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Benedict BC, Ghanbari MM, Muller R. Phased Array Beamforming Methods for Powering Biomedical Ultrasonic Implants. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2022; 69:2756-2765. [PMID: 35939455 DOI: 10.1109/tuffc.2022.3197705] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Millimeter-scale implants using ultrasound (US) for power and communication have been proposed for a range of deep-tissue applications, including neural recording and stimulation. However, published implementations have shown high sensitivity to misalignment with the external US transducer. Ultrasonic beamforming using a phased array to these implants can improve tolerance to misalignment, reduce implant volume, and allow multiple implants to be operated simultaneously in different locations. This article details the design of a custom planar phased array US system, which is capable of steering and focusing US power within a 3-D volume. Analysis and simulation is performed to determine the choice of array element pitch, with special attention given to maximizing the power available at the implant while meeting FDA limits for diagnostic US. Time reversal (TR) is proposed as a computationally simple approach to beamforming that is robust despite scattering and inhomogeneity of the acoustic medium. This technique is demonstrated both in active drive and pulse-echo modes, and it is experimentally compared with other beamforming techniques by measuring energy transfer efficiency. Simultaneous power delivery to multiple implants is also demonstrated.
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Barbruni GL, Ros PM, Demarchi D, Carrara S, Ghezzi D. Miniaturised Wireless Power Transfer Systems for Neurostimulation: A Review. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2020; 14:1160-1178. [PMID: 33201828 DOI: 10.1109/tbcas.2020.3038599] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In neurostimulation, wireless power transfer is an efficient technology to overcome several limitations affecting medical devices currently used in clinical practice. Several methods were developed over the years for wireless power transfer. In this review article, we report and discuss the three most relevant methodologies for extremely miniaturised implantable neurostimulators: ultrasound coupling, inductive coupling and capacitive coupling. For each powering method, the discussion starts describing the physical working principle. In particular, we focus on the challenges given by the miniaturisation of the implanted integrated circuits and the related ad-hoc solutions for wireless power transfer. Then, we present recent developments and progresses in wireless power transfer for biomedical applications. Last, we compare each technique based on key performance indicators to highlight the most relevant and innovative solutions suitable for neurostimulation, with the gaze turned towards miniaturisation.
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Cagnan H, Denison T, McIntyre C, Brown P. Emerging technologies for improved deep brain stimulation. Nat Biotechnol 2019; 37:1024-1033. [PMID: 31477926 PMCID: PMC6877347 DOI: 10.1038/s41587-019-0244-6] [Citation(s) in RCA: 108] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 07/26/2019] [Indexed: 12/18/2022]
Abstract
Deep brain stimulation (DBS) is an effective treatment for common movement disorders and has been used to modulate neural activity through delivery of electrical stimulation to key brain structures. The long-term efficacy of stimulation in treating disorders, such as Parkinson's disease and essential tremor, has encouraged its application to a wide range of neurological and psychiatric conditions. Nevertheless, adoption of DBS remains limited, even in Parkinson's disease. Recent failed clinical trials of DBS in major depression, and modest treatment outcomes in dementia and epilepsy, are spurring further development. These improvements focus on interaction with disease circuits through complementary, spatially and temporally specific approaches. Spatial specificity is promoted by the use of segmented electrodes and field steering, and temporal specificity involves the delivery of patterned stimulation, mostly controlled through disease-related feedback. Underpinning these developments are new insights into brain structure-function relationships and aberrant circuit dynamics, including new methods with which to assess and refine the clinical effects of stimulation.
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Affiliation(s)
- Hayriye Cagnan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Timothy Denison
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Engineering Sciences, University of Oxford, Oxford, UK
| | - Cameron McIntyre
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Peter Brown
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Carmena JM, Rabaey JM, Alon E, Boser BE, Maharbiz MM. Ultrasonic beamforming system for interrogating multiple implantable sensors. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2015:2673-6. [PMID: 26736842 DOI: 10.1109/embc.2015.7318942] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
In this paper, we present an ultrasonic beamforming system capable of interrogating individual implantable sensors via backscatter in a distributed, ultrasound-based recording platform known as Neural Dust [1]. A custom ASIC drives a 7 × 2 PZT transducer array with 3 cycles of 32V square wave with a specific programmable time delay to focus the beam at the 800mm neural dust mote placed 50mm away. The measured acoustic-to-electrical conversion efficiency of the receive mote in water is 0.12% and the overall system delivers 26.3% of the power from the 1.8V power supply to the transducer drive output, consumes 0.75μJ in each transmit phase, and has a 0.5% change in the backscatter per volt applied to the input of the backscatter circuit. Further miniaturization of both the transmit array and the receive mote can pave the way for a wearable, chronic sensing and neuromodulation system.
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Muraskin J, Sherwin J, Lieberman G, Garcia JO, Verstynen T, Vettel JM, Sajda P. Fusing multiple neuroimaging modalities to assess group differences in perception-action coupling. PROCEEDINGS OF THE IEEE. INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS 2017; 105:83-100. [PMID: 28713174 PMCID: PMC5509353 DOI: 10.1109/jproc.2016.2574702] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
In the last few decades, non-invasive neuroimaging has revealed macro-scale brain dynamics that underlie perception, cognition and action. Advances in non-invasive neuroimaging target two capabilities; 1) increased spatial and temporal resolution of measured neural activity, and 2) innovative methodologies to extract brain-behavior relationships from evolving neuroimaging technology. We target the second. Our novel methodology integrated three neuroimaging methodologies and elucidated expertise-dependent differences in functional (fused EEG-fMRI) and structural (dMRI) brain networks for a perception-action coupling task. A set of baseball players and controls performed a Go/No-Go task designed to mimic the situation of hitting a baseball. In the functional analysis, our novel fusion methodology identifies 50ms windows with predictive EEG neural correlates of expertise and fuses these temporal windows with fMRI activity in a whole-brain 2mm voxel analysis, revealing time-localized correlations of expertise at a spatial scale of millimeters. The spatiotemporal cascade of brain activity reflecting expertise differences begins as early as 200ms after the pitch starts and lasting up to 700ms afterwards. Network differences are spatially localized to include motor and visual processing areas, providing evidence for differences in perception-action coupling between the groups. Furthermore, an analysis of structural connectivity revealed that the players have significantly more connections between cerebellar and left frontal/motor regions, and many of the functional activation differences between the groups are located within structurally defined network modules that differentiate expertise. In short, our novel method illustrates how multimodal neuroimaging can provide specific macro-scale insights into the functional and structural correlates of expertise development.
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Affiliation(s)
- Jordan Muraskin
- Columbia University, Department of Biomedical Engineering, New York, NY, USA
| | - Jason Sherwin
- Columbia University, Department of Biomedical Engineering, New York, NY, USA
| | - Gregory Lieberman
- U.S. Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA. He is also with University of Pennsylvania, Department of Bioengineering, Philadelphia, PA, USA
| | - Javier O Garcia
- U.S. Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA
| | - Timothy Verstynen
- Carnegie Mellon University, Department of Psychology, Pittsburgh, PA, USA
| | - Jean M Vettel
- U.S. Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA. He is also with University of Pennsylvania, Department of Bioengineering, Philadelphia, PA, USA and also with University of California, Santa Barbara, Department of Psychological & Brain Sciences, Santa Barbara, CA, USA
| | - Paul Sajda
- Columbia University, Department of Biomedical Engineering, New York, NY, USA
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Bertrand A. Distributed Signal Processing for Wireless EEG Sensor Networks. IEEE Trans Neural Syst Rehabil Eng 2015; 23:923-35. [DOI: 10.1109/tnsre.2015.2418351] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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