We made comparative cadaver test in Vienna where we compared OptiNav optical navigation system with BrainLab navigation system. The results were pleasant surprise for us. First of all the results from both systems were quite the same. Our system gave more profits (our advantage) like: real view on surgery table (vision cameras instead of infrared), high resistance to dirt (blood etc) - BrainLab infrared balls were changed three times and one set of OptiNav markers was to the end of surgery, cost of set of BrainLab balls comparing to OptiNav markers (almost nothing - just printed and sterilized)

We designed modern tools for surgery working with navigation:

OptiNav did two surgery (knee prosthesis and hip resurfacing) as a cadaver test in Vienna:

OptiNav engineers have just designed modern advanced algorithm which is very helpful for resurfacing surgery. A surgeon just draw along surface of a neck. System is collecting points from the surface and using advanced mathematical algorithm fits a model of the neck to real points. After that system gives the information about correct drilling axis.

In the press: Control Engineering, August 2009

Audit ISO 9001:2000 certificate - positive result

New cameras from Prosilica in new case were tested. We did once again the same test. The test was done at a distance about 1,7m (between 1.3m to 2m). The distance between two cameras (the base) was about 28cm.

The result is again great. 3D RMS accuracy is 0.32mm. 79.6% of results have error below 0.35mm and 94.7% of results are below 0.7mm. Full test's protocol is here:
protocol_07_2007.pdf

The movie from laboratory: new_cameras.avi

Animation of our new cameras' case: camera_case.avi

New cameras from Prosilica were tested. We did the same test as for Point Grey cameras. The test was done at a distance about 1,8m (between 1.4m to 2.1m). The distance between two cameras (the base) was about 60cm.

The result is absolutely great. 3D RMS accuracy is 0.21mm. 89.4% of results have error below 0.35mm and 100% of results are below 0.7mm. This is more than 3 times better then for Point Grey cameras. Obviously the base (the distance between two cameras) was much biger and we used better lenses. Full test's protocol is here:
protocol_01_2007.pdf

Our goal was to have accuracy below 1mm in field of view (distance about 1m – 1.5m)

The average error is 0.53mm, and the RMS is 0.70mm. This means that in general, in average, the system has an accuracy around half a millimetre. For average value (30 samples) we had only one measurement a bit higher than 2mm (about 2.1mm), 97% below 1.5mm and almost 90% below 1mm.

A real system calculate relative data, it means that calculate distances to a reference point. As you can see in the protocol ( page 3) relative error for our system was very low - RMS 0.022 (RMS 0.018 averages). That was calculated as a distance in our x axis (Zeiss y axis) - OptiNav x and y axes are obviously the best. If we analyse the distance to one point in the middle of field of view, the RMS is 0.504mm so, z axis (Zeiss x axis) bring the largest error (page 1) That is cause of the distance in between two cameras (the base). Our camera has 120mm base - when you consider that error is decreasing proportionally to the square of the distance in between cameras (the base) - if we increasy only 4 times the distance in between two cameras (using the same poor lenses) we would have 16 times better accuracy.

As you can see on page 1 and especially on page 5 (explanation) of the protocol there is evident correlation between marker's location in cameras' field of view and size of error - for left and right edges the error is the biggest cause of the lenses' distortion ( our camera has very simple, cheap, one-element lens) ... that is the main reason why we must have good cameras with good lenses.

The first test was done for single marker and Point Grey cameras at a distance of about 1.6m. As you can see here: PointGrey_single_marker.avi 3D vectors are very unstable and RMS(z)= 0.77mm

Three markers object for the same Point Grey cameras gave us more stable 3D vectors and lower RMS(z)= 0.20mm for the same distance - you can see it here: PointGrey_object.avi

Very interesting results we had for Hamamatsu cameras (much more expensive with really good lenses). At a distance of about 4.7m we had RMS(z)=0.35mm and excellent RMS(z)= 0.02mm at a distance of about 1.6mm for single marker! The stability of 3D vectors was much better as well - see here: Hamamatsu_single_marker.avi

The first clinical test (Orthopedic Hospital in Otwock, Poland) - the navigation system was used in classical surgery (knee's prosthesis) as a double of classical tools. The result was very good and a part of surgery you can see here: surgery.avi
and in the photos:

OptiNav has ISO 9001:2000 certificate

The main goal was to check the software procedures and accuracy using phantom bone which had been tested in Zeiss laboratory. The Tests report confirm accuracy and correctness of the software for all knee's procedures (initial calibration of the pointer is very important).