Today there is a great deal of collective knowledge about how certain movement patterns lead to increased risks and the damage they can cause. On the other hand, there is a lack of simple and cost-effective ways of measuring these risks reliably.
We have developed a product that addresses this problem.
Wavr has previously talked about “body mounted sensor technology” and “smart body-close technology”. Now we have given our technology a name – Zentnl.
Imagine your regular work clothes. Sewn into the clothes are interconnected sensors and a hub that transmits measurement data wirelessly. The sensors tell you in real time how you move i.e. how different joints are activated, their angles and angular velocity.
This measurement data is received by a cloud service where an AI analyzes and compares your movement patterns with previously known risk factors. This gives you as a user an idea of what ergonomic risk factors you are exposed to in your everyday life. This is to give you an idea of where adjustments need to be made in the working environment to prevent wear injuries.
The methods commonly used in the workplace today to assess ergonomic risks are observation methods. In practice, this means that a knowledgeable person comes out and looks at the business and fills out a checklist. The problem with this method is that the variations between assessors are large and that they cannot capture sufficiently detailed information about an individual’s movement patterns. In other words, with observation methods, we have a very inadequate basis for quantitatively understanding what is happening in the workplace. It will therefore be difficult to really know whether we are exceeding recommendations or legal requirements for limit values.
The alternative to observation methods is to use experts in ergonomics who have access to motion labs or equipment for field measurements. The problem with this is that the equipment is very expensive, clumsy and requires expertise to be used and to be able to assimilate the measurement results.
At present, there is no method for measuring risk exposure for all employees in a cost-effective and easily accessible manner.
With actual data on how a person moves in their everyday lives, we are able to understand where and in what tasks there is an increased risk so that action can be taken. The effects are increased health in the individual and reduced loss of production due to illness.
Like other wearables for consumers, it is important that the user should be able to understand what they are looking at and be able to act on this information. A user of Zentnl should be able to easily absorb and understand the risks which they are exposed to. The measurement data shown to users is sufficient to improve safety and health without infringing on privacy.
“The digitization of motion and artificial intelligence will, in the future, be crucial to understanding physical load and even today there are simpler solutions such as watches and bracelets. With Zentnl, we are now creating completely new opportunities to understand, change and improve how we move in everyday life and at work.”Patrik Zayas, CEO
Through its innovative approach, Zentnl has great potential to significantly improve the working environment, safety and health in several industries.
“Change the way you move”WAVR Tech
This is what we’re building. This is Zentnl – for better public health