1
|
Valente V. Evolution of Biotelemetry in Medical Devices: From Radio Pills to mm-Scale Implants. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2022; 16:580-599. [PMID: 35834463 DOI: 10.1109/tbcas.2022.3190767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The advent of semiconductor technology in the mid-20th century created unprecedented opportunities to develop a new generation of small-scale wireless medical sensing devices that can support remote monitoring of patients' vital signs. The first radio pills were developed as early as the 1950's using only a few transistors. These swallowable capsules could sense and wirelessly transmit vital parameters from inside the human body. Since then we have witnessed the rapid progress of medical devices driven by the evolution of semiconductor technology, from single-transistor oscillators to complex mixed-signal multi-channel and multi-modal systems. This paper retraces the evolution of biotelemetry devices from their very early inception to the smart miniaturized systems of modern days, focusing on semiconductor-enabled sensing methods and circuits developed over the last six decades. The paper also includes the author's perspective on current and future trends in the development of CMOS-based biotelemeters, focusing on concepts of implant modularity, miniaturization and hybrid energy harvesting solutions.
Collapse
|
2
|
Tabrizi HO, Farhanieh O, Owen Q, Magierowski S, Ghafar-Zadeh E. Wide Input Dynamic Range Fully Integrated Capacitive Sensor for Life Science Applications. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2021; 15:339-350. [PMID: 33891555 DOI: 10.1109/tbcas.2021.3075348] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This paper presents a new fully integrated CMOS capacitance sensor chip with a wider input dynamic range (IDR) compared to the state-of-the-art, suitable for a variety of life science applications. With the novel differential capacitance to current conversion topology, it achieves an IDR of about seven times higher compared to the previous charge based capacitive measurement (CBCM) circuits and about three times higher compared to the CBCM with cascode current mirrors. It also features a calibration circuitry consisting of an array of switched capacitors, interdigitated electrodes (IDEs) realized on the topmost metal layer, a current-controlled 300 MHz oscillator, and a counter-serializer to create digital output. The proposed sensor, fabricated in AMS 0.35 μm CMOS technology, enables a high-resolution measurement, equal to 416 aF, of physiochemical changes in the IDE with up to 1.27 pF input offset adjustment range (IOAR). With a measurement speed of 15 μs, this sensor is among the fast CMOS capacitive sensors in the literature. In this paper, we demonstrate its functionality and applicability and present the experimental results for monitoring 2 μL evaporating droplets of chemical solvents. By using samples of solvents with different conductivity and relative permittivity, a wide range of capacitance and resistance variations in the sample-IDE interface electric equivalent model can be created. In addition, the evaporating droplet test has inherently fast dynamic changes. Based on the results, our proposed device addresses the challenge of detecting small capacitance changes despite large parasitic elements caused by the ions in the solution or by remnants deposited on the electrode.
Collapse
|
3
|
Purcell EK, Becker MF, Guo Y, Hara SA, Ludwig KA, McKinney CJ, Monroe EM, Rechenberg R, Rusinek CA, Saxena A, Siegenthaler JR, Sortwell CE, Thompson CH, Trevathan JK, Witt S, Li W. Next-Generation Diamond Electrodes for Neurochemical Sensing: Challenges and Opportunities. MICROMACHINES 2021; 12:128. [PMID: 33530395 PMCID: PMC7911340 DOI: 10.3390/mi12020128] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/19/2021] [Accepted: 01/19/2021] [Indexed: 12/12/2022]
Abstract
Carbon-based electrodes combined with fast-scan cyclic voltammetry (FSCV) enable neurochemical sensing with high spatiotemporal resolution and sensitivity. While their attractive electrochemical and conductive properties have established a long history of use in the detection of neurotransmitters both in vitro and in vivo, carbon fiber microelectrodes (CFMEs) also have limitations in their fabrication, flexibility, and chronic stability. Diamond is a form of carbon with a more rigid bonding structure (sp3-hybridized) which can become conductive when boron-doped. Boron-doped diamond (BDD) is characterized by an extremely wide potential window, low background current, and good biocompatibility. Additionally, methods for processing and patterning diamond allow for high-throughput batch fabrication and customization of electrode arrays with unique architectures. While tradeoffs in sensitivity can undermine the advantages of BDD as a neurochemical sensor, there are numerous untapped opportunities to further improve performance, including anodic pretreatment, or optimization of the FSCV waveform, instrumentation, sp2/sp3 character, doping, surface characteristics, and signal processing. Here, we review the state-of-the-art in diamond electrodes for neurochemical sensing and discuss potential opportunities for future advancements of the technology. We highlight our team's progress with the development of an all-diamond fiber ultramicroelectrode as a novel approach to advance the performance and applications of diamond-based neurochemical sensors.
