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Kim M, Yoo S, Kim C. Miniaturization for wearable EEG systems: recording hardware and data processing. Biomed Eng Lett 2022; 12:239-250. [PMID: 35692891 PMCID: PMC9168644 DOI: 10.1007/s13534-022-00232-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/06/2022] [Accepted: 05/12/2022] [Indexed: 12/05/2022] Open
Abstract
As more people desire at-home diagnosis and treatment for their health improvement, healthcare devices have become more wearable, comfortable, and easy to use. In that sense, the miniaturization of electroencephalography (EEG) systems is a major challenge for developing daily-life healthcare devices. Recently, because of the intertwined relationship between EEG recording and processing, co-research of EEG recording hardware and data processing has been emphasized for whole-in-one miniaturized EEG systems. This paper introduces miniaturization techniques in analog-front-end hardware and processing algorithms for such EEG systems. To miniaturize EEG recording hardware, various types of compact electrodes and mm-sized integrated circuits (IC) techniques including artifact rejection are studied to record accurate EEG signals in a much smaller manner. Active electrode and in-ear EEG technologies are also researched to make small-form-factor EEG measurement structures. Furthermore, miniaturization techniques for EEG processing are discussed including channel selection techniques that reduce the number of required electrode channel and hardware implementation of processing algorithms that simplify the EEG processing stage.
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Affiliation(s)
- Minjae Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Daejeon, 34141 Republic of Korea
| | - Seungjae Yoo
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Daejeon, 34141 Republic of Korea
| | - Chul Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Daejeon, 34141 Republic of Korea
- KAIST Institute for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daehak-ro, Daejeon, 34141 Republic of Korea
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Lee HS, Eom K, Park M, Ku SB, Lee K, Lee HM. High-density neural recording system design. Biomed Eng Lett 2022; 12:251-261. [DOI: 10.1007/s13534-022-00233-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/10/2022] [Accepted: 05/20/2022] [Indexed: 10/18/2022] Open
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Sawigun C, Thanapitak S. A Compact Sub-μW CMOS ECG Amplifier With 57.5-MΩ Z in, 2.02 NEF, 8.16 PEF and 83.24-dB CMRR. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2021; 15:549-558. [PMID: 34081584 DOI: 10.1109/tbcas.2021.3086182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This paper presents a compact DDA-based fully-differential CMOS instrumentation amplifier dedicated for micro-power ECG monitoring. Only eight transistors are employed to realize a power-efficient current-sharing DDA. A RC network (using MOS pseudo resistors and poly capacitors) forms feedback loops around the DDA creating an ac-only amplification. The proposed amplifier is dc-coupled via gate terminals of the p-channel input transistors. It thus achieves sufficiently high input impedance over the entire ECG frequency range. Fabricated in a 0.35-μm CMOS process, the proposed amplifier occupies 0.0712 mm2. It operates from a 2 V dc supply with 336 nA current consumption. Measurements show that the amplifier attains its input impedance of 57.5 MΩ at 150 Hz and achieves 1.54 μVrms input-referred noise over 0.1-300 Hz. Noise and power efficiency factors are 2.02 and 8.16, respectively. At 50 Hz, the mean CMRR of 83.24 dB is obtained from 11-chip measurement. Experiments performed on a human subject confirm the functionality of the proposed amplifier in a real measurement scenario.
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Jia Y, Guler U, Lai YP, Gong Y, Weber A, Li W, Ghovanloo M. A Trimodal Wireless Implantable Neural Interface System-on-Chip. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2020; 14:1207-1217. [PMID: 33180731 PMCID: PMC7814662 DOI: 10.1109/tbcas.2020.3037452] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
A wireless and battery-less trimodal neural interface system-on-chip (SoC), capable of 16-ch neural recording, 8-ch electrical stimulation, and 16-ch optical stimulation, all integrated on a 5 × 3 mm2 chip fabricated in 0.35-μm standard CMOS process. The trimodal SoC is designed to be inductively powered and communicated. The downlink data telemetry utilizes on-off keying pulse-position modulation (OOK-PPM) of the power carrier to deliver configuration and control commands at 50 kbps. The analog front-end (AFE) provides adjustable mid-band gain of 55-70 dB, low/high cut-off frequencies of 1-100 Hz/10 kHz, and input-referred noise of 3.46 μVrms within 1 Hz-50 kHz band. AFE outputs of every two-channel are digitized by a 50 kS/s 10-bit SAR-ADC, and multiplexed together to form a 6.78 Mbps data stream to be sent out by OOK modulating a 434 MHz RF carrier through a power amplifier (PA) and 6 cm monopole antenna, which form the uplink data telemetry. Optical stimulation has a switched-capacitor based stimulation (SCS) architecture, which can sequentially charge four storage capacitor banks up to 4 V and discharge them in selected μLEDs at instantaneous current levels of up to 24.8 mA on demand. Electrical stimulation is supported by four independently driven stimulating sites at 5-bit controllable current levels in ±(25-775) μA range, while active/passive charge balancing circuits ensure safety. In vivo testing was conducted on four anesthetized rats to verify the functionality of the trimodal SoC.
