scholarly journals Neurochip3: An Autonomous Multichannel Bidirectional Brain-Computer Interface for Closed-Loop Activity-Dependent Stimulation

2021 ◽  
Vol 15 ◽  
Author(s):  
Larry E. Shupe ◽  
Frank P. Miles ◽  
Geoff Jones ◽  
Richy Yun ◽  
Jonathan Mishler ◽  
...  
Keyword(s):  
Closed Loop ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Circuit Boards ◽  
Autonomous Operation ◽  
Analog Front End ◽  
Signal Amplifier ◽  
Main Components ◽  
Sd Card ◽  
Activity Dependent

Toward addressing many neuroprosthetic applications, the Neurochip3 (NC3) is a multichannel bidirectional brain-computer interface that operates autonomously and can support closed-loop activity-dependent stimulation. It consists of four circuit boards populated with off-the-shelf components and is sufficiently compact to be carried on the head of a non-human primate (NHP). NC3 has six main components: (1) an analog front-end with an Intan biophysical signal amplifier (16 differential or 32 single-ended channels) and a 3-axis accelerometer, (2) a digital control system comprised of a Cyclone V FPGA and Atmel SAM4 MCU, (3) a micro SD Card for 128 GB or more storage, (4) a 6-channel differential stimulator with ±60 V compliance, (5) a rechargeable battery pack supporting autonomous operation for up to 24 h and, (6) infrared transceiver and serial ports for communication. The NC3 and earlier versions have been successfully deployed in many closed-loop operations to induce synaptic plasticity and bridge lost biological connections, as well as deliver activity-dependent intracranial reinforcement. These paradigms to strengthen or replace impaired connections have many applications in neuroprosthetics and neurorehabilitation.

scholarly journals An Implantable Brain-Computer Interface for Investigation of Novel Closed-Loop Therapies

2018 ◽  
Vol 12 ◽  
Author(s):  
Martin Schüttler ◽  
Fabian Kohler ◽  
Christian Stolle ◽  
Jörg Fischer ◽  
Thomas Stieglitz ◽  
...  
Keyword(s):  
Closed Loop ◽  
Brain Computer Interface ◽  
Computer Interface

scholarly journals A closed-loop, music-based brain-computer interface for emotion mediation

PLoS ONE ◽  
2019 ◽  
Vol 14 (3) ◽  
pp. e0213516 ◽  
Author(s):  
Stefan K. Ehrlich ◽  
Kat R. Agres ◽  
Cuntai Guan ◽  
Gordon Cheng
Keyword(s):  
Closed Loop ◽  
Brain Computer Interface ◽  
Computer Interface

A Closed-Loop Brain–Computer Interface Triggering an Active Ankle–Foot Orthosis for Inducing Cortical Neural Plasticity

2014 ◽  
Vol 61 (7) ◽  
pp. 2092-2101 ◽  
Author(s):  
Ren Xu ◽  
Ning Jiang ◽  
Natalie Mrachacz-Kersting ◽  
Chuang Lin ◽  
Guillermo Asin Prieto ◽  
...  
Keyword(s):  
Neural Plasticity ◽  
Closed Loop ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Ankle Foot Orthosis ◽  
Foot Orthosis

scholarly journals Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot

2021 ◽  
Vol 15 ◽  
Author(s):  
Neethu Robinson ◽  
Tushar Chouhan ◽  
Ernest Mihelj ◽  
Paulina Kratka ◽  
Frédéric Debraine ◽  
...  
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Brain Computer Interface ◽  
Brain Activation ◽  
Classification Performance ◽  
Open Loop ◽  
Computer Interface ◽  
Single Subject ◽  
User Engagement

Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms (p = 0.0008). We also observe that stronger and more localized brain activation patterns are elicited in the closed-loop paradigm in which the experiment interface closely resembled the end application. Thus, based on this longitudinal evaluation of single-subject data, we demonstrate that BCI-based calibration paradigms with active user-engagement, such as with real-time feedback, could help in achieving better user acceptability and performance.

scholarly journals Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain–computer interface to a virtual reality avatar

2016 ◽  
Vol 13 (3) ◽  
pp. 036006 ◽  
Author(s):  
Trieu Phat Luu ◽  
Yongtian He ◽  
Samuel Brown ◽  
Sho Nakagome ◽  
Jose L Contreras-Vidal
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Closed Loop ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Gait Adaptation
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