Collapse
Affiliation(s)
- Erin K. Purcell
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA; (Y.G.); (A.S.); (W.L.)
- Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA;
- Neuroscience Program, Michigan State University, East Lansing, MI 48824, USA;
- Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Michael F. Becker
- Fraunhofer USA Center Midwest, East Lansing, MI 48824, USA; (M.F.B.); (R.R.); (J.R.S.); (S.W.)
| | - Yue Guo
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA; (Y.G.); (A.S.); (W.L.)
| | - Seth A. Hara
- Division of Engineering, Mayo Clinic, Rochester, MN 55905, USA;
| | - Kip A. Ludwig
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA; (K.A.L.); (J.K.T.)
- Department of Neurosurgery, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Collin J. McKinney
- Department of Chemistry, Electronics Core Facility, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA;
| | - Elizabeth M. Monroe
- Department of Chemistry and Biochemistry, University of Nevada, Las Vegas, NV 89154, USA; (E.M.M.); (C.A.R.)
| | - Robert Rechenberg
- Fraunhofer USA Center Midwest, East Lansing, MI 48824, USA; (M.F.B.); (R.R.); (J.R.S.); (S.W.)
| | - Cory A. Rusinek
- Department of Chemistry and Biochemistry, University of Nevada, Las Vegas, NV 89154, USA; (E.M.M.); (C.A.R.)
| | - Akash Saxena
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA; (Y.G.); (A.S.); (W.L.)
- Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - James R. Siegenthaler
- Fraunhofer USA Center Midwest, East Lansing, MI 48824, USA; (M.F.B.); (R.R.); (J.R.S.); (S.W.)
| | - Caryl E. Sortwell
- Neuroscience Program, Michigan State University, East Lansing, MI 48824, USA;
- Department of Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
| | - Cort H. Thompson
- Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA;
- Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - James K. Trevathan
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA; (K.A.L.); (J.K.T.)
- Grainger Institute for Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Suzanne Witt
- Fraunhofer USA Center Midwest, East Lansing, MI 48824, USA; (M.F.B.); (R.R.); (J.R.S.); (S.W.)
| | - Wen Li
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA; (Y.G.); (A.S.); (W.L.)
- Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA;
- Neuroscience Program, Michigan State University, East Lansing, MI 48824, USA;
- Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| |
Collapse
|
4
|
Chen J, Cheng P, Sun Y, Wang Y, Zhang X, Yang Z, Ding G. A Minimally Invasive Hollow Microneedle With a Cladding Structure: Ultra-Thin but Strong, Batch Manufacturable. IEEE Trans Biomed Eng 2019; 66:3480-3485. [DOI: 10.1109/tbme.2019.2906571] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
|
5
|
Morales MA, Halpern JM. Guide to Selecting a Biorecognition Element for Biosensors. Bioconjug Chem 2018; 29:3231-3239. [PMID: 30216055 DOI: 10.1021/acs.bioconjchem.8b00592] [Citation(s) in RCA: 184] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Biosensors are powerful diagnostic tools defined as having a biorecognition element for analyte specificity and a transducer for a quantifiable signal. There are a variety of different biorecognition elements, each with unique characteristics. Understanding the advantages and disadvantages of each biorecognition element and their influence on overall biosensor performance is crucial in the planning stages to promote the success of novel biosensor development. Therefore, this review will focus on selecting the optimal biorecognition element in the preliminary design phase for novel biosensors. Included is a review of the typical characteristics and binding mechanisms of various biorecognition elements, and how they relate to biosensor performance characteristics, specifically sensitivity, selectivity, reproducibility, and reusability. The goal is to point toward language needed to improve the design and development of biosensors toward clinical success.
