A Modular Analog Front-End for the Recording of Neural Spikes and Local Field Potentials within a Neural Measurement System

被引:0
|
作者
Heidmann, Nils [1 ]
Hellwege, Nico [1 ]
Pistor, Jonas [1 ]
Peters-Drolshagen, Dagmar [1 ]
Paul, Steffen [1 ]
机构
[1] Univ Bremen, Inst Electrodynam & Microelect ITEM Me, D-28359 Bremen, Germany
关键词
Neural Measurement System; Action Potentials; Spikes; Brain Computer Interface; Low Power; Low Noise;
D O I
10.1016/j.proeng.2014.11.407
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
The measurement of neural signals is mandatory for an extensive and detailed understanding of the cortex. A parallel recording of multiple recording channels and varying neural signal types is required in order to cover a high density of neural information. Therefore, analog front-ends are required which record signals from the micro-mechanical electrodes and preprocesses these data for a transmission out of the brain. This paper presents an analog front-end for the recording of local field potentials and neural spikes. A modular approach is applied that enables the integration within a complete system or the operation as a single component. The use of configurable recording channels provides the capability to adjust the channels, dependent on the signal type of interest. The proposed front-end has been fabricated in a 0.35 mu m-CMOS process, and performance values are demonstrated by measurements. (C) 2014 Published by Elsevier Ltd.
引用
收藏
页码:1239 / 1242
页数:4
相关论文
共 50 条
  • [41] A Low-power Current-Reuse Dual-Band Analog Front-End for Multi-Channel Neural Signal Recording
    Sepehrian, H.
    Gosselin, B.
    2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2014, : 5284 - 5287
  • [42] An ultrahigh input impedance low noise analog front-end design for epilepsy brain recording system
    Anh, Nguyen Thi Ngoc
    Tien, Nguyen The
    Tuan, Nguyen Van
    Tuan, Dao Duy
    Thanh, Vu Van
    Thai, Pham Quang
    Au, Huynh Hai
    Tho, Nguyen Van
    INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 2024, 52 (11) : 5469 - 5482
  • [43] A CMOS Micro-power and Area Efficient Neural Recording and Stimulation Front-End for Biomedical Applications
    Sami Ur Rehman
    Awais Mehmood Kamboh
    Circuits, Systems, and Signal Processing, 2015, 34 : 1725 - 1746
  • [44] A fully-integrated 16-channel EEG readout front-end for neural recording applications
    Nasserian, Mahshid
    Peiravi, Ali
    Moradi, Farshad
    AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 2018, 94 : 109 - 121
  • [45] A LOW-NOISE LOW-POWER FRONT-END AMPLIFIER FOR NEURAL-RECORDING APPLICATIONS
    Zarifi, Mohammad Hossein
    Frounchi, Javad
    Tinati, Mohammad A.
    Farshchi, Shahin
    Judy, Jack W.
    BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2010, 22 (04): : 301 - 306
  • [46] A CMOS Micro-power and Area Efficient Neural Recording and Stimulation Front-End for Biomedical Applications
    Rehman, Sami Ur
    Kamboh, Awais Mehmood
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2015, 34 (06) : 1725 - 1746
  • [47] A bidirectional neural interface CMOS analog front-end IC with embedded isolation switch for implantable devices
    Abdi, Alfian
    Cha, Hyouk-Kyu
    MICROELECTRONICS JOURNAL, 2016, 58 : 70 - 75
  • [48] Toward 1024-Channel Parallel Neural Recording: Modular Δ-ΔΣ Analog Front-End Architecture with 4.84fJ/C-s.mm2 Energy-Area Product
    Park, Sung-Yun
    Cho, Jihyun
    Na, Kyounghwan
    Yoon, Euisik
    2015 SYMPOSIUM ON VLSI CIRCUITS (VLSI CIRCUITS), 2015,
  • [49] Prediction of the Timing and the Rhythm of the Parkinsonian Subthalamic Nucleus Neural Spikes Using the Local Field Potentials
    Michmizos, Kostis P.
    Sakas, Damianos
    Nikita, Konstantina S.
    IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 2012, 16 (02): : 190 - 197
  • [50] A TDM-Based Multi-Channel Analog Front-end for Wearable Dry EEG Recording System
    Tang, Tao
    Goh, Wang Ling
    Yao, Lei
    Gao, Yuan
    2017 IEEE 15TH INTERNATIONAL NEW CIRCUITS AND SYSTEMS CONFERENCE (NEWCAS), 2017, : 297 - 300