When we grasp an object, our visuomotor system has to solve an intricate problem: how to find the best out of an infinity of possible contact points of the fingers with the object? The contact point selection model (CoPS) we present here solves this problem and predicts human grasp point selection in precision grip grasping by combining a few basic rules that have been identified in human and robotic grasping. Usually, not all of the rules can be perfectly satisfied. Therefore, we assessed their relative importance by creating simple stimuli that put them into conflict with each other in pairs. Based on these conflict experiments we made model-based grasp point predictions for another experiment with a novel set of complexly shaped objects. The results show that our model predicts the human choice of grasp points very well, and that observers' preferences for their natural grasp angles is as important as physical stability constraints. Incorporating a human grasp point selection model like the one presented here could markedly improve current approaches to cortically guided arm and hand prostheses by making movements more natural while also allowing for a more efficient use of the available information.

Choosing appropriate grasp points is necessary for successfully interacting with objects in our environment. We brought two possible determinants of grasp point selection into conflict: the attempt to grasp an object near its center of mass to minimize torque and ensure stability and the attempt to minimize movement distance. We let our participants grasp two elongated objects of different mass and surface friction that were approached from different distances to both sides of the object. Maximizing stability predicts grasp points close to the object's center, while minimizing movement costs predicts a bias of the grasp axis toward the side at which the movement started. We found smaller deviations from the center of mass for the smooth and heavy object, presumably because the larger torques and more slippery surface for the heavy object increase the chance of unwanted object rotation. However, our right-handed participants tended to grasp the objects to the right of the center of mass, irrespective of where the movement started. The rightward bias persisted when vision was removed once the hand was half way to the object. It was reduced when the required precision was increased. Starting the movement above the object eliminated the bias. Grasping with the left hand, participants tended to grasp the object to the left of its center. Thus, the selected grasp points seem to reflect a compromise between maximizing stability by grasping near the center of mass and grasping on the side of the acting hand, perhaps to increase visibility of the object.

When grasping rectangular or circular objects with a precision grip the digits close in on the object in opposite directions. In doing so the digits move perpendicular to the local surface orientation as they approach opposite sides of the object. This perpendicular approach is advantageous for accurately placing the digits. Trapezoidal objects have non-parallel surfaces so that moving the digits in opposite directions would make the digits approach the contact surfaces at an angle that is not 90°. In this study we examined whether this happens, or whether subjects tend to approach trapezoidal objects' surfaces perpendicularly. We used objects of diVerent sizes and with diVerent surface slants. Subjects tended to approach the object's surfaces orthogonally, suggesting that they aim for an optimal precision of digit placement rather than simply closing their hand as it reaches the object.