Kuno, WakabaSugiura, YutaAsano, NaoKawai, WataruSugimoto, MakiRobert W. Lindeman and Gerd Bruder and Daisuke Iwai2017-11-212017-11-212017978-3-03868-038-31727-530Xhttps://doi.org/10.2312/egve.20171362https://diglib.eg.org:443/handle/10.2312/egve20171362In this research, we propose a method for reconstructing hand posture by measuring the deformation of the back of the hand with a wearable device. The deformation of skin on the back of the hand can be measured by using several photo-reflective sensors attached to a wearable device. In the learning phase, our method constructs a regression model by using the data on hand posture captured by a depth camera and data on the skin deformation of the back of the hand captured by several photoreflective sensors. In the estimation phase, by using this regression model, the posture of the hand is reconstructed from the data of the photo-reflective sensors in real-time. The posture of fingers can be estimated without hindering the natural movement of the fingers since the deformation of the back of the hand is measured without directly measuring the position of the fingers. This method can be used by users to manipulate information in a virtual environment with their fingers. We conducted an experiment to evaluate the accuracy of reconstructing hand posture with the proposed system.Humancentered computingInteraction devices10.2312/egve.20171362221-228