Abstract
This is a live demonstration of the work described in [1] and [2] (paper ID 7153). The goal of this work is to use a neuromorphic model for providing tactile feedback to a prosthetic hand and user to improve grasping functionality. Custom force sensors are placed on the fingertips of a bebionc3 (Steeper, Leeds, UK) prosthetic hand and communicate with the prosthesis controller (Infinite Biomedical Technologies, Baltimore, USA). The prosthesis grip force is used as the input to a leaky integrate and fire (LIF) with spike rate adaption neuron model to produce a tactile signal represented by spiking information, which is similar to the behavior of mechanoreceptors found in humans. The prosthesis controller produces spiking information to capture the tactile signal during a grasping task. The neuromorphic tactile signal can then be used as grip force modulation [1] or for closed-loop sensory feedback as discussed in [2].
Original language | English (US) |
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Title of host publication | 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 1 |
Volume | 2018-January |
ISBN (Electronic) | 9781509058037 |
DOIs | |
State | Published - Mar 23 2018 |
Event | 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Torino, Italy Duration: Oct 19 2017 → Oct 21 2017 |
Other
Other | 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 |
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Country/Territory | Italy |
City | Torino |
Period | 10/19/17 → 10/21/17 |
ASJC Scopus subject areas
- Biomedical Engineering
- Electrical and Electronic Engineering
- Instrumentation