Print Email Facebook Twitter Grasp recognition with spatiotemporal deep learning and proximity sensors in transradial prostheses Title Grasp recognition with spatiotemporal deep learning and proximity sensors in transradial prostheses Author van den Berg, Jasper (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Biomechanical Engineering; TU Delft Cognitive Robotics) Contributor Della Santina, C. (mentor) Kober, J. (graduation committee) Mastinu, Enzo (mentor) Degree granting institution Delft University of Technology Programme Mechanical Engineering | BioMechanical Design Date 2023-09-28 Abstract The traumatic loss of a hand is a horrific experience usually followed by significant psychological, functional and rehabilitation challenges. Even though much progress has been made in the past decades, the prosthetic challenge of restoring the human hand functionality is still far from being achieved. Autonomous prosthetic hands showed promising results and wide potential benefits; benefits that must be still explored. Here, we hypothesized that a combination of a radar sensor and a low-resolution time-of-flight camera can provide sufficient spatial and temporal information for deep learning algorithms to detect object shapes and materials in static and dynamic scenarios. To test this hypothesis, we analysed HANDdata, a recent human-object interaction dataset with a particular focus on reach-to-grasp actions, via both common and novel deep learning algorithms. The offline analyses reported here showed a great potential for both static and dynamic object characteristics recognition meant for autonomous grasping. Results seem to suggest modern, low-power radar as a potential key technology for next-generation intelligent and autonomous prostheses. Subject ProsthesesDeep LearningGrasp classificationAutonomous ControlRadarCNNTCNMaterial classificationObject classificationComputer Vision To reference this document use: http://resolver.tudelft.nl/uuid:01e0d45a-43d9-4f57-8844-f4354fab0cd3 Part of collection Student theses Document type master thesis Rights © 2023 Jasper van den Berg Files PDF jlg_vandenberg_4662342_Ms ... thesis.pdf 933.29 KB Close viewer /islandora/object/uuid:01e0d45a-43d9-4f57-8844-f4354fab0cd3/datastream/OBJ/view