Collapse
Affiliation(s)
- Marissa A Morales
- Department of Chemical Engineering , University of New Hampshire , Durham , New Hampshire 03824 , United States
| | - Jeffrey Mark Halpern
- Department of Chemical Engineering , University of New Hampshire , Durham , New Hampshire 03824 , United States
| |
Collapse
|
6
|
Bozorgzadeh B, Schuweiler DR, Bobak MJ, Garris PA, Mohseni P. Neurochemostat: A Neural Interface SoC With Integrated Chemometrics for Closed-Loop Regulation of Brain Dopamine. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2016; 10:654-67. [PMID: 26390501 PMCID: PMC4809062 DOI: 10.1109/tbcas.2015.2453791] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
This paper presents a 3.3×3.2 mm(2) system-on-chip (SoC) fabricated in AMS 0.35 μm 2P/4M CMOS for closed-loop regulation of brain dopamine. The SoC uniquely integrates neurochemical sensing, on-the-fly chemometrics, and feedback-controlled electrical stimulation to realize a "neurochemostat" by maintaining brain levels of electrically evoked dopamine between two user-set thresholds. The SoC incorporates a 90 μW, custom-designed, digital signal processing (DSP) unit for real-time processing of neurochemical data obtained by 400 V/s fast-scan cyclic voltammetry (FSCV) with a carbon-fiber microelectrode (CFM). Specifically, the DSP unit executes a chemometrics algorithm based upon principal component regression (PCR) to resolve in real time electrically evoked brain dopamine levels from pH change and CFM background-current drift, two common interferents encountered using FSCV with a CFM in vivo. Further, the DSP unit directly links the chemically resolved dopamine levels to the activation of the electrical microstimulator in on-off-keying (OOK) fashion. Measured results from benchtop testing, flow injection analysis (FIA), and biological experiments with an anesthetized rat are presented.
Collapse
|
7
|
Bahrami H, Mirbozorgi SA, Rusch LA, Gosselin B. Biological channel modeling and implantable UWB antenna design for neural recording systems. IEEE Trans Biomed Eng 2014; 62:88-98. [PMID: 25055379 DOI: 10.1109/tbme.2014.2339836] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Ultrawideband (UWB) short-range communication systems have proved to be valuable in medical technology, particularly for implanted devices, due to their low-power consumption, low cost, small size, and high data rates. Neural activity monitoring in the brain requires high data rate (800 kb/s per neural sensor), and we target a system supporting a large number of sensors, in particular, aggregate transmission above 430 Mb/s (∼512 sensors). Knowledge of channel behavior is required to determine the maximum allowable power to 1) respect ANSI guidelines for avoiding tissue damage, and 2) respect FCC guidelines on unlicensed transmissions. We utilize a realistic model of the biological channel to inform the design of antennas for the implanted transmitter and the external receiver under these requirements. Antennas placement is examined under two scenarios having contrasting power constraints. Performance of the system within the biological tissues is examined via simulation and experiment. Our miniaturized antennas, 12 mm ×12 mm, need worst-case receiver sensitivities of -38 and -30.5 dBm for the first and second scenarios, respectively. These sensitivities allow us to successfully detect signals transmitted through tissues in the 3.1-10.6-GHz UWB band.
Collapse
|
8
|
Shah RS, Chang SY, Min HK, Cho ZH, Blaha CD, Lee KH. Deep brain stimulation: technology at the cutting edge. J Clin Neurol 2010; 6:167-82. [PMID: 21264197 PMCID: PMC3024521 DOI: 10.3988/jcn.2010.6.4.167] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2010] [Revised: 09/16/2010] [Accepted: 09/16/2010] [Indexed: 01/15/2023] Open
Abstract
Deep brain stimulation (DBS) surgery has been performed in over 75,000 people worldwide, and has been shown to be an effective treatment for Parkinson's disease, tremor, dystonia, epilepsy, depression, Tourette's syndrome, and obsessive compulsive disorder. We review current and emerging evidence for the role of DBS in the management of a range of neurological and psychiatric conditions, and discuss the technical and practical aspects of performing DBS surgery. In the future, evolution of DBS technology may depend on several key areas, including better scientific understanding of its underlying mechanism of action, advances in high-spatial resolution imaging and development of novel electrophysiological and neurotransmitter microsensor systems. Such developments could form the basis of an intelligent closed-loop DBS system with feedback-guided neuromodulation to optimize both electrode placement and therapeutic efficacy.
