# Special Issue \"Body Sensors Networks for E-Health Applications\"
## 4 Articles Related to Communication Protocols in the Field of BSN  
Communication protocols are another aspect of interest in BSNs. In this sense, the study presented in Reference [6] proposes an energy efficient routing protocol for intrabody wireless networks of biomedical sensors based on nanotechnology. Thanks to new materials such as carbon nanotubes and graphene, new sensorization opportunities are opening up in the field of biomedicine, taking advantage of their size, sensitivity and biocompatibility. These materials operate at frequencies close to terahertz, but this is an underused spectrum that can have a great impact on the future development of medical technologies, since it allows a smaller size of the antennas, a greater bandwidth, a lower sensitivity to dispersion and propagation effects, and greater safety in biological mediums. Wireless NanoSensor Networks (WNSN) address the communication problems of nano-sensors and nano-devices. In this type of network, the measurement is performed by a large group of nano-sensors distributed in the area of interest. Furthermore, the nodes have very limited energy and computational resources. These aspects condition communications, which must be carried out cooperatively and be managed using routing protocols of low complexity and high energy efficiency. The protocol described in Reference [6] proposes a new clustering method to solve the problems derived from the high number and short communication range of the nano-nodes in a WNSN inside the human body. This protocol continuously updates the main node of the cluster between the nodes with the highest residual energy, balancing the power consumption of the network. The clustering of the nodes is done in layers so that a data packet can be sent to the main node of the cluster in one hop. The number of nodes in the cluster can be reduced in order to decrease the overall energy consumption of the network. Finally, the main nodes of the cluster communicate with a control node through multi-hop routing. The simulation results highlight the advantages of the proposed protocol over other recent protocols, guaranteeing energy efficiency and the success rate in the information transmission.  
The study carried out in Reference [7] focuses on the external access of the BSNs, placing special interest in the analysis of the influence of the human body on this type of wireless communication. Recent research papers are investigating the improvements provided by the dynamic adaptation to conditions of line-of-sight (LOS) or non-line-of-sight (NLOS). In this way it is possible to minimize the packet error rate by dynamically adapting the transmission bit rate depending on the visibility conditions caused by the changing nature of the communication channel due to the presence of the human body. The protocol proposed in Reference [7] is based in Ultra-Wideband (UWB) technology because of its robustness in multipath conditions versus narrowband options, and uses a low complexity Deep Neural Network (DNN) (only two hidden layers, each with 50 nodes) that can be run in real time in a standard general-purpose microcontroller. The experimental results confirmed the benefits of DNN in classifying LOS and NLOS conditions in different experiments carried out with volunteers. Based on these results, it could be concluded that body structure and body mass index (BMI) are factors that affect the effectiveness of the classification algorithm, being lower in subjects with higher BMI. Furthermore, the suitability of self-learning technologies for their application in radio communication systems is confirmed.