One generally has the impression that one feels one's hand at the same location as one sees it. However, because our brain deals with possibly conflicting visual and proprioceptive information about hand position by combining it into an optimal estimate of the hand's location, mutual calibration is not necessary to achieve such a coherent percept. Does sensory integration nevertheless entail sensory calibration? We asked subjects to move their hand between visual targets. Blocks of trials without any visual feedback about their hand's position were alternated with blocks with veridical visual feedback. Whenever vision was removed, individual subjects' hands slowly drifted toward the same position to which they had drifted on previous blocks without visual feedback. The time course of the observed drift depended in a predictable manner (assuming optimal sensory combination) on the variable errors in the blocks with and without visual feedback. We conclude that the optimal use of unaligned sensory information, rather than changes within either of the senses or an accumulation of execution errors, is the cause of the frequently observed movement drift. The conclusion that seeing one's hand does not lead to an alignment between vision and proprioception has important consequences for the interpretation of previous work on visuomotor adaptation.adaptation ͉ motor control ͉ vision ͉ proprioception ͉ drift O ne generally has the impression that one feels one's hand at the same location as one sees it. This impression has formed the basis for many theories about the calibration of our senses (1, 2), about how movements are controlled (3), and about the formation of body schema (4). The visual estimate of the position of one's hand (relative to oneself) is based on the retinal position of the hand's image and the orientation of the eyes. The proprioceptive estimate is based on joint or limb angles. When information is available in both modalities, we combine these sources of information into one coherent idea of where our hand is relative to ourselves (5), as has been modeled successfully assuming an optimal combination of sensory information (6-8) (Fig. 1A). The optimal combination of information from multiple sensors is a weighted average, with weights based on the precision (the inverse of the variance, see Eq.

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We present a prototype of a flexible nitinol needle (φ 1.0 mm and length 172 mm) integrated with an array of 12 Fiber Bragg Grating (FBG) sensors. These sensors measure the axial strain, which enables the computation of the needle curvature. We reconstruct the three-dimensional (3-D) needle shape from the curvature. Experiments are performed where the needle is deflected in free space. The maximum errors between the experiments and beam theory-based model are 0.20 mm (in-plane deflection with single bend), 0.51 mm (in-plane deflection with double bend), and 1.66 mm (out-of-plane). We also describe kinematics-based and mechanics-based models for predicting the 3-D needle shape during insertion into soft tissue. We perform experiments where the needle is inserted into a soft-tissue simulant, and the 3-D needle shape is reconstructed using the FBG sensors. We compare the reconstructed needle shape to deflection obtained from camera images and our models. The maximum error between the experiments and the camera images is 0.74 mm. The maximum errors between the kinematics-based and mechanics-based models and the camera images are 3.77 mm and 2.20 mm, respectively. This study demonstrates that deflection models and needles integrated with FBG sensors have the potential to be used in combination with clinical imaging modalities in order to enable accurate needle steering.

Box trainers equipped with sensors may help in acquiring objective information about a trainee's performance while performing training tasks with real instruments. The main aim of this study is to investigate the added value of force parameters with respect to commonly used motion and time parameters such as path length, motion volume, and task time. Two new dynamic bimanual positioning tasks were developed that not only requiring adequate motion control but also appropriate force control successful completion. Force and motion data for these tasks were studied for three groups of participants with different experience levels in laparoscopy (i.e., 11 novices, 19 intermediates, and 12 experts). In total, 10 of the 13 parameters showed a significant difference between groups. When the data from the significant motion, time, and force parameters are used for classification, it is possible to identify the skills level of the participants with 100% accuracy. Furthermore, the force parameters of many individuals in the intermediate group exceeded the maximum values in the novice and expert group. The relatively high forces used by the intermediates argue for the inclusion of training and assessment of force application during tissue handling in future laparoscopic skills training programs.