تقرير
Decoding Neural Signals with Computational Models: A Systematic Review of Invasive BMI
| العنوان: | Decoding Neural Signals with Computational Models: A Systematic Review of Invasive BMI |
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| المؤلفون: | Firuzi, Rezwan, Ahmadyani, Hamed, Abdi, Mohammad Foad, Naderi, Dana, Hassan, Jahan, Bokani, Ayub |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Human-Computer Interaction |
| الوصف: | There are significant milestones in modern human's civilization in which mankind stepped into a different level of life with a new spectrum of possibilities and comfort. From fire-lighting technology and wheeled wagons to writing, electricity and the Internet, each one changed our lives dramatically. In this paper, we take a deep look into the invasive Brain Machine Interface (BMI), an ambitious and cutting-edge technology which has the potential to be another important milestone in human civilization. Not only beneficial for patients with severe medical conditions, the invasive BMI technology can significantly impact different technologies and almost every aspect of human's life. We review the biological and engineering concepts that underpin the implementation of BMI applications. There are various essential techniques that are necessary for making invasive BMI applications a reality. We review these through providing an analysis of (i) possible applications of invasive BMI technology, (ii) the methods and devices for detecting and decoding brain signals, as well as (iii) possible options for stimulating signals into human's brain. Finally, we discuss the challenges and opportunities of invasive BMI for further development in the area. Comment: We have made significant changes to this article |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2211.03324 |
| رقم الأكسشن: | edsarx.2211.03324 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |