Decoding Neural Signals: Invasive BMI Review

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Firuzi, Rezwan, Bokani, Ayub, Hassan, Jahan, Ahmadyani, Hamed, Abdi, Mohammad Foad, Naderi, Dana, Ebrahimi, Diako
Natura: Preprint
Pubblicazione: 2022
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866908429569753088
author Firuzi, Rezwan
Bokani, Ayub
Hassan, Jahan
Ahmadyani, Hamed
Abdi, Mohammad Foad
Naderi, Dana
Ebrahimi, Diako
author_facet Firuzi, Rezwan
Bokani, Ayub
Hassan, Jahan
Ahmadyani, Hamed
Abdi, Mohammad Foad
Naderi, Dana
Ebrahimi, Diako
contents Human civilization has witnessed transformative technological milestones, from ancient fire lighting to the internet era. This chapter delves into the invasive brain machine interface (BMI), a pioneering technology poised to be a defining chapter in our progress. Beyond aiding medical conditions, invasive BMI promises far reaching impacts across diverse technologies and aspects of life. The exploration begins by unraveling the biological and engineering principles essential for BMI implementation. The chapter comprehensively analyzes potential applications, methodologies for detecting and decoding brain signals, and options for stimulating signals within the human brain. It concludes with a discussion on the multifaceted challenges and opportunities for the continued development of invasive BMI. This chapter not only provides a profound understanding of the foundational elements of invasive BMI but also serves as a guide through its applications, intricacies, and potential societal implications. Navigating neurobiology, engineering innovations, and the evolving landscape of human AI symbiosis, the chapter sheds light on the promises and hurdles that define the future of invasive BMI.
format Preprint
id arxiv_https___arxiv_org_abs_2211_03324
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Decoding Neural Signals: Invasive BMI Review
Firuzi, Rezwan
Bokani, Ayub
Hassan, Jahan
Ahmadyani, Hamed
Abdi, Mohammad Foad
Naderi, Dana
Ebrahimi, Diako
Human-Computer Interaction
Human civilization has witnessed transformative technological milestones, from ancient fire lighting to the internet era. This chapter delves into the invasive brain machine interface (BMI), a pioneering technology poised to be a defining chapter in our progress. Beyond aiding medical conditions, invasive BMI promises far reaching impacts across diverse technologies and aspects of life. The exploration begins by unraveling the biological and engineering principles essential for BMI implementation. The chapter comprehensively analyzes potential applications, methodologies for detecting and decoding brain signals, and options for stimulating signals within the human brain. It concludes with a discussion on the multifaceted challenges and opportunities for the continued development of invasive BMI. This chapter not only provides a profound understanding of the foundational elements of invasive BMI but also serves as a guide through its applications, intricacies, and potential societal implications. Navigating neurobiology, engineering innovations, and the evolving landscape of human AI symbiosis, the chapter sheds light on the promises and hurdles that define the future of invasive BMI.
title Decoding Neural Signals: Invasive BMI Review
topic Human-Computer Interaction
url https://arxiv.org/abs/2211.03324