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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shankar, V. Sherbakov, L. Galbraith, B. Sohail, A. Livitz, G. Gorchetchnikov, A. Ames, H. Guenther, F.H. Versace, M. |
| Copyright Year | 2013 |
| Description | Author affiliation: Center of Excellence for Learning in Educ., Sci., & Technol., Boston Univ. & CELEST, Boston, MA, USA (Sherbakov, L.; Galbraith, B.; Sohail, A.; Livitz, G.; Gorchetchnikov, A.; Ames, H.; Versace, M.) || Depts. of Speech, Language, & Hearing Sci. & Biomed. Eng., Boston Univ., Boston, MA, USA (Guenther, F.H.) || GRASP Lab., Univ. of Pennsylvania, Philadelphia, PA, USA (Shankar, V.) |
| Abstract | Co-robotic assistants, or Cobots can improve the quality of life for individuals with locked-in syndrome (LIS) by allowing augmented control over their surroundings. Implemented in collaboration between the Boston University Neuromorphics Lab and Neural Prosthesis Lab, this work provides a proof of concept of an autonomous robot coupled with a non-invasive brain machine interface (BMI). The system uses Steady State Visually Evoked Potential (SSVEP) for target selection and a massively parallel neural network that models functionality of the primate “where” and “what” visual pathways. The simulated visual processes perform object recognition on images streamed from the Cobot equipped with a pan-and-tilt camera. In this paper, we describe a subcomponent of the system designed to allow the neural network to learn the identity of objects, the user to select a target object and the Cobot to perform autonomous visual investigation. |
| Starting Page | 1441 |
| Ending Page | 1444 |
| File Size | 1378748 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467319690 |
| ISSN | 19483554 |
| DOI | 10.1109/NER.2013.6696215 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-11-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Head Robot kinematics Cameras Brain models |
| Content Type | Text |
| Resource Type | Article |
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