Networks of injectable microdevices powered and digitally linked by volume conduction for neuroprosthetics: a proof-of-concept
Networks of injectable microdevices powered and digitally linked by volume conduction for neuroprosthetics: a proof-of-concept
Citació
- Becerra-Fajardo L, Minguillon J, Comerma A, Ivorra A. Networks of injectable microdevices powered and digitally linked by volume conduction for neuroprosthetics: a proof-of-concept. In: 11th International IEEE/EMBS Conference on Neural Engineering (NER 2023); 2023 Apr 24-27; Baltimore, United States. [Piscataway]: IEEE; 2023. [4 p.]. DOI: 10.1109/NER52421.2023.10123743
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Descripció
Resum
Wireless power transfer (WPT) methods such as inductive coupling and ultrasounds are used as an alternative to electrochemical batteries to energize active implantable medical devices. However, existing WPT methods require the use of bulky components (e.g., coils) that hinder miniaturization. To avoid this, we proposed the use of volume conduction of high frequency (HF) current bursts to power and bidirectionally communicate with threadlike implants that can be used for electrical stimulation and sensing (e.g., electromyography acquisition). Here, we in vitro demonstrate that several wireless devices can be powered and digitally linked by volume conduction. Eleven devices were randomly placed in a saline medium and were enclosed by two electrodes connected to an external system. The system interrogated the devices, and the waveforms obtained by the external system's demodulator were digitally processed to decode the information sent by the devices through the same HF current bursts. Data was successfully decoded from the devices, independently of the power that each single device obtained. The WPT efficiency of volume conduction boosts when a massive number of devices are powered with a single external system, creating a network of microdevices for neuroprosthetics. This will allow to accomplish closed-loop control for neural interphases using highly miniaturized injectable devices.Descripció
Comunicació presentada a 11th International IEEE/EMBS Conference on Neural Engineering (NER 2023), celebrada del 24 al 27 d'abril de 2023 a Baltimore, Estats Units.