Modeling of Capacitive Resonant Wireless Power and Data Transfer to Deep Biomedical Implants

被引:39
|
作者
Narayanamoorthi, R. [1 ]
机构
[1] SRM Inst Sci & Technol, Elect & Elect Engn, Chennai 603203, Tamil Nadu, India
关键词
Capacitive data transfer; Internet of Things (IoT); intracranial pressure; resonant electric coupling; wireless power transfer; TRANSFER SYSTEM; ENERGY; SENSOR;
D O I
10.1109/TCPMT.2019.2922046
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Neural implantable sensors require a harmless sustainable wireless power transfer technique for their lifetime operation. The capacitive-coupled (CC) power transfer method has proved to induce minimum electromagnetic interference as compared with inductive resonant power transfer. However, the CC method suffers from the limitation of low power transfer efficiency (PTE) and is suitable only for short-distance power transfer applications. In physical health-monitoring practices, the deep implants require high PTE with minimum electromagnetic interference. Similarly, the measured data need to be transmitted to the external world for remote monitoring and analysis. Nevertheless, the size and safety constraints limit the direct interfacing of the data communication module to implants. With this objective, this paper proposes a resonant capacitive-coupling (RCC) approach for wireless power transfer to brain implants. Moreover, to further improve the PTE, the proposed model is investigated with the additional intermediate plate capacitance between the transmitter (Tx) and the receiver (Rx). The analytical and experimental studies are carried out for intracranial pressure sensor (ICP) application and obtain the PTE of 24.2%, 34.14%, and 42.21% for CC, RCC, and RCC with an intermediate plate (RCCI) approaches, respectively. In addition, to eliminate the use of the antenna for data transfer, the same capacitive plates are used and tested with amplitude phase-shift keying (ASK) modulation technique for uplink communication. The proposed system is also integrated with the Internet of Things (IoT) module for the remote monitoring and analyses of patient health.
引用
收藏
页码:1253 / 1263
页数:11
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