Design and Implementation of a Hybrid Wireless Power and Communication System for Medical Implants

• Published in: arXiv.org 2023-11
• Main Authors: Khaleghi, A, Hasanvand, A, Balasingham, I
• Format: Article
• Language: English
• Subjects: Algorithms; Antennas; Artificial intelligence; Backscattering; Big Data; Communication; Communications systems; Data analysis; Data collection; Machine learning; Radio frequency; Surgical implants; Tissues; Transplants & implants; Wireless communications
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2311.08933

Data collection and analysis from multiple implant nodes in humans can provide targeted medicine and treatment strategies that can prevent many chronic diseases. This data can be collected for a long time and processed using artificial intelligence (AI) techniques in a medical network for early detection and prevention of diseases. Additionally, machine learning (ML) algorithms can be applied for the analysis of big data for health monitoring of the population. Wireless powering, sensing, and communication are essential parts of future wireless implants that aim to achieve the aforementioned goals. In this paper, we present the technical development of a wireless implant that is powered by radio frequency (RF) at 401 MHz, with the sensor data being communicated to an on-body reader. The implant communication is based on two simultaneous wireless links: RF backscatter for implant-to-on-body communication and a galvanic link for intra-body implant-to-implant connectivity. It is demonstrated that RF powering, using the proposed compact antennas, can provide an efficient and integrable system for powering up to an 8 cm depth inside body tissues. Furthermore, the same antennas are utilized for backscatter and galvanic communication.