults. Based on these findings, we recommend that physical exercise programmes may be a more effective ergonomic intervention for reducing the risks of low back pain (LBP) in lifting among older workers, compared with instructions of safe lifting strategies. As for younger workers, instructions of safe lifting strategies would be effective in LBP risk reduction.

The error of L5/S1 joint moment calculation in a body-centered non-inertial reference frame when the fictitious force is ignored

In ergonomics studies, linked segment models are commonly used for estimating dynamic L5/S1 joint moments during lifting tasks. The kinematics data input to these models are with respect to an arbitrary stationary reference frame. However, a body-centered reference frame, which is defined using the position and the orientation of human body segments, is sometimes used to conveniently identify the location of the load relative to the body. When a body-centered reference frame is moving with the body, it is a non-inertial reference frame and fictitious force exists. Directly applying a linked segment model to the kinematics data with respect to a body-centered non-inertial reference frame will ignore the effect of this fictitious force and introduce errors during L5/S1 moment estimation. In the current study, various lifting tasks were performed in the laboratory environment. The L5/S1 joint moments during the lifting tasks were calculated by a linked segment model with respect to a stationary reference frame and to a body-centered non-inertial reference frame. The results indicate that applying a linked segment model with respect to a body-centered non-inertial reference frame will result in overestimating the peak L5/S1 joint moments of the coronal plane, sagittal plane, and transverse plane during lifting tasks by 78%, 2%, and 59% on average, respectively. The instant when the peak moment occurred was delayed by 0.13, 0.03, and 0.09s on average, correspondingly for the three planes. The root-mean-square errors of the L5/S1 joint moment for the three planes are 21Nm, 19Nm, and 9Nm, correspondingly.

Estimating 3-D L5/S1 moments during manual lifting using a video coding system: validity and interrater reliability

OBJECTIVE

The aim of the study was to investigate the validity and interrater reliability of using a proposed video coding system to estimate the dynamical 3-D L5/ S1 joint moment on the basis of four key frames from video clips of asymmetric lifting tasks.

BACKGROUND

L5/S1 joint loading has been widely adopted to quantify low-back loading during lifting tasks. However, the measurement of L5/S1 joint loading usually requires a laboratory environment, which cannot be applied during field surveys.

METHOD

The validity of this system was investigated by comparing the estimated L5/S1 joint moments of various simulated lifting tasks with motion tracking system-based reference L5/S1 joint moments.

RESULTS

The comparison showed that the video coding system yielded good estimates on peak moment (r = .91, average absolute error [AAE] = 20.3 Nm) and cumulative moment (r = .88,AAE = 22.5 Nm.sec) of the sagittal plane. The interrater reliability of this system was assessed among 10 raters who used this system. The intraclass correlation ranged between .51 and .89 for the moments of different planes.

CONCLUSION

The results of the validity and interrater reliability analyses showed that the proposed video coding system could provide a good estimate of total L5/S1 joint loading on the basis of side-view video clips of the simulated lifting tasks.

APPLICATION

Although it was not as accurate as a motion tracking system for L5/S1 joint loading calculations, this approach can be an alternative for back load estimation for some lifting configurations when the use of motion tracking systems is not possible.

Two linear regression models predicting cumulative dynamic L5/S1 joint moment during a range of lifting tasks based on static postures

Previous studies have indicated that cumulative L5/S1 joint load is a potential risk factor for low back pain. The assessment of cumulative L5/S1 joint load during a field study is challenging due to the difficulty of continuously monitoring the dynamic joint load. This study proposes two regression models predicting cumulative dynamic L5/S1 joint moment based on the static L5/S1 joint moment of a lifting task at lift-off and set-down and the lift duration. Twelve men performed lifting tasks at varying lifting ranges and asymmetric angles in a laboratory environment. The cumulative L5/S1 joint moment was calculated from continuous dynamic L5/S1 moments as the reference for comparison. The static L5/S1 joint moments at lift-off and set-down were measured for the two regression models. The prediction error of the cumulative L5/S1 joint moment was 21 ± 14 Nm × s (12% of the measured cumulative L5/S1 joint moment) and 14 ± 9 Nm × s (8%) for the first and the second models, respectively. Practitioner Summary: The proposed regression models may provide a practical approach for predicting the cumulative dynamic L5/S1 joint loading of a lifting task for field studies since it requires only the lifting duration and the static moments at the lift-off and/or set-down instants of the lift.

Estimation of 3-D peak L5/S1 joint moment during asymmetric lifting tasks with cubic spline interpolation of segment Euler angles

Previous research proposed a method using interpolation of the joint angles in key frames extracted from a field-survey video to estimate the dynamic L5/S1 joint loading for symmetric lifting tasks. The advantage of this method is that there is no need to use unwieldy equipment for capturing full body movement for the lifting tasks. The current research extends this method to asymmetric lifting tasks. The results indicate that 4-point cubic spline interpolation of segment Euler angles combined with a biomechanical model can provide a good estimation of 3-D peak L5/S1 joint moments for asymmetric lifting tasks. The average absolute error in the coronal, sagittal, and transverse planes with respect to the local pelvis axes was 16Nm, 22Nm, and 11Nm, respectively. It was also found that the dynamic component of the peak L5/S1 joint moment was not monotonously convergent when the number of interpolation points was increased. These results can be helpful for developing applied ergonomic field-survey tools such as video bases systems for estimating L5/S1 moments of manual materials handling tasks.

