Co-Design Method and Wafer-Level Packaging Technique of Thin-Film Flexible Antenna and Silicon CMOS Rectifier Chips for Wireless-Powered Neural Interface Systems

Okabe, Kenji; Jeewan, Horagodage Prabhath; Yamagiwa, Shota; Kawano, Takeshi; Ishida, M.; Akita, Ippei

doi:10.3390/s151229885

Cited by 10 publications

(3 citation statements)

References 38 publications

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“…There have been many designs of wireless neural stimulators that are relatively large in size (>1 mm 3 ) (Okabe et al, 2015 ; Zargham and Gulak, 2015 ; Larson and Nurmikko, 2016 ). The well-known RF BION uses inductive coupling at 2 MHz with a multi-turn coil with ferrite, but is ~10 times larger than our device, measuring 16 mm in length and 2 mm in diameter (Loeb et al, 2001 ).…”

Section: Discussionmentioning

confidence: 99%

A Sub-millimeter, Inductively Powered Neural Stimulator

et al. 2017

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Wireless neural stimulators are being developed to address problems associated with traditional lead-based implants. However, designing wireless stimulators on the sub-millimeter scale (<1 mm3) is challenging. As device size shrinks, it becomes difficult to deliver sufficient wireless power to operate the device. Here, we present a sub-millimeter, inductively powered neural stimulator consisting only of a coil to receive power, a capacitor to tune the resonant frequency of the receiver, and a diode to rectify the radio-frequency signal to produce neural excitation. By replacing any complex receiver circuitry with a simple rectifier, we have reduced the required voltage levels that are needed to operate the device from 0.5 to 1 V (e.g., for CMOS) to ~0.25–0.5 V. This reduced voltage allows the use of smaller receive antennas for power, resulting in a device volume of 0.3–0.5 mm3. The device was encapsulated in epoxy, and successfully passed accelerated lifetime tests in 80°C saline for 2 weeks. We demonstrate a basic proof-of-concept using stimulation with tens of microamps of current delivered to the sciatic nerve in rat to produce a motor response.

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Section: Discussionmentioning

confidence: 99%

A Sub-millimeter, Inductively Powered Neural Stimulator

et al. 2017

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“…Three key areas rapidly hastening the onset of effective intra-cortical BCIs include developments in: Electrodes and other implantable materials with reduced neuro-inflammatory responses, including recent advances in carbon nanotube (CNT) electrodes [16,17,18,19,20,21,22],Novel fabrications allowing much greater sensor density [23,24,25,26], andImproved wireless communication and power transmission technologies [27,28,29]. …”

Section: Introductionmentioning

confidence: 99%

The Cluster Variation Method: A Primer for Neuroscientists

Maren

2016

Brain Sciences

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Effective Brain–Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables, is defined in terms of a single interaction enthalpy parameter (h) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

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“…Most common elastomeric materials have low dielectric constants. This low value can be increased by mixing the substrate with high dielectric constant materials such as ceramics like Ba x Sr 1−x TiO 3 [ 258 ] , BaTiO 3 [ 257 ], NdTiO 3 [ 259 ], MgCaTiO 2 [ 259 ], CNTs [ 260 ], and nanoparticles [ 261 ]. Metamaterial based flexible antenna is a relatively new development and has found its way in the commercial market because of its characteristics like lightweight, robustness, and reconfigurability [ 239 , 262 , 263 , 264 , 265 ].…”

Section: Challenges and Future Prospects Of Flexible Antennasmentioning

confidence: 99%

Flexible Antennas: A Review

et al. 2020

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The field of flexible antennas is witnessing an exponential growth due to the demand for wearable devices, Internet of Things (IoT) framework, point of care devices, personalized medicine platform, 5G technology, wireless sensor networks, and communication devices with a smaller form factor to name a few. The choice of non-rigid antennas is application specific and depends on the type of substrate, materials used, processing techniques, antenna performance, and the surrounding environment. There are numerous design innovations, new materials and material properties, intriguing fabrication methods, and niche applications. This review article focuses on the need for flexible antennas, materials, and processes used for fabricating the antennas, various material properties influencing antenna performance, and specific biomedical applications accompanied by the design considerations. After a comprehensive treatment of the above-mentioned topics, the article will focus on inherent challenges and future prospects of flexible antennas. Finally, an insight into the application of flexible antenna on future wireless solutions is discussed.

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Co-Design Method and Wafer-Level Packaging Technique of Thin-Film Flexible Antenna and Silicon CMOS Rectifier Chips for Wireless-Powered Neural Interface Systems

Cited by 10 publications

References 38 publications

A Sub-millimeter, Inductively Powered Neural Stimulator

A Sub-millimeter, Inductively Powered Neural Stimulator

The Cluster Variation Method: A Primer for Neuroscientists

Flexible Antennas: A Review

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