Brain signal acquisition methods in BCIs to estimate human motion intention-A survey

D. S.V. Bandara; Kazuo Kiguchi

doi:10.1109/MHS.2018.8887072

Brain signal acquisition methods in BCIs to estimate human motion intention-A survey

D. S.V. Bandara, Kazuo Kiguchi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Brain Computer Interfaces (BCIs) play an important role in current technological era to replace the disrupted neuromuscular pathways of humans caused by disorders or amputation. Especially, in restoring the motor functions of disabled or amputated body parts using wearable robotic devices, BCIs contribute to estimate the user's motion in terms of next motion onset, intended motion, and its velocity to control them. Brain signal acquisition is one of the important steps of a BCI. Over the time, both invasive and non-invasive techniques for signal acquisition are in use. This paper reviews available brain signal acquisition techniques in terms of mutual drawbacks and benefits, current status, challenges, future developments, etc.

Original language	English
Title of host publication	MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538667927
DOIs	https://doi.org/10.1109/MHS.2018.8887072
Publication status	Published - Dec 2018
Event	29th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2018 - Nagoya, Japan Duration: Dec 10 2018 → Dec 12 2018

Publication series

Name	MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science

Conference

Conference	29th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2018
Country/Territory	Japan
City	Nagoya
Period	12/10/18 → 12/12/18

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Electrical and Electronic Engineering
Mechanical Engineering
Control and Optimization
Instrumentation
Human-Computer Interaction

Access to Document

10.1109/MHS.2018.8887072

Cite this

Bandara, D. S. V., & Kiguchi, K. (2018). Brain signal acquisition methods in BCIs to estimate human motion intention-A survey. In MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science Article 8887072 (MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MHS.2018.8887072

Brain signal acquisition methods in BCIs to estimate human motion intention-A survey. / Bandara, D. S.V.; Kiguchi, Kazuo.
MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science. Institute of Electrical and Electronics Engineers Inc., 2018. 8887072 (MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Bandara, DSV & Kiguchi, K 2018, Brain signal acquisition methods in BCIs to estimate human motion intention-A survey. in MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science., 8887072, MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science, Institute of Electrical and Electronics Engineers Inc., 29th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2018, Nagoya, Japan, 12/10/18. https://doi.org/10.1109/MHS.2018.8887072

Bandara DSV , Kiguchi K. Brain signal acquisition methods in BCIs to estimate human motion intention-A survey. In MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science. Institute of Electrical and Electronics Engineers Inc. 2018. 8887072. (MHS 2018 - 2018 29th International Symposium on Micro-NanoMechatronics and Human Science). doi: 10.1109/MHS.2018.8887072

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Brain signal acquisition methods in BCIs to estimate human motion intention-A survey

Abstract

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Conference

All Science Journal Classification (ASJC) codes

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