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Unobtrusive Vital Data Recognition by Robots to Enhance Natural Human-Robot Communication

: Bieber, Gerald; Haescher, Marian; Antony, Niklas; Höpfner, Florian; Krause, Silvio


Korn, Oliver (Ed.):
Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction
Cham: Springer International Publishing, 2019 (Human-computer interaction series)
ISBN: 978-3-030-17106-3 (Print)
ISBN: 978-3-030-17107-0 (Online)
Book Article
Fraunhofer IGD ()
Fraunhofer IGD-R ()
mobile webcam; human-robot interaction (HRI); Lead Topic: Smart City; Research Line: Human computer interaction (HCI)

The ongoing technical improvement of robotic assistants, such as robot vacuum cleaners, telepresence robots, or shopping assistance robots, requires a powerful but unobtrusive form of communication between humans and robots. The capabilities of robots are expanding, which entails a need to improve and increase the perception of all possible communication channels. Therefore, the modalities of text- or speech-based communication have to be extended by body language and direct feedback such as non-verbal communication. In order to identify the feelings or bodily reactions of their interlocutor, we suggest that robots should use unobtrusive vital data assessment to recognize the emotional state of the human. Therefore, we present the concept of vital data recognition through the robot touching and scanning body parts. Thereby, the robot measures tiny movements of the skin, muscles, or veins caused by the pulse and heartbeat. Furthermore, we introduce a camera-based, non-body contact optical heart rate recognition method that can be used in robots in order to identify humans’ reactions during robot-human communication or interaction. For the purpose of heart rate and heart rate variability detection, we have used standard cameras (webcams) that are located inside the robot’s eye. Although camera-based vital sign identification has been discussed in previous research, we noticed that certain limitations with regard to real-world applications still exist. We identified artificial light sources as one of the main influencing factors. Therefore, we propose strategies that aim to improve natural communication between social robots and humans.