I. Introduction
A wearable device is an electronic system that is worn by a user as an accessory to monitor different physiological parameters during several daily activities, improving personal health, from sport to health care. They monitor several phys-iological parameters and collect biometric data such as the heart rate (ECG and HRV) and muscle bio-signals (EMG) from human body to provide valuable information in the field of healthcare and wellness [1], [2]. Moreover, they work as a receiver for the collection and retransmission of these signals. When more than one device is included, a true network of sensors can be created [3]. In case of body area network, communication strategies are needed to improve the performance [5], [13]. In this sense, the complexity of the network devices may generate not negligible interference issues [6]. Besides possible EMI problems, another important issue is the potential risk due to the human body exposure to the electromagnetic field generated by such devices. In fact, considering standardized safety limits [7]–[10] dosimetry of wearable wireless devices is of crucial importance [11], [12]. In particular, the computation of the specific absorption rate (SAR) of wearable antennas represents a valuable assessment parameter [14], [15], also considering functional aspects due to the body shadow effect [16]. As a consequence, the research activity in design antennas able to minimize the exposure is essential [17], [18]. In the present contribution, the SAR generated by a wearable device is computed by means of a full wave FDTD code running on a supercomputer [19]. A high resolution body model has been considered in order to get a high accuracy in the electromagnetic field computation, including precise values for the tissue permittivity and conduc-tivity. The geometry and the feeding point of device's antenna is accurately included in the code. The availability of a code running on a supercomputer allows to repeat quickly many simulations, by adding small parametric variations like the device position on the human body and its orientation. In that way, a statistical analysis of the SAR and antenna matching variations can be carried out.