Evaluation of sensor configurations for robotic surgical instruments

Designing surgical instruments for robotic-assisted minimally-invasive surgery (RAMIS) is challenging due to constraints on the number and type of sensors imposed by considerations such as space or the need for sterilization. A new method for evaluating the usability of virtual teleoperated surgical instruments based on virtual sensors is presented. This method uses virtual prototyping of the surgical instrument with a dual physical interaction, which allows testing of different sensor configurations in a real environment. Moreover, the proposed approach has been applied to the evaluation of prototypes of a two-finger grasper for lump detection by remote pinching. In this example, the usability of a set of five different sensor configurations, with a different number of force sensors, is evaluated in terms of quantitative and qualitative measures in clinical experiments with 23 volunteers. As a result, the smallest number of force sensors needed in the surgical instrument that ensures the usability of the device can be determined. The details of the experimental setup are also included.

Independent uncertainty estimates for coefficient based sea surface temperature retrieval from the Along-Trck Scanning Radiometer instruments

We establish a methodology for calculating uncertainties in sea surface temperature estimates from coefficient based satellite retrievals. The uncertainty estimates are derived independently of in-situ data. This enables validation of both the retrieved SSTs and their uncertainty estimate using in-situ data records. The total uncertainty budget is comprised of a number of components, arising from uncorrelated (eg. noise), locally systematic (eg. atmospheric), large scale systematic and sampling effects (for gridded products). The importance of distinguishing these components arises in propagating uncertainty across spatio-temporal scales. We apply the method to SST data retrieved from the Advanced Along Track Scanning Radiometer (AATSR) and validate the results for two different SST retrieval algorithms, both at a per pixel level and for gridded data. We find good agreement between our estimated uncertainties and validation data. This approach to calculating uncertainties in SST retrievals has a wider application to data from other instruments and retrieval of other geophysical variables.