Two weeks ago, I talked about the limitations of motion capture tools. (I mentioned that these tools have been referred to as “Laser-guided RULA”, which I can now attribute to Bob Sesek from Auburn,
Alabama.) This technology is exciting for ergonomists because it can automate tasks that are time-consuming. Like everyone else, we are strongly motivated to find ways to improve our efficiency through technology. But not at the expense of validity.
Data collection
At Taylor’d Ergonomics, when we assess a task, we measure the forces applied by the hands, document the direction that the force is applied and the location of the hands in space. As discussed previously, these force measurements are critical to understanding strain/sprain injury risk. We also
measure how often the task is performed (frequency), and how long the effort requires (duration); video can be handy for these “time” measures, if we can’t see the task multiple times in real life. While we are out in the workplace gathering all this information, we are also building a relationship with the employee, learning about techniques that help, workplace conditions that make the job harder, and ideas for improving the job.
Data analysis
If the task can be assessed with a psychophysical tool, like the Liberty Mutual Manual Material
Handling (LM MMH) equations, then we would do that, because this tool is fast, has been validated, and is widely accepted. The LM MMH equations are an updated version of the “Snook tables” that were originally published in 1978.
For all other tasks, we use a biomechanical model to evaluate how much effort the task requires, as a percent of maximum strength, typically for female worker with 25th percentile strength. If this worker can safely perform the tasks, then stronger workers should be at lower risk. Until recently, we used a combination of University of Michigan’s 3D Static Strength Prediction Program, HandPak (Potvin), Arm Force Field (LaDelfa and Potvin) and Maximum Acceptable Effort (MAE, Potvin). We are now using Work(s) (Potvin and Agnew), which integrates all these tools.
A job often includes several different tasks, so we assess them all, and use a cumulative
fatigue model called RCRA to determine whether the work cycle allows sufficient rest for the worker to continue to safely perform the work activities for the entire shift. If we do not account for the variety of tasks, the LM MMH and MAE assessment tools assume that the worker is resting between efforts.
These tools are computerized, so we’re not doing complex math on a piece of paper (circa 1990), but they do require more effort than pointing a phone at a worker. Dr. Potvin, one of the researchers who developed this method, posted last week on Linked In about his approach to ergonomics assessments. I encourage all ergonomists to integrate his guidance into their process. (Full disclosure: Dr. Potvin was my advisor when I finished my Master’s degree, almost 30 years ago. So yes, I’m a big fan. I have a deep respect for his knowledge and approach, and he and Mike Agnew
have been patient and responsive as our team has adopted this new tool.)
This data analysis process takes more time than the motion capture tools, of course, but it allows us to:
- Assess the demands of gripping and pinching.
- Assess tasks that require twisting and sideways bending
- Assess forces in all directions. It’s rare, lately, for us to encounter a two-handed task in front of the body with a good grip.
- Explore how changes will affect risk. (What if we raise the conveyor? What if we reduce the weight but increase the frequency? What if we rotate between two different jobs? What if we remove an obstacle so the worker can push forward instead of sideways?) These “what if” analyses add significant value for most of our clients.
I have reviewed several motion capture tools, and acknowledged where they might be helpful. They may allow you to screen lots of jobs quickly if you are prepared to measure force properly.
If you’re thinking about adopting this new technology, I encourage you to ask the vendor:
- How does the tool assess risk for the side of the body not showing in the video?
- Does the tool account for body postures that are not “forward/back”? (reaching to the side, for example, or back twisting)
- Does the tool evaluate wrist, gripping and pinching demands? If so, how?
- What guidance is provided for the analyst to objectively measure and input force? Will the model run without force data? (If so, how will analyst be accountable to measure this very important hazard?)
- Does the tool account for different strengths when applying force in different directions? (for example, pushing sideways vs. forward)
- What guidance is provided regarding which worker to videotape? If you assess the job using a video of a large male worker, can the tool predict the risk for a smaller worker?
There have been times during my career when I’ve wished I could click the “fast-forward” button and arrive at a time when data collection and analysis are more automated, so I could focus more on the creative, rewarding aspects of job improvement. I do believe that we’ll get there eventually, but I hope that the demand for flashy, colour-coded reports doesn’t blind us to the significant limitations of the currently available technology. If you want an analysis of risk, and you want to predict how risk will change with job improvements, we still must “measure stuff” and do the analysis work.
FAQs:
- How do motion capture toosl assess risk for the side of the body not visible in the video, and what potential limitations might arise from this limitation in assessment? The motion capture tool’s assessment of risk for the side of the body not visible in the video remains unclear. Understanding how the tool addresses this limitation is crucial to evaluating its overall effectiveness and reliability in assessing ergonomic risks comprehensively.
- Regarding the evaluation of wrist, gripping, and pinching demands, what specific methods or features do motion capture tools employ? How accurate and comprehensive are the tools in capturing and assessing these factors, and do they provide guidance for analysts to objectively measure and input force data? The article raises questions about how motion capture tools evaluate wrist, gripping, and pinching demands. Specific details about the tools’ methods in capturing and assessing these ergonomic factors are needed for readers to gauge the tool’s accuracy and comprehensiveness in addressing crucial aspects of ergonomic risk. Additionally, understanding the guidance provided to analysts for measuring and inputting force data is essential for accountability in the risk assessment process.