Contactless measurement of physiological parameters The possibility of remote measurement of vital parameters makes it possible to implement telemedicine systems. However these systems are of particular interest for subjects who, due to age or pathologies, are weak and fragile. For these subjects, the management of devices for measuring vital parameters that must be appropriately positioned in contact with the skin, in fixed positions, is difficult. For this reason, in this paper two technologies are shown for the noncontact measurement of two physiological parameters, heart rate and respiratory rate, based on the acquisition and processing of video signals and radar signals. The techniques presented are based on the use of commercial devices. The use of these technologies simplifies the acquisition of vital parameters compared to traditional technologies. The reliability of the measured values was evaluated by comparing the values obtained with a pulse oximeter and an app on a smartphone.

Multiperson remote heartrate measurement from human faces  a CNN based approach The conventional heart rate measurement techniques using electrocardiogram, wrist belts and so on, are attached with some disadvantages like discomfort, irritation of the skin and even more. From this starting point various video based heart rate measurement techniques were developed in the last years. All of these techniques use video data of the human faces to extract information to estimate the heart rate of the person in front of the camera. Most of them work with the detection of minimal changes in the color spectrum of the recorded video data. With these extracted information and multiple concluding steps, they are able to estimate the heart rate of the person sitting in front of the camera. All of these approaches have some big disadvantages, they are only able to measure the heart rate of one person  and in a small number of cases up to three persons. So the main objective of this work is to adapt and enhance existing research approaches of processing visual biological signals. The focus is set on the design and deployment of a new system, which is able to process visual data as well as detect and localize human faces by using artificial neural networks and calculate each individuals heart rate from the processed dataxe2x80x99s information. For the first time in this research area, different scenarios with more than three observed participants are being analyzed to calculate the heart rate for each of them separately. It will be shown that by using the applied technical architecture and technologies, it is possible to deploy a comparable and qualitatively competitive system. In addition, the implemented system proves the feasibility of processing various facesxe2x80x99 signals and calculating the respective heart rates simultaneously within an acceptable range of tolerance.