A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface

Measurement of neural signal provides important value for study of brain function and the pathogenesis of neurological. With emerging extensive research of electrical activity, more and more neural signal need to be collected, transmitted and stored, making the compression processing of neural signal become important part of digital signal processing. In recent years, ASIC-based wireless neural signal acquisition system has been developed rapidly, encountered strict restrictions on power consumption which is dominant determined by the data rate and complexity of algorithm. In order to reduce power consumption, lower data rate and algorithm with lower complexity needed to be selected when design a neural acquisition system. This paper focus on neural signal compression method based on compressed sensing and its performance and compare it with conventional compression algorithm. We compare complexity of various algorithms in the view of circuit complement, show that the complexity of neural signal compression can be dramatically reduced by using specially designed compressed sensing matrix, thereby reducing the system power consumption.

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Development of single channel EEG Acquisition system for BCI applications

Research Journal of Pharmacy and Technology ◽

10.52711/0974-360x.2021.00818 ◽

2021 ◽

pp. 4705-4709

Author(s):

V.G. Rajendran ◽

Jayalalitha S. ◽

Adalarasu K. ◽

Nirmalraj T.

Keyword(s):

Integrated Circuits ◽

Bandpass Filter ◽

Single Channel ◽

Acquisition System ◽

Computer Interface ◽

Brain Machine Interface ◽

Instrumentation Amplifier ◽

Signal Acquisition ◽

Level Shifter ◽

Machine Interface

Brain-Computer Interface (BCI) plays a major role in current technologies such as rehabilitation, control of devices, and various medical applications. BCI or brain-machine interface provides direct communication between a brain signal and an external device. In this paperwork, a detailed survey was carried out with the design of single-channel EEG system for various applications. Also, this paper mainly focused on the development of single-channel electroencephalography (EEG) signal acquisition system which includes a preamplifier, bandpass filter, post-amplifier and level shifter circuits. The design of the preamplifier and post-amplifier circuit was carried out by integrated circuits (IC) such as instrumentation amplifier IN128P and bandpass filter with the help of low power operational amplifier LM324. The developed single-channel acquisition board was tested by acquiring an electrooculogram (EOG) signal with closed and opened eye conditions. The acquired signal is displayed and stored in the computer with the help of the HBM-DAQ unit.

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A New data coding method for wireless command transmission BPSK modulator in implantable neural signal acquisition system

2008 IEEE International Conference on Electron Devices and Solid-State Circuits ◽

10.1109/edssc.2008.4760682 ◽

2008 ◽

Author(s):

Z. M. Lianga ◽

B. Lia ◽

Z. H. Wua

Keyword(s):

Acquisition System ◽

Signal Acquisition ◽

Neural Signal ◽

Data Coding ◽

Coding Method

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A reconfigurable general behavior data acquisition system for motor brain machine interface

2015 7th International IEEE/EMBS Conference on Neural Engineering (NER) ◽

10.1109/ner.2015.7146578 ◽

2015 ◽

Cited By ~ 1

Author(s):

Lichao Wang ◽

Guanghao Sun ◽

Zhaozhong Gui ◽

Yiwen Wang ◽

Shaomin Zhang ◽

...

Keyword(s):

Data Acquisition ◽

Data Acquisition System ◽

Acquisition System ◽

Brain Machine Interface ◽

General Behavior ◽

Machine Interface

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In vivoPerformance Evaluation of Implantable Wireless Neural Signal Transmission System for Brain Machine Interface

Experimental Neurobiology ◽

10.5607/en.2009.18.2.137 ◽

2009 ◽

Vol 18 (2) ◽

pp. 137

Author(s):

Hyun Joo Lee ◽

Selenge Nyamdorj ◽

Hyung-Cheul Shin ◽

Jae Mok Ahn

Keyword(s):

Signal Transmission ◽

Transmission System ◽

Brain Machine Interface ◽

Neural Signal ◽

Machine Interface

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Clinical Diagnosis of Psychiatry Based on Electroencephalography

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2021.3338 ◽

2021 ◽

Vol 11 (3) ◽

pp. 955-963

Author(s):

Lixue Yuan ◽

Yinyan Fan ◽

Quanxi Gan ◽

Huibin Feng

Keyword(s):

Environmental Control ◽

Low Cost ◽

Training System ◽

Brain Machine Interface ◽

Signal Acquisition ◽

Eeg Signal ◽

Eeg Signals ◽

Feedback Information ◽

Machine Interface ◽

Neural Feedback

At present, neurophysiological signals used for neuro feedback are EEG (Electroencephalogram), functional magnetic resonance imaging. Among them, the acquisition of EEG signals has the advantages of non-invasive way with low cost. It has been widely used in brain-machine interface technology in recent years. Important progress has been made in rehabilitation and environmental control. However, neural feedback and brainmachine interface technology are completely similar in signal acquisition, signal feature extraction, and pattern classification. Therefore, the related research results of brain-machine interface can be used to closely cooperate with clinical needs to research and develop neural feedback technology based on EEG. Based on neurophysiology and brain-machine interface technology, this paper develops a neural feedback training system based on the acquisition and analysis of human EEG signals. Aiming at the autonomous rhythm components in the EEG signal, such as sensorimotor rhythm and alpha rhythm, the characteristic parameters are extracted through real-time EEG signal processing to generate feedback information, and the subject is self-regulated and trained from a physiological-psychological perspective by providing adjuvant treatment, a practical and stable treatment platform for the clinic.

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