In the present contribution, we introduce a wireless optical communication-based system architecture which is shown to significantly improve the reliability and the spectral and power efficiency of the transcutaneous link in cochlear implants (CIs). We refer to the proposed system as optical wireless cochlear implant (OWCI). In order to provide a quantified understanding of its design parameters, we establish a theoretical framework that takes into account the channel particularities, the integration area of the internal unit, the transceivers misalignment, and the characteristics of the optical units. To this end, we derive explicit expressions for the corresponding average signal-to-noise-ratio, outage probability, ergodic spectral efficiency and capacity of the transcutaneous optical link (TOL). These expressions are subsequently used to assess the dependence of the TOL's communication quality on the transceivers design parameters and the corresponding channels characteristics. The offered analytic results are corroborated with respective results from Monte Carlo simulations. Our findings reveal that OWCI is a particularly promising architecture that drastically increases the reliability and effectiveness of the CI TOL, whilst it requires considerably lower transmit power compared to the corresponding widely-used radio frequency (RF) solution.

In this paper, we assess the signal quality of the out-body to in-body optical communication link, which can be used as a fundamental enabler of novel biomedical appliances, such as medical implants, as well as biological and chemical components monitoring. In particular, we present a mathematical understanding of the transdermal system, which takes into account the optical channel characteristics, the integrated area limitations of the in-body unit, the transceivers’ pointing errors and the particularities of the optical units. Moreover, to accommodate the propagation characteristics, we present a novel simplified, but accurate, transdermal path-gain model. Finally, we extract low-complexity closed-form expressions for the instantaneous and average signal to noise ratio of the transdermal optical link (TOL). Numerical and simulation results are provided for several insightful scenarios and reveal that pointing errors can significantly affect the reliability and effectiveness of the TOL; hence, it should be taken into account in the analysis and design of such systems.

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Machine learning (ML) empowers biomedical systems with the capability to optimize their performance through modeling of the available data extremely well, without using strong assumptions about the modeled system. Especially in nanoscale biosystems, where the generated data sets are too vast and complex to mentally parse without computational assist, ML is instrumental in analyzing and extracting new insights, accelerating material and structure discoveries and designing experience as well as supporting nano-scale communications and networks. However, despite these efforts, the use of ML in nano-scale biomedical engineering remains still under-explored in certain areas and research challenges are still open in fields such as structure and material design and simulations, communications and signal processing, and bio-medicine applications. In this article, we review the existing research regarding the use of ML in nano-scale biomedical engineering. In more detail, we first identify and discuss the main challenges that can be formulated as ML problems. These challenges are classified in the three aforementioned main categories. Next, we discuss the state of the art ML methodologies that are used to countermeasure the aforementioned challenges. For each of the presented methodologies, special emphasis is given to its principles, applications and limitations. Finally, we conclude the article with insightful discussions, that reveals research gaps and highlights possible future research directions.

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