Force feedback has proven to be beneficial in the domain of robot-assisted rehabilitation. According to the patients� personal needs,\r\nthe generated forces may either be used to assist, support, or oppose their movements. In our current research project, we focus\r\nonto the upper limb training for MS (multiple sclerosis) and CVA (cerebrovascular accident) patients, in which a basic building\r\nblock to implement many rehabilitation exercises was found. This building block is a haptic linear path: a second-order continuous\r\npath, defined by a list of points in space. Earlier, different attempts have been investigated to realize haptic linear paths. In order to\r\nhave a good training quality, it is important that the haptic simulation is continuous up to the second derivative while the patient\r\nis enforced to follow the path tightly, even when low or no guiding forces are provided. In this paper, we describe our best solution\r\nto these haptic linear paths, discuss the weaknesses found in practice, and propose and validate an improvement.
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