Alle publicaties voor Arjan Gijsberts
2020
| , , , , , , , , , en , Gaze, visual, myoelectric, and inertial data of grasps for intelligent prosthetics (2020), in: Scientific Data, 7:1(1--15) |
| , , , , , , , , , , , , en , Gaze, visual,myoelectric data of grasps for intelligent prosthetics (2020), in: Nature Scientific Data |
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2019
| , , , , , , , , en , Effects of hand amputation surgery procedures on sEMG activity to control robotic hand prostheses, in: FESSH, Berlin, Germany, 2019 |
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, , , , en , On the visiomotor behavior of amputees and able-bodied people during grasping, (2019), in: Frontiers in Bioengienering and Biotechnology
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2018
| , , , , , , , , en , Aiming with varying degrees of accuracy requirements: Fitt’s Law and associated gaze behaviour in upper limb amputees, in: Urobody conference, Bremen, Germany, 2018 |
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| , , , , , , , , , , en , Apparent motion perception in upper limb amputees with phantom sensations: obstacle shunning and obstacle tolerance, in: Hand, Brain and Technology: The Somatosensory System, Monte Verità, Switzerland, 2018 |
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| , , , , , , , , , en , Apparent motion perception in upper limb amputees with phantom sensations: obstacle shunning and obstacle tolerance, in: Proceedings of the ACNS conference 2018, Melbourne, Australia, 2018 |
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| , , , , , , , , , , , , en , Myo-electricity and gaze tracking data to improve hand prosthetics and neuro-cognitive examination, in: FESSH 2018, Copenhagen, Denmark, 2018 |
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| , , , en , Visual Cues to Improve Myoelectric Control of Upper Limb Prostheses, in: 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), Enschede, The Netherlands, pagina's 783-788, IEEE, 2018 |
[DOI] [URL] |
2017
| , , , , en , Analysis of the repeatability of grasp recognition for hand robotic prosthesis control based on sEMG data, in: IEEE International Conference on Rehabilitation Robotics, London, UK,, 2017 |
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| , , , , , , , , , , , en , Megane Pro: myo-electricity, visual and gaze tracking integration as a resource for dexterous hand prosthetics, in: IEEE International Conference on Rehabilitation Robotics, London, UK, 2017 |
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2016
, , , , , , , en , Clinical Parameter Effect on the Capability to Control Myoelectric Robotic Prosthetic Hands (2016), in: Journal of Rehabilitation Research and Development, 53:3(345-358)
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2015
, , , , , , , en , Characterization of a Benchmark Database for Myoelectric Movement Classification (2015), in: Transactions on Neural Systems and Rehabilitation Engineering, 23:1(73-83)
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[DOI] [URL] |
2014
| , , en , Classification of hand movements in amputated subjects by sEMG and accelerometers, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA, 2014 |
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| , , , , , , , en , Electromyography data for non-invasive naturally controlled robotic hand prostheses (2014), in: Scientific Data, 1:140053 |
[DOI] [URL] |
, , , en , Measuring Movement Classification Performance with the Movement Error Rate (2014), in: IEEE Transactions on neural systems and rehabiliation engineering
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| , , en , Natural Control Capabilities of Robotic Hands by Hand Amputated Subjects, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago (USA), IEEE, 2014 |
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2013
| , , , en , Dexterous Control of Prosthetic Hands, in: ICAR 2013 Proceedings, Montevideo, Uruguay, 2013 |
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2012
| , , , , , , , en , Building the NINAPRO Database: A Resource for the Biorobotics Community, in: Proceedings of the IEEE International Conference on Biomedical Robotics and Biomechatronics, Roma, Italy, pagina's 51, 2012 |
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| , , , , , en , Experiences in the Creation of an Electromyography Database to Help Hand Amputated Persons, in: Proceedings of the 24th European Medical Informatics Conference - MIE2012, Pisa, Italy, 2012 |
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