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Jia Y, Lee B, Kong F, Zeng Z, Connolly M, Mahmoudi B, Ghovanloo M. A Software-Defined Radio Receiver for Wireless Recording From Freely Behaving Animals. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:1645-1654. [PMID: 31647447 PMCID: PMC6990704 DOI: 10.1109/tbcas.2019.2949233] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
To eliminate tethering effects on the small animals' behavior during electrophysiology experiments, such as neural interfacing, a robust and wideband wireless data link is needed for communicating with the implanted sensing elements without blind spots. We present a software-defined radio (SDR) based scalable data acquisition system, which can be programmed to provide coverage over standard-sized or customized experimental arenas. The incoming RF signal with the highest power among SDRs is selected in real-time to prevent data loss in the presence of spatial and angular misalignments between the transmitter (Tx) and receiver (Rx) antennas. A 32-channel wireless neural recording system-on-a-chip (SoC), known as WINeRS-8, is embedded in a headstage and transmits digitalized raw neural signals, which are sampled at 25 kHz/ch, at 9 Mbps via on-off keying (OOK) of a 434 MHz RF carrier. Measurement results show that the dual-SDR Rx system reduces the packet loss down to 0.12%, on average, by eliminating the blind spots caused by the moving Tx directionality. The system operation is verified in vivo on a freely behaving rat and compared with a commercial hardwired system.
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Sharma M, Strathman HJ, Walker RM. Verification of a Rapidly Multiplexed Circuit for Scalable Action Potential Recording. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:1655-1663. [PMID: 31825873 PMCID: PMC7454001 DOI: 10.1109/tbcas.2019.2958348] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
This report presents characterizations of in vivo neural recordings performed with a CMOS multichannel neural recording chip that uses rapid multiplexing directly at the electrodes, without any pre-amplification or buffering. Neural recordings were taken from a 16-channel microwire array implanted in rodent cortex, with comparison to a gold-standard commercial bench-top recording system. We were able to record well-isolated threshold crossings from 10 multiplexed electrodes and typical local field potential waveforms from 16, with strong agreement with the standard system (average SNR = 2.59 and 3.07 respectively). For 10 electrodes, the circuit achieves an effective area per channel of 0.0077 mm2, which is >5x smaller than typical multichannel chips. Extensive characterizations of noise and signal quality are presented and compared to fundamental theory, as well as results from in vivo and in vitro experiments. By demonstrating the validation of rapid multiplexing directly at the electrodes, this report confirms it as a promising approach for reducing circuit area in massively-multichannel neural recording systems, which is crucial for scaling recording site density and achieving large-scale sensing of brain activity with high spatiotemporal resolution.
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Zhao Y, Shang Z, Lian Y. A 2.55 NEF 76 dB CMRR DC-Coupled Fully Differential Difference Amplifier Based Analog Front End for Wearable Biomedical Sensors. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:918-926. [PMID: 31247560 DOI: 10.1109/tbcas.2019.2924416] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
High input impedance, low noise, high common mode rejection ratio (CMRR), and ultralow power are the most important performance indicators in the design of analog front end (AFE) for wearable biomedical sensors. This paper presents a fully differential difference amplifier based AFE that employs dc-coupled input stage to increase the input impedance and improve CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body dc bias scheme is introduced to deal with the input dc offset. Implemented in 0.35 μm CMOS process with an area of 0.405 mm2, the proposed AFE consumes 0.9 μW at 1.8 V and shows excellent noise effective factor of 2.55, and CMRR of 76 dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2 cm under both resting and walking conditions, but also obtain the distinct α-wave after eye blink from EEG recording.
