Intra-Body Communications for Nervous System Applications: Current Technologies and Future Directions

The Internet of Medical Things (IoMT) paradigm will enable next generation healthcare by enhancing human abilities, supporting continuous body monitoring and restoring lost physiological functions due to serious impairments. This paper presents intra-body communication solutions that interconnect implantable devices for application to the nervous system, challenging the specific features of the complex intra-body scenario. The presented approaches include both speculative and implementative methods, ranging from neural signal transmission to testbeds, to be applied to specific neural diseases therapies. Also future directions in this research area are considered to overcome the existing technical challenges mainly associated with miniaturization, power supply, and multi-scale communications.

Linear approximation of CPM signals for a reduced-complexity, multi-mode telemetry transmitter

In space applications, hardware (HW) implementation is made more expensive not only by the levels of performance required, but also by complex and rigorous HW qualification tests. Reducing qualification cost and time is thus a key design requirement. In this paper, a new versatile transmitter is proposed for space telemetry, capable of soft-switching across different linear and continuous phase modulation schemes while maintaining the same hardware structure. This permits a single HW qualification to ``cover'' diverse uses of the same hardware, and thus avoid re-qualification in case of configuration changes. The envisaged solution foresees the use of a single filter, suitable not only for linear modulations such as M-QAM, but also for continuous phase modulation methods. At this stage, we focus on pulse code modulation/frequency modulation (PCM/FM), for which we propose a minimum mean square error (MMSE) algorithm. The proposed algorithm, which adds to the system flexibility and effectiveness, may use a single first filter based on Laurent decomposition for initialization, if needed. Performances are assessed using the mean square error (MSE) measure between the proposed MMSE-modulated signal and the completely modulated signal. Simulation results confirm that the proposed algorithm leads to MSE values that are lower than the case of Laurent decomposition using the first component only.