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We propose a new way of eyes-free interaction for wearables. It is based on the user's proprioceptive sense, i.e., rather than seeing, hearing, or feeling an outside stimulus, users feel the pose of their own body.We have implemented a wearable device called Pose-IO that offers input and output based on proprioception. Users communicate with Pose-IO through the pose of their wrists. Users enter information by performing an input gesture by flexing their wrist, which the device senses using a 3-axis accelerometer. Users receive output from Pose-IO by finding their wrist posed in an output gesture, which Pose-IO actuates using electrical muscle stimulation. This mechanism allows users to interact with Pose-IO without visual or auditory senses, but through the proprioceptive sense alone.We developed three simple applications that demonstrate symmetric proprioceptive interaction, where input and output occur through the same limb, as well as asymmetric interaction, where input and output occur through different limbs. In a first user study, participants using a symmetric proprioceptive interface re-entered poses received from Pose-IO with an average accuracy of 5.8° despite the minimal bandwidth offered by the device. In a second, exploratory study, we investigated participants' emotional response to asymmetric proprioceptive interaction and the concept of the user's body serving as interface. Participants reported to enjoy the experience (mean= 4.6 out of 5).

We present an automatic tool to approximate curved geometries with piece-wise developable surfaces. At the center of our work is an algorithm that wraps a given 3D input surface with multiple developable patches, each modeled as a discrete orthogonal geodesic net. Our algorithm features a global optimization routine for effectively finding the placement of the developable patches. After wrapping the mesh, we use these patches and a non-linear projection step to generate a surface that approximates the original input, but is also amendable to simple and efficient fabrication techniques thanks to being piecewise developable. Our algorithm allows users to steer the trade-off between approximation power and the number of developable patches used. We demonstrate the effectiveness of our approach on a range of 3D shapes. Compared to previous approaches, our results exhibit a smaller or comparable error with fewer patches to fabricate.