%0 Journal Article %1 10460576 %A Kern, Florian %A Tschanter, Jonathan %A Latoschik, Marc Erich %D 2024 %J IEEE Transactions on Visualization and Computer Graphics %K myown vilearn xrhub %P 1-11 %R 10.1109/TVCG.2024.3372124 %T Handwriting for Text Input and the Impact of XR Displays, Surface Alignments, and Sentence Complexities %U https://ieeexplore.ieee.org/document/10460576 %X Text input is desirable across various eXtended Reality (XR) use cases and is particularly crucial for knowledge and office work. This article compares handwriting text input between Virtual Reality (VR) and Video See-Through Augmented Reality (VST AR), facilitated by physically aligned and mid-air surfaces when writing simple and complex sentences. In a 2x2x2 experimental design, 72 participants performed two ten-minute handwriting sessions, each including ten simple and ten complex sentences representing text input in real-world scenarios. Our developed handwriting application supports different XR displays, surface alignments, and handwriting recognition based on digital ink. We evaluated usability, user experience, task load, text input performance, and handwriting style. Our results indicate high usability with a successful transfer of handwriting skills to