@article{chiossi2023senscon, title = {SensCon: Embedding Physiological Sensing into Virtual Reality Controllers}, author = {Francesco Chiossi and Thomas Kosch and Luca Menghini and Steeven Villa and Sven Mayer}, year = {2023}, journal = {Proc. ACM Hum.-Comput. Interact.}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, number = {MobileHCI}, doi = {10.1145/3604270}, url = {https://sven-mayer.com/wp-content/uploads/2023/07/chiossi2023senscon.pdf}, date = {2023-01-01}, issue = {7}, abstract = {Virtual reality experiences increasingly use physiological data for virtual environment adaptations to evaluate user experience and immersion. Previous research required complex medical-grade equipment to collect physiological data, limiting real-world applicability. To overcome this, we present SensCon for skin conductance and heart rate data acquisition. To identify the optimal sensor location in the controller, we conducted a first study investigating users' controller grasp behavior. In a second study, we evaluated the performance of SensCon against medical-grade devices in six scenarios regarding user experience and signal quality. Users subjectively preferred SensCon in terms of usability and user experience. Moreover, the signal quality evaluation showed satisfactory accuracy across static, dynamic, and cognitive scenarios. Therefore, SensCon reduces the complexity of capturing and adapting the environment via real-time physiological data. By open-sourcing SensCon, we enable researchers and practitioners to adapt their virtual reality environment effortlessly. Finally, we discuss possible use cases for virtual reality-embedded physiological sensing.}, keywords = {electrodermal activity, electromyography, physiological computing, physiological sensing, virtual reality} }