Haptic feedback is feedback relating to the sense of touch. Current research suggests that the use of haptic feedback could give an increase in speed and accuracy when doing certain tasks such as outlining organ contours in medical applications or even filling in spreadsheets. This master thesis project has two different goals concerning haptic feedback. The first is to try to improve the forces for the SensAble PHANTOM Omni® Haptic Device when used in an application to outline contours in medical images, to give the user better feedback. The PHANTOM Omni is a device able to read in user movement of an arm attached to it in three dimensions, but it is also able to output forces through this arm back to the user, i.e. giving haptic feedback. By improving these forces and thus providing better feedback, we hope that speed and accuracy increases for a user working with the mentioned application.
The second part of the project consists of evaluating if delays in a network between the haptic feedback device and the place where the data sets are located impact the user perceived quality or the outcome of the task. We do this by considering a number of potential architectures for distributing the image processing and generation of haptic feedback. By considering both of these goals we hope to demonstrate both a way to get faster and more accurate results when doing the tasks already mentioned (and other tasks), but also to understand the limitations of haptic performance with regard to distributed processing. We have successfully fulfilled our first goal by introducing a haptic force which seems quite promising. This should mean that the people working with outlining contours in medical images can work more effectively; which is good both economically for hospitals and quality of service-wise for patients.
Our results concerning the second goal indicate that a haptic system for outlining contour can work well when using this new haptic force, even on low quality data links (which can be used for example in battlefield medicine or by specialists to conduct long distance operations or examinations) -- if the system architecture distributes the functionality so as to provide low delay haptic feedback locally.
We have tried to compare our results from the second part with a model for the impact of network delay on voice traffic quality developed by Cole and Rosenbluth, but as there is not necessarily a numeric correspondence between the quality values that we used and the ITU MOS quality values for voice we cannot make a numeric comparison between our results and that model. However our experimental data seem to suggest that the decrease in perceived quality was not as fast as one might expect considering simply the ratios of the voice packet rate (typically 50 Hz) and the 1000 Hz rate of the haptic feedback loop. The decrease in quality seems to only be about one half of what the ratio of these rates might suggest (i.e., a factor of 10x faster decrease in quality with increasing delay rather than 20x).
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