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Exoskeletons, wearable sensors, artificial intelligence, computer vision, virtual and augmented reality, and data analytics: These emerging technologies are changing the way safety professionals approach ergonomics.
“This is a very exciting time in the field of ergonomics,” says Jeff Hoyle, M.S., CPE, director of ergonomics services at The Ergonomics Center at North Carolina State University. “There’s a lot of cool tech with the potential to make our jobs and our lives easier and, probably more importantly, improve the lives of those we serve on a daily basis.”
In a recent webinar hosted by our Ergonomics Practice Specialty, Hoyle provided a high-level overview of emerging technologies in ergonomics and their potential.
Emerging Technologies Are Rising to Today’s Ergonomic Challenges
The individual technologies often meet different needs. For example, exoskeletons aim to reduce musculoskeletal stress and the risk of injury related to factors such as task complexity, awkward postures and confined or restricted work areas. Computer vision can help safety professionals assess hazards and recommend ergonomic improvements.
Keep an eye on these five emerging technologies in ergonomics.
1. Exoskeletons and Exosuits
As defined by the ASTM International Committee F48 on Exoskeletons and Exosuits, an exoskeleton is a “wearable device that augments, enables, assists and/or enhances motion, posture or physical activity through mechanical interaction with the body.” Exosuits are similar but have primarily soft and/or elastic structures.
What Are Some Examples of Exoskeletons and Exosuits?
There are two different types of exoskeletons: Active and passive.
An active exoskeleton is powered by one or more actuators or electrical motors. An active device might support the arms, the back, and/or legs and may have built-in connected sensors that capture motion data to compile into a risk index. These may also have haptic or auditory feedback.
Passive exoskeletons have no external power source, but may have internal springs or cams or the ability to store energy. Some passive exoskeletons support the arms for overhead tasks, others support the back for lifting and bending tasks, and others support the legs for squatting, stooping, or knee-bending tasks.
How Are Exoskeletons and Exosuits Being Used Today?
Research is ongoing, but results to date suggest promising reductions in muscle activity and greater productivity for certain repetitive or static overhead types of work. However, Hoyle cautions that some studies have indicated the biomechanical impacts were not beneficial and that the use of exoskeletons actually increased mental workload in one study.
If you’re considering this technology, Hoyle recommends conducting a pilot before large-scale implementation.
2. Wearable Sensor Technology
Wearable sensors produce data that, when input into software programs, can help safety professionals understand the kinematics, postures and movements of employees wearing these sensors.
What Are Some Examples of Wearable Sensor Technology?
Wearable sensors can track movement, provide feedback to users and create a dashboard for managers. More comprehensive systems provide a multi-bodypart-sensor system and external elements.
Additionally, neurotechnology sensors can track mental activity to assess cognitive performance such as stress, focus/attention and distraction.
How Are Wearable Sensors Being Used Today?
While there is not yet third-party research on their efficacy, Toyota and Walmart have released preliminary results from their wearable sensor programs.
Toyota deployed wearable sensors at its Indiana production plant among 120 employees over two months and saw a 95% reduction in time to complete risk assessments; 84% of team members improve lifting techniques from haptics alone; and a 15% risk reduction by end of trial.
Walmart launched its wearables program in 2018 and it now includes 6,000 associates in 18 buildings. The company reported that ergonomic-related injuries decreased by nearly 65% among participating associates within the first year.
3. Computer Vision
Computer vision is a field of artificial intelligence that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and take action based on those inputs.
This includes applications like the facial recognition that unlocks your mobile phone, object detection that discovers damage on equipment machinery and notifies a mechanic, and object tracking used for autonomous vehicle navigation.
Computer vision can help automate or semi-automate ergonomic risk assessments.
What Are Some Examples of Computer Vision?
Several university-backed organizations offer this technology now:
- Velocity EHS and TuMeke Ergonomics offer partially automated ergonomic analysis tools for whole-body assessment. Safety professionals can take video with a smartphone and upload it to cloud software that partially automates inputs and outputs to streamline measures such as the Rapid Upper Limb Assessment (RULA), Rapid Entire Body Assessment (REBA) and the NIOSH Lifting Equation.
- Multimodal Occupational Posture Dataset (MOPED25) is an open-source tool from NC State University that used computer vision and a 14-camera system to assess full-body poses and motion for 25 occupational tasks.
4. Virtual Reality and Augmented Reality
Virtual reality fully immerses the user into an alternative world or reality, apart from the real world. Augmented reality overlays digital information in the real world or on real-world elements. You might see this every weekend while watching football: The stripe of yellow on the field marking the first down line is a form of augmented reality.
What Are Some Examples of Virtual Reality and Augmented Reality?
These emerging technologies are being broadly applied in several areas:
- Research and development: Virtual prototyping and design allows interaction with products before they’re manufactured and decreases development time.
- Manufacturing: By optimizing assembly steps, including design of layouts/equipment on production floor, and displaying assembly steps directly on an object, a site can reduce risk to employees and save time and money.
- Maintenance and repair: These operations can also be displayed on the object.
- Training: Inside a virtual world, employees can safely practice tasks they need to perform in the real world.
How Are Virtual Reality and Augmented Reality Being Used Today?
Hoyle shared three examples of major companies deploying this technology:
- Lockheed Martin’s Collaborative Human Immersive Laboratory uses virtual reality to create products or production environments. Employees can actually become avatars and step onto a factory floor.
- John Deere is using virtual reality to optimize tractor design and assembly, and perform maintenance tasks on a tractor before production.
- Construction company Choate uses augmented reality to help workers visualize and optimize construction tasks in their actual workspace before they start the build, which saves time and money.
5. Advanced Data Analytics
Advanced analytics are methods of analyzing data using sophisticated tools and computational power to understand trends, patterns and performance metrics. Predictive analytics are a subdivision of advanced analytics (and a form of artificial intelligence) that focus on identifying future events, outcomes and probabilities.
What Are Some Examples of Advanced Data Analytics?
This tech is being broadly applied in several areas:
- Sales: Forecasting trends in purchasing.
- Research and development: Implementing product improvements based on performance and/or failures, customer service complaints and maintenance requests.
- Manufacturing: Using data about injuries, risk, production bottlenecks and quality/rework to mitigate these concerns.
- Maintenance/repair: Employing software to predict when equipment will need servicing.
How Are Data Analytics Being Used Today?
In aeronautics, 3D-imaging technology, essentially computer vision and data analytics, has been used to streamline diagnostics and maintenance on F-35 and F-22 fighter planes.
In construction, data analytics are helping identify and predict job site risks and streamline tasks, including worker safety.
What Should Safety Professionals Consider When Evaluating Emerging Technologies?
Despite the promise of these technologies, safety professionals must consider several adoption challenges when assessing their potential use:
- Cost: As these technologies become more widely available, costs will decrease and more companies will realize a positive return on investment, including greater injury prevention.
- Scalability: Many of these technologies are designed to assess a single person, such as computer vision technology and some wearables.
- Data accuracy: Many companies claim to produce accurate data, but Hoyle says he’s “not sold” on those claims because of his own pilot testing of computer vision systems. “There’s a lot of promise, but additional validation testing is needed,” he notes.
- Data security and privacy: Videos of employees and risk metrics must be protected.
- Data processing power: The amount of data generated is enormous and the processing power needed to analyze it can be expensive, Hoyle says.
“As practitioners, we have to get involved with understanding these technologies and even get involved with the development to advance us forward,” Hoyle says. “I’m really optimistic about the future, but we have to get involved to be a part of it.”
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