About this Research Topic
Biosignals have been extensively used in the medical domain for more than 200 years, with Electrocardiography (ECG) and Electroencephalography (EEG) being well-known examples. Over the past decades, the application of computer science and engineering principles to the field has proven to be of paramount importance, leading to remarkable technical, methodological and scientific achievements.
Today, biosignals are a popular topic within the global research community, and potential applications are far-reaching within the medical arena, paving the way for the emerging field of Physiological Computing (PC). In an analogous way to that of physical computing, PC can be defined as the study and development of interactive software and hardware systems capable of sensing, processing, reacting and interfacing the digital and analog worlds. The difference between both is that PC specifically focuses on the use of biosignals, posing a separate class of problems; while biomedical engineering is a classical discipline with affinity to the area, biosignals applied to Human-Computer Interaction (HCI) drive researchers in areas ranging from computer science, electrical engineering, among many others. Just to name a few examples, PC has grown to include human enhancement using exoskeletons, augmentative communication, nonverbal communication (e.g. affective and silent speech interfaces).
PC has also had vast implications within the industrial landscape, for example, the company AliveCor in 2011 debuted an accessory for ECG monitoring in iOS devices, and was later funded by Qualcomm with $10.5M. To date, the research community has been highly fragmented in terms of journal publications that address the interface between HCI and PC; this is especially relevant given the shift of the Brain-Computer Interfaces (BCI) community towards multimodal and non-BCI physiological data (EDA, EMG, Accelerometry, etc). HCI is one of the areas where biomedical signals are demonstrating a high potential to enhance the way people leverage digital interaction, however, such interfaces still present several challenges in what concerns their design and creation.
Many questions regarding the application of PC to next-generation HCI remain open: What information can be extracted from each modality and used for HCI? How can the systems be easy-to-use and a part of the user’s daily life? How should the usefulness and effectiveness of PC interfaces be evaluated? What PC approaches will result in practical and powerful interfaces for real-world deployment? How will the collaboration between HCI and PC researchers affect the architectural framework of the next generation of interfaces?
Encouraged by the fact that PC is attracting an interdisciplinary and increasingly large research community, we believe that the time is ripe to present high-quality, original work that discusses the ways in which PC can support the design, implementation, and evaluation of next-generation human-computer interfaces. The aim of this Research Topic is to present outstanding work related to the use of biomedical signals for next generation computer interfaces. Topics include biomedical devices, machine learning and intelligent interaction moderated by biomedical signals, methods and methodologies, human factors and applications for supporting the development of next-generation HCI interfaces with physiological awareness.
Today, biosignals are a popular topic within the global research community, and potential applications are far-reaching within the medical arena, paving the way for the emerging field of Physiological Computing (PC). In an analogous way to that of physical computing, PC can be defined as the study and development of interactive software and hardware systems capable of sensing, processing, reacting and interfacing the digital and analog worlds. The difference between both is that PC specifically focuses on the use of biosignals, posing a separate class of problems; while biomedical engineering is a classical discipline with affinity to the area, biosignals applied to Human-Computer Interaction (HCI) drive researchers in areas ranging from computer science, electrical engineering, among many others. Just to name a few examples, PC has grown to include human enhancement using exoskeletons, augmentative communication, nonverbal communication (e.g. affective and silent speech interfaces).
PC has also had vast implications within the industrial landscape, for example, the company AliveCor in 2011 debuted an accessory for ECG monitoring in iOS devices, and was later funded by Qualcomm with $10.5M. To date, the research community has been highly fragmented in terms of journal publications that address the interface between HCI and PC; this is especially relevant given the shift of the Brain-Computer Interfaces (BCI) community towards multimodal and non-BCI physiological data (EDA, EMG, Accelerometry, etc). HCI is one of the areas where biomedical signals are demonstrating a high potential to enhance the way people leverage digital interaction, however, such interfaces still present several challenges in what concerns their design and creation.
Many questions regarding the application of PC to next-generation HCI remain open: What information can be extracted from each modality and used for HCI? How can the systems be easy-to-use and a part of the user’s daily life? How should the usefulness and effectiveness of PC interfaces be evaluated? What PC approaches will result in practical and powerful interfaces for real-world deployment? How will the collaboration between HCI and PC researchers affect the architectural framework of the next generation of interfaces?
Encouraged by the fact that PC is attracting an interdisciplinary and increasingly large research community, we believe that the time is ripe to present high-quality, original work that discusses the ways in which PC can support the design, implementation, and evaluation of next-generation human-computer interfaces. The aim of this Research Topic is to present outstanding work related to the use of biomedical signals for next generation computer interfaces. Topics include biomedical devices, machine learning and intelligent interaction moderated by biomedical signals, methods and methodologies, human factors and applications for supporting the development of next-generation HCI interfaces with physiological awareness.
Keywords: Biosignals, Human-Computer Interaction, Machine Learning, Physiological Computing, Biomedical Devices
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