Abstract
Hand rehabilitation therapy is fundamental for post-stroke or post-surgery impairments. Traditional rehabilitation requires the presence of a therapist for executing and controlling therapy: this implies high costs, stress for the patient, and subjective evaluation of the therapy effectiveness. Alternative approaches, based on mechanical and tracking-based gloves, have been recently proposed. Mechanical devices are often expensive, cumbersome and patient specific, while tracking-based devices are not subject to this limitations, but, especially if based on a single tracking sensor, could suffer from occlusions. In this paper a multi-sensors approach, the Virtual Glove (VG), based on the simultaneous use of two orthogonal LEAP motion controllers, was presented. In particular, the VG design was summarized, an engineered version was presented and its characterization was performed through spatial measurements. Measurements have been compared with those collected with a accurate spatial positioning system for evaluating the VG precision. The proposed strategy described the procedure to be used for VG assembly and for making it to correctly operate.
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Acknowledgments
The Authors are very grateful the Department of Physics and Chemical Sciences of the University of L’Aquila for having allowed the use of the mill and, in particular, to Mr Francesco del Grande for his invaluable help in constructing the Virtual Glove support and collecting experimental measurements.
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Placidi, G., Cinque, L., Polsinelli, M., Spezialetti, M. (2018). Characterization of a Virtual Glove for Hand Rehabilitation Based on Orthogonal LEAP Controllers. In: De Marsico, M., di Baja, G., Fred, A. (eds) Pattern Recognition Applications and Methods. ICPRAM 2017. Lecture Notes in Computer Science(), vol 10857. Springer, Cham. https://doi.org/10.1007/978-3-319-93647-5_11
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