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Lee B, Jia Y, Mirbozorgi SA, Connolly M, Tong X, Zeng Z, Mahmoudi B, Ghovanloo M. An Inductively-Powered Wireless Neural Recording and Stimulation System for Freely-Behaving Animals. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:413-424. [PMID: 30624226 PMCID: PMC6510586 DOI: 10.1109/tbcas.2019.2891303] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
An inductively-powered wireless integrated neural recording and stimulation (WINeRS-8) system-on-a-chip (SoC) that is compatible with the EnerCage-HC2 for wireless/battery-less operation has been presented for neuroscience experiments on freely behaving animals. WINeRS-8 includes a 32-ch recording analog front end, a 4-ch current-controlled stimulator, and a 434 MHz on - off keying data link to an external software- defined radio wideband receiver (Rx). The headstage also has a bluetooth low energy link for controlling the SoC. WINeRS-8/EnerCage-HC2 systems form a bidirectional wireless and battery-less neural interface within a standard homecage, which can support longitudinal experiments in an enriched environment. Both systems were verified in vivo on rat animal model, and the recorded signals were compared with hardwired and battery-powered recording results. Realtime stimulation and recording verified the system's potential for bidirectional neural interfacing within the homecage, while continuously delivering 35 mW to the hybrid WINeRS-8 headstage over an unlimited period.
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Affiliation(s)
- Byunghun Lee
- School of Electrical Engineering, Incheon National University, South Korea ()
| | - Yaoyao Jia
- GT- Bionics lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30308, USA ()
| | - S. Abdollah Mirbozorgi
- GT- Bionics lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30308, USA ()
| | - Mark Connolly
- Department of Physiology, Emory University, Atlanta, GA 30329, USA
| | - Xingyuan Tong
- School of Electronics Engineering, Xi’an University of Posts and Telecommunications, Xi’an, 710121, China
| | | | - Babak Mahmoudi
- Department of Physiology, Emory University, Atlanta, GA 30329, USA
| | - Maysam Ghovanloo
- GT- Bionics lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30308, USA ()
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Lee B, Koripalli MK, Jia Y, Acosta J, Sendi MSE, Choi Y, Ghovanloo M. An Implantable Peripheral Nerve Recording and Stimulation System for Experiments on Freely Moving Animal Subjects. Sci Rep 2018; 8:6115. [PMID: 29666407 PMCID: PMC5904113 DOI: 10.1038/s41598-018-24465-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 03/26/2018] [Indexed: 01/24/2023] Open
Abstract
A new study with rat sciatic nerve model for peripheral nerve interfacing is presented using a fully-implanted inductively-powered recording and stimulation system in a wirelessly-powered standard homecage that allows animal subjects move freely within the homecage. The Wireless Implantable Neural Recording and Stimulation (WINeRS) system offers 32-channel peripheral nerve recording and 4-channel current-controlled stimulation capabilities in a 3 × 1.5 × 0.5 cm3 package. A bi-directional data link is established by on-off keying pulse-position modulation (OOK-PPM) in near field for narrow-band downlink and 433 MHz OOK for wideband uplink. An external wideband receiver is designed by adopting a commercial software defined radio (SDR) for a robust wideband data acquisition on a PC. The WINeRS-8 prototypes in two forms of battery-powered headstage and wirelessly-powered implant are validated in vivo, and compared with a commercial system. In the animal study, evoked compound action potentials were recorded to verify the stimulation and recording capabilities of the WINeRS-8 system with 32-ch penetrating and 4-ch cuff electrodes on the sciatic nerve of awake freely-behaving rats. Compared to the conventional battery-powered system, WINeRS can be used in closed-loop recording and stimulation experiments over extended periods without adding the burden of carrying batteries on the animal subject or interrupting the experiment.
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Affiliation(s)
- Byunghun Lee
- Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, 30308, USA.,Incheon National University, Department of Electrical Engineering, Incheon, 22012, South Korea
| | - Mukhesh K Koripalli
- University of Texas, Rio Grande Valley, Department of Electrical Engineering, Edinburg, 78539, USA
| | - Yaoyao Jia
- Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, 30308, USA
| | - Joshua Acosta
- University of Texas, Rio Grande Valley, Department of Electrical Engineering, Edinburg, 78539, USA
| | - M S E Sendi
- Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, 30308, USA
| | - Yoonsu Choi
- University of Texas, Rio Grande Valley, Department of Electrical Engineering, Edinburg, 78539, USA
| | - Maysam Ghovanloo
- Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, 30308, USA.
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