Three-dimensional (3D) object reconstruction is the process of building a 3D model of a real object. This task is performed by taking several scans of an object from different locations (views). Due to the limited field of view of the sensor and the object's self-occlusions, it is a difficult problem to solve. In addition, sensor positioning by robots is not perfect, making the actual view different from the expected one. We propose a next best view (NBV) algorithm that determines each view to reconstruct an arbitrary object. Furthermore, we propose a method to deal with the uncertainty in sensor positioning. The algorithm fulfills all the constraints of a reconstruction process, such as new information, positioning constraints, sensing constraints and registration constraints. Moreover, it improves the scan's quality and reduces the navigation distance. The algorithm is based on a search-based paradigm where a set of candidate views is generated and then each candidate view is evaluated to determine which one is the best. To deal with positioning uncertainty, we propose a second stage which re-evaluates the views according to their neighbours, such that the best view is that which is within a region of the good views. The results of simulation and comparisons with previous approaches are presented.
5 December 2013 in IEEE Transactions on Neural Systems and Rehabilitation Engineering
Virtual reality platforms capable of assisting rehabilitation must provide support for rehabilitation principles: promote repetition, task oriented training, appropriate feedback, and a motivating environment. As such, development of these platforms is a complex process which has not yet reached maturity. This paper presents our efforts to contribute to this field, presenting Gesture Therapy, a virtual reality-based platform for rehabilitation of the upper limb. We describe the system architecture and main features of the platform and provide preliminary evidence of the feasibility of the platform in its current status.
Evidence of superiority of robot training for the hand over classical therapies in stroke patients remains controversial. During the subacute stage, hand training is likely to be the most useful. To establish whether robot active assisted therapies provides any additional motor recovery for the hand when administered during the subacute stage (<4 months from event) in a Mexican adult population diagnosed with stroke. Compared to classical occupational therapy, robot based therapies for hand recovery will show significant differences at subacute stages. A randomized clinical trial. A between subjects randomized controlled trial was carried out on subacute stroke patients (n = 17) comparing robot active assisted therapy (RT) with a classical occupational therapy (OT). Both groups received 40 sessions ensuring at least 300 repetitions per session. Treatment duration was (mean ± std) 2.18 ± 1.25 months for the control group and 2.44 ± 0.88 months for the study group. The primary outcome was motor dexterity changes assessed with the Fugl-Meyer (FMA) and the Motricity Index (MI). Both groups (OT: n = 8; RT: n = 9) exhibited significant improvements over time (Non-parametric Cliff's delta-within effect sizes: dwOT-FMA = 0.5, dwOT-MI = 0.5, dwRT-FMA = 1, dwRT-MI = 1). Regarding differences between the therapies; the Fugl-Meyer score indicated a significant advantage for the hand training with the robot (FMA hand: WRS: W = 8, p <0.01), whilst the Motricity index suggested a greater improvement (size effect) in hand prehension for RT with respect to OT but failed to reach significance (MI prehension: W = 17.5, p = 0.080). No harm occurred. Robotic therapies may be useful during the subacute stages of stroke - both endpoints (FM hand and MI prehension) showed the expected trend with bigger effect size for the robotic intervention. Additional benefit of the robotic therapy over the control therapy was only significant when the difference was measured with FM, demanding further investigation with larger samples. Implications of this study are important for decision making during therapy administration and resource allocation.