=Paper=
{{Paper
|id=Vol-3939/abstract4
|storemode=property
|title=Representing Bionic-vision Devices in the Neural Electronic Interface
						Ontology
|pdfUrl=https://ceur-ws.org/Vol-3939/abstract4.pdf
|volume=Vol-3939
|authors=Jisoo Seo,Alexander D. Diehl,Daniel L. Rathbun,Gopikrishnan M. Chandrasekharan,Callie McGrath,William D. Duncan
|dblpUrl=https://dblp.org/rec/conf/icbo/SeoDRCMD24
}}
==Representing Bionic-vision Devices in the Neural Electronic Interface
						Ontology==
<pdf width="1500px">https://ceur-ws.org/Vol-3939/abstract4.pdf</pdf>
<pre>
                         Representing Bionic-Vision Devices in the Neural
                         Electronic Interface Ontology – Abstract
                         Jisoo Seo1,∗ , Alexander D. Diehl1 , Daniel L. Rathbun2 , Gopikrishnan M. Chandrasekharan3 ,
                         Callie McGrath4 and William D. Duncan3
                         1
                           University at Buffalo, Buffalo, NY 14260, USA
                         2
                           Detroit Institute of Ophthalmology, Henry Ford Health, Detroit, MI 48202, USA
                         3
                           University of Florida College of Dentistry, Gainesville, FL 32610, USA
                         4
                           Independent Researcher, Tacoma, WA 98402, USA


                                     Abstract
                                     Devices such as retinal and cochlear implants improve the quality of life for those suffering from vision or hearing
                                     loss. These devices interface with the central nervous system to enhance (or augment) stimuli from the patient’s
                                     external environment. However, there are major obstacles to the effective use of this technology. Standards are
                                     lacking for defining the types of devices used for this purpose, the conditions under which these devices should
                                     be employed, the assessment of patients’ sensory ability, and the metrics for evaluating the performance of these
                                     devices. For example, due to the lack of precise epidemiological data to distinguish between low and ultra- low
                                     vision levels, it is difficult to estimate the number of suitable vision loss patients. To address these needs, we
                                     are developing the Neural Electronic Interface Ontology (NEIO). NEIO uses ontological principles to address
                                     these challenges. Genus-differentia definitions, taxonomic hierarchies, and formal relations precisely define the
                                     different kinds of neural-interface devices. Such definitions include device components and functions, and the
                                     pathological conditions that these devices address. Where relevant, we reuse classes from other ontologies in
                                     order to leverage the expertise of the developers of these ontologies and promote interoperability. For example,
                                     we use Uberon to represent the anatomical locations where the devices are implanted. We are using data from
                                     bionic-visions.org to create classes to represent the bionic-vision devices, relevant components of these devices,
                                     and the organizations that produce them. We are currently adding measures of visual ability. These measures will
                                     enable comparisons between outcomes from various sight restoration methods. The comparison classes include
                                     bionic-vision devices, gene therapy, stem-cell therapy, and pharmaceuticals. This work forms the foundation of
                                     an ontological framework to represent the assessment of visual ability. This framework will, in turn, facilitate the
                                     identification of appropriate vision restoration procedures for patients with a variety of eye diseases, thereby
                                     optimizing patient outcomes. Finally, although NEIO is currently focused on bionic vision, NEIO aims to provide
                                     a semantic framework for representing the domain of neural electronic interface technology in general.

                                     Keywords
                                     Ontology, Neural-Interface Devices, Bionic Vision, Retina Implant




                         15th International Conference on Biomedical Ontologies 2024, July 17-19, 2024, Enschede, The Netherlands
                         ∗
                             Corresponding author.
                         Envelope-Open jisooseo@buffalo.edu (J. Seo); addiehl@buffalo.edu (A. D. Diehl); drathbu2@hfhs.or (D. L. Rathbun);
                         gopikrishnan.mc@gmail.com (G. M. Chandrasekharan); philosophy@calliemcgrath.space (C. McGrath);
                         wdduncan@gmail.com (W. D. Duncan)
                         Orcid 0009-0008-8150-9779 (J. Seo); 0000-0001-9990-8331 (A. D. Diehl); 0000-0001-7387-7944 (D. L. Rathbun);
                         0009-0006-7251-3026 (G. M. Chandrasekharan); 0009-0005-6233-0827 (C. McGrath); 0000-0001-9625-1899 (W. D. Duncan)
                                     © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).


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