Current cardiopulmonary activity monitoring is based on contact devices which cannot be used in extreme cases such as premature infants, burnt victims or rescue operations. In order to overcome these limitations, the use of radar technologies emerges as an alternative. This paper aims to enhance the comprehension that non-contact technologies, in particular radar techniques, offer as a monitoring tool. For this purpose, a modified low cost commercial 122 GHz frequency-modulated continuous-wave (FMCW) radar is used to better fit the current application domain. The radar signals obtained are processed using a classic linear filtering algorithm aiming to separate the breathing from the heartbeat component while preserving signals integrity. In a standoff configuration and with different subject orientations, results show that the signal obtained with the radar can be used to extract not only the respiratory and heartbeat rates, but also the heart rate variability (HRV) sequence. Moreover, results evidence the coupling between breathing and heartbeat, also showing that the HRV sequence obtained can identify the respiratory sinus arrhythmia (RSA) effect. Finally, the radar is tested in a simultaneous multi-target scenario, demonstrating its monitoring capabilities in more complex situations. Nevertheless, there are some challenges left to use the system in a real-life monitoring environments, such as the removal of random body movements.

The Internet of Things (IoT) is one of today’s main disruptive technologies and, although massive research has been carried out in recent years, there are still some open issues such as the consideration of software engineering methods and tools. We propose the adoption of the Teleo-Reactive approach in order to facilitate the development of Internet of Things systems as a set of communicating Teleo-Reactive nodes. The software behavior of the nodes is specified in terms of goals, perceptions and actions over the environment, achieving higher abstraction than using general-purpose programming languages and therefore, enhancing the involvement of non-technical users in the specification process. Throughout this paper, we describe the elements of a Teleo-Reactive node and a systematic procedure for translating Teleo-Reactive specifications into executable code for Internet of Things devices. The case study of a robotic agent is used in order to validate the whole approach.

The use of radar technology for contactless monitoring of cardiorespiratory activity has been a significant research topic for the last two decades. However, despite the abundant literature focusing on the use of different radar architectures for healthcare applications, an in-depth analysis is missing about the most appropriate configuration. This paper presents a comparison between continuous-wave (CW) and linear-frequencymodulated continuous-wave (LFMCW) radars for application in vital sign monitoring scenarios. These waveforms are generated with the same architecture at two different frequencies: 24 and 134 GHz. Results evidence that both configurations are capable of measuring general metrics, such as the breathing and heart rates. However, LFMCW offers better results in the identification of cardiac events and the extraction of certain derived biomarkers, such as the heart rate variability sequences (HRV). Conclusions show that this performance does not depend on the selected working frequency.