The validity and interrater reliability of video-based posture observation during asymmetric lifting tasks

OBJECTIVE

The objective was to evaluate the validity and interrater reliability of a video-based posture observation method for the major body segment angles during asymmetric lifting tasks.

BACKGROUND

Observational methods have been widely used as an awkward-posture assessment tool for ergonomics studies. Previous research proposed a video-based posture observation method with estimation of major segment angles during lifting tasks. However, it was limited to symmetric lifting tasks. The current study extended this method to asymmetric lifting tasks and investigated the validity and the interrater reliability.

METHOD

Various asymmetric lifting tasks were performed in a laboratory while a side-view video camera recorded the lift, and the body segment angles were measured directly by a motion tracking system. For this study, 10 raters estimated seven major segment angles using a customized program that played back the video recording, thus allowing users to enter segment angles. The validity of estimated segment angles was evaluated in relation to measured segment angles. Interrater reliability was assessed among the raters.

RESULTS

For all the segment angles except trunk lateral bending, the estimated segment angles were strongly correlated with the measured segment angles (r > .8), and the intraclass correlation coefficient was greater than 0.75.

CONCLUSION

The proposed observational method was able to provide a robust estimation of major segment angles for asymmetric lifting tasks based on side-view video clips. The estimated segment angles were consistent among raters.

APPLICATION

This method can be used for assessing posture during asymmetric lifting tasks. It also supports developing a video-based rapid joint loading estimation method.

Prediction accuracy in estimating joint angle trajectories using a video posture coding method for sagittal lifting tasks

This study investigated prediction accuracy of a video posture coding method for lifting joint trajectory estimation. From three filming angles, the coder selected four key snapshots, identified joint angles and then a prediction program estimated the joint trajectories over the course of a lift. Results revealed a limited range of differences of joint angles (elbow, shoulder, hip, knee, ankle) between the manual coding method and the electromagnetic motion tracking system approach. Lifting range significantly affected estimate accuracy for all joints and camcorder filming angle had a significant effect on all joints but the hip. Joint trajectory predictions were more accurate for knuckle-to-shoulder lifts than for floor-to-shoulder or floor-to-knuckle lifts with average root mean square errors (RMSE) of 8.65 degrees , 11.15 degrees and 11.93 degrees , respectively. Accuracy was also greater for the filming angles orthogonal to the participant's sagittal plane (RMSE = 9.97 degrees ) as compared to filming angles of 45 degrees (RMSE = 11.01 degrees ) or 135 degrees (10.71 degrees ). The effects of lifting speed and loading conditions were minimal. To further increase prediction accuracy, improved prediction algorithms and/or better posture matching methods should be investigated. STATEMENT OF RELEVANCE: Observation and classification of postures are common steps in risk assessment of manual materials handling tasks. The ability to accurately predict lifting patterns through video coding can provide ergonomists with greater resolution in characterising or assessing the lifting tasks than evaluation based solely on sampling with a single lifting posture event.

A field evaluation method for assessing whole body biomechanical joint stress in manual lifting tasks

Work-related musculoskeletal injuries are often associated with overexertion of the body at work. The manual materials handling activity of lifting is a major source of work-related musculoskeletal disorders. Biomechanical evaluation offers useful information about the physical stress imposed on the worker's body joints; however, biomechanical analysis is usually tedious and complex. For evaluation purpose, the biomechanical method needs to be easy to apply in a field environment. Manual lifting occurs as one of the most common manual materials handling tasks in the workplace. A biomechanical evaluation method was developed based on the ratio of joint moment to joint capacity. The method was applied to evaluate the physical stress of manual lifting in truck loading jobs using a nine-link whole body joint model. Thirty eight industrial tasks were evaluated using the developed joint moment ratio. The moment ratio was compared with subjectively rated body discomfort, overall workload, and the NIOSH lifting index. The moment ratio was found to have a high correlation with the NIOSH lifting index. The biomechanical method can be used with relatively simple equipment and procedure which may be suitable for on-site ergonomic evaluation.

Development of a set of equations describing joint trajectories during para-sagittal lifting

Given a lifting task with predetermined starting and ending positions, the angular trajectories are usually very consistent with a distinctive pattern. This paper derives a set of equations that can describe the joint trajectories during a para-sagittal lifting task. Three optimal motion patterns were also expressed by the polynomials: minimal hand jerk, minimal center of gravity (CG) jerk, and minimal muscle utilization rate (MUR). The variability of the joint movements were synthesized by overlapping the optimal patterns.