Collapse
Affiliation(s)
- Rahul S Shah
- Department of Neurological Surgery, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | | |
Collapse
|
9
|
Gilja V, Chestek CA, Nuyujukian P, Foster J, Shenoy KV. Autonomous head-mounted electrophysiology systems for freely behaving primates. Curr Opin Neurobiol 2010; 20:676-86. [PMID: 20655733 PMCID: PMC3401169 DOI: 10.1016/j.conb.2010.06.007] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2010] [Revised: 06/16/2010] [Accepted: 06/28/2010] [Indexed: 11/18/2022]
Abstract
Recent technological advances have led to new light-weight battery-operated systems for electrophysiology. Such systems are head mounted, run for days without experimenter intervention, and can record and stimulate from single or multiple electrodes implanted in a freely behaving primate. Here we discuss existing systems, studies that use them, and how they can augment traditional, physically restrained, 'in-rig' electrophysiology. With existing technical capabilities, these systems can acquire multiple signal classes, such as spikes, local field potential, and electromyography signals, and can stimulate based on real-time processing of recorded signals. Moving forward, this class of technologies, along with advances in neural signal processing and behavioral monitoring, have the potential to dramatically expand the scope and scale of electrophysiological studies.
Collapse
Affiliation(s)
- Vikash Gilja
- Dept. of Computer Science, Stanford University, Stanford, CA 94305, USA
| | | | | | | | | |
Collapse
|
10
|
Roham M, Blaha CD, Garris PA, Lee KH, Mohseni P. A configurable IC for wireless real-time in vivo monitoring of chemical and electrical neural activity. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2009:4222-5. [PMID: 19963812 DOI: 10.1109/iembs.2009.5333089] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
A 16-channel chip for wireless in vivo recording of chemical and electrical neural activity is described. The 7.83-mm2 IC is fabricated using a 0.5-microm CMOS process and incorporates a 71-microW, 3rd-order, configurable, DeltaSigma modulator per channel, achieving an input-referred noise of 4.69 microVrms in 4-kHz BW and 94.1 pArms in 5-kHz BW for electrical and fastscan voltammetric chemical neurosensing, respectively. Brain extracellular levels of dopamine elicited by electrical stimulation of the medial forebrain bundle have been recorded wirelessly on multiple channels using 300-V/s fast-scan cyclic voltammetry in the anesthetized rat.
Collapse
Affiliation(s)
- Masoud Roham
- Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA
| | | | | | | | | |
Collapse
|
11
|
Ayers S, Berberian K, Gillis KD, Lindau M, Minch BA. Post-CMOS fabrication of Working Electrodes for On-Chip Recordings of Transmitter Release. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2010; 4:86-92. [PMID: 20514361 PMCID: PMC2877396 DOI: 10.1109/tbcas.2009.2033706] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The release of neurotransmitters and hormones from secretory vesicles plays a fundamental role in the function of the nervous system including neuronal communication. High-throughput testing of drugs modulating transmitter release is becoming an increasingly important area in the fields of cell biology, neurobiology, and neurology. Carbon-fiber amperometry, provides high-resolution measurements of amount and time course of transmitter release from single vesicles, and their modulation by drugs and molecular manipulations. However, such methods do not allow the rapid collection of data from a large number of cells. To allow such testing, we have developed a CMOS potentiostat circuit that can be scaled to a large array. In this paper, we present two post-CMOS fabrication methods to incorporate the electrochemical electrode material. We demonstrate by proof of principle the feasibility of on-chip electrochemical measurements of dopamine, and catecholamine release from adrenal chromaffin cells. The measurement noise is consistent with the typical electrode noise in recordings with external amplifiers. The electronic noise of the potentiostat in recordings with 400 mus integration time is ~0.11 pA and is negligible compared to the inherent electrode noise.
Collapse
Affiliation(s)
- Sunitha Ayers
- School of Electrical and Computer Engineering, Cornell University, Ithaca, NY
| | - Khajak Berberian
- Department of Biomedical Engineering, Cornell University, Ithaca, NY
| | - Kevin D. Gillis
- Department of Biological Engineering, University of Missouri, Columbia, MO. NY
| | - Manfred Lindau
- School of Engineering and Applied Physics, Cornell University, Ithaca, NY
| | | |
Collapse
|
12
|
Harrison RR, Kier RJ, Chestek CA, Gilja V, Nuyujukian P, Ryu S, Greger B, Solzbacher F, Shenoy KV. Wireless neural recording with single low-power integrated circuit. IEEE Trans Neural Syst Rehabil Eng 2009; 17:322-9. [PMID: 19497825 DOI: 10.1109/tnsre.2009.2023298] [Citation(s) in RCA: 159] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902-928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor.
Collapse
Affiliation(s)
- Reid R Harrison
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT 84112, USA.
| | | | | | | | | | | | | | | | | |
Collapse
|