For centuries, scientific research has succeeded by chronicling experiments with pinpoint accuracy. Yet despite all the progress in the actual laboratory, recording is often still done manually, in notebooks, logs or computer systems for instance. In the future, a gesture recognition system could perform this task for scientists.
In this interview with MEDICA-tradefair.com, Marc Andre Daxer talks about the development of a tracking system for laboratory use, defines the areas where it creates added value and reveals in which direction laboratory automation is heading.
Mr. Daxer, you developed a tracking system for the automated documentation of laboratory experiments. How does this system work exactly?
Marc Andre Daxer: Our tracking system recognizes gestures and hand motion. It was designed by our department – Laboratory Automation and Biomanufacturing Engineering – in collaboration with the Department of Machine Vision and Signal Processing. The demonstrator was subsequently implemented by my colleague Christian Jauch from our partner department.
We use a 3D camera in our prototype that is equipped with rudimentary gesture recognition technology already provided by the developer. We can utilize this feature to infer procedural steps from the recognized hand gestures in the right context. For instance, if I hold my hand as if I am holding a long, cylindrical object and make a pressure movement with my thumb, this should be interpreted as pipetting. When we subsequently combine this information with object recognition, which then identifies the pipette and the target vessel, it allows us to significantly increase the accuracy and reliability of the complete system. We continue to enhance these algorithms at the same time and by now have a gesture recognition accuracy of over 90 percent at our fingertips. ...
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