IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology · 2018 · 65 citations · 27 references
EngineeringBioengineeringBiomedical EngineeringBiosensorsNeural EngineeringSensorsBiopotential MeasurementImplant TechnologyImplantable Biomedical DevicesImplantable Neural DevicesNeural InterfacesNeural Signal AcquisitionMultichannel Biopotential RecordingMultichannel Signal AcquisitionNeural RecordingNeural Recording SystemsNeural Signal RecordingNoninvasive Neural RecordingWireless Biopotential AcquisitionWireless Neural Recording
We propose a novel multi-channel (eight channels) passive neuro-sensing system for wireless acquisition of brain signals as low as 20 μVpp. Compared to previous batteryless multichannel neuropotential sensors, the proposed design exhibits 28 times better sensitivity, ~ 2 times smaller footprint, and scalability to 100s or even 1000s of channels. The proposed system consists of an external interrogator and a neuro-recorder implanted inside the scalp. For operation, the interrogator first sends a 2.4 GHz carrier signal to “turn on” the implant and, second, an infrared control signal for channel selection. The latter activates the desired channel via a photo-activated multiplexer. For this channel, the carrier signal is mixed with the neural signal (fneuro) to generate a 4.8 GHz ± fneuro modulated signal. The latter is then transmitted back to the interrogator. To verify the implant's operation inside biological tissues, in vitro measurements are presented using pig skin. Experimental results show that the proposed neuropotential recorder exhibits 20 μVpp sensitivity at all eight channels (viz. it can record any signal generated by the human brain). The system is also in compliance with the strictest Federal Communications Commission standards for patient safety. Notably, the proposed approach is scalable to a much higher number of channels. As such, the proposed system can be a game-changing capability for a wide range of applications.
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Genetic algorithms in electromagnetics
Choice Reviews Online · 2007 · 395 citations
Engineering, Computational Engineering, Electrical Engineering +17
A Minimally Invasive 64-Channel Wireless μECoG Implant
Rikky Muller, Hanh‐Phuc Le, Wen Li et al. · IEEE Journal of Solid-State Circuits · 2014 · 368 citations · Full text
Engineering, Biomedical Engineering, Electrical Engineering +17