A Low-Power, Wireless, Capacitive Sensing Frontend Based on a Self-Oscillating Inductive Link

Schormans, Matthew; Valente, Virgilio; Demosthenous, Andreas

doi:10.1109/tcsi.2018.2835148

Cited by 8 publications

(2 citation statements)

References 25 publications

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“…WIRELESS Sensing has emerged as a viable option for implantable medical devices (IMDs) [ 1 ] with an essential need for power and device size minimizations. Numerous works and approaches for neural recording and wireless transmission/reception using integrated CMOS circuits have been reported with robust functionalities [ 2 ], [ 3 ], [ 4 ], [ 5 ], [ 6 ], [ 7 ], [ 8 ], [ 9 ], [ 10 ], [ 11 ], [ 12 ], [ 13 ]. Power-efficient brain machine interface circuits for neural recording with feature extraction have also been reported [ 14 ], [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

Das

Nasrollahpour

et al. 2023

IEEE Open J. Circuits Syst.

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A magnetoelectric antenna (ME) can exhibit the dual capabilities of wireless energy harvesting and sensing at different frequencies. In this article, a behavioral circuit model for hybrid ME antennas is described to emulate the radio frequency (RF) energy harvesting and sensing operations during circuit simulations. The ME antenna of this work is interfaced with a CMOS energy harvester chip towards the goal of developing a wireless communication link for fully integrated implantable devices. One role of the integrated system is to receive pulsemodulated power from a nearby transmitter, and another role is to sense and transmit low-magnitude neural signals.The measurements reported in this paper are the first results that demonstrate simultaneous low-frequency wireless magnetic sensing and high-frequency wireless energy harvesting at two different frequencies with one dual-mode ME antenna. The proposed behavioral ME antenna model can be utilized during design optimizations of energy harvesting circuits. Measurements were performed to validate the wireless power transfer link with an ME antenna having a 2.57 GHz resonance frequency connected to an energy harvester chip designed in 65nm CMOS technology. Furthermore, this dual-mode ME antenna enables concurrent sensing using a carrier signal with a frequency that matches the second 63.63 MHz resonance mode. A wireless test platform has been developed for evaluation of ME antennas as a tool for neural implant design, and this prototype system was utilized to provide first experimental results with the transmission of magnetically modulated action potential waveforms. W

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Section: Introductionmentioning

confidence: 99%

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

Das

Nasrollahpour

et al. 2023

IEEE Open J. Circuits Syst.

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show abstract

“…In DCM, when the inductor current drops to zero, the inductor current flows backwards, which results in the current intrusion and a great fluctuation of the output voltage [38], [39]. To prevent the current intrusion phenomenon, the zero-crossing detection circuit is usually used in [32], [34], and [35], but it increases the system cost and its accuracy influences the control performance.…”

Section: Introductionmentioning

confidence: 99%

A Soft-Switching Control for Cascaded Buck-Boost Converters Without Zero-Crossing Detection

Liu

Song

et al. 2019

IEEE Access

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This paper proposes a novel soft-switching control without zero-crossing detection for the cascaded buck-boost converters (CBBCs). The proposed soft-switching control consists of two parts: soft-switching modulation and closed-loop control. In the modulation, the employed PWM approach is constructed by introducing a small negative current into the conventional PWM, and the soft-switching modulation based on the negative-current-based PWM is presented by adding a new switching process controlled by a modulation variable in the CBBC. In the closed-loop control, the relationship between the models of the negative-current-based PWM and the soft-switching modulation is deduced, and by utilizing the deduced relationship, the closed-loop control is designed while the PWM is modified to achieve the softswitching. Meanwhile, to further reduce the ripple current and device losses, the parameter of the proposed control is optimized by refining the restrictive conditions. While the zero-crossing point of the inductor current is calculated with a given algorithm based on a current measurement, the circuit of zero-crossing detection is avoided. The validity and feasibility of the proposed soft-switching control approach are confirmed by the simulations and experiments on a 200-W prototype. INDEX TERMS Soft-switching control, negative-current-based PWM, zero-crossing detection, optimal design, CBBC.

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Inductively-Coupled MEMS Pressure Sensor

Patel,

Darbasi,

Antoniades

et al. 2023

2023 IEEE Biomedical Circuits and Systems Conference (BioCAS)

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A Low-Power, Wireless, Capacitive Sensing Frontend Based on a Self-Oscillating Inductive Link

Cited by 8 publications

References 25 publications

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

A Soft-Switching Control for Cascaded Buck-Boost Converters Without Zero-Crossing Detection

Inductively-Coupled MEMS Pressure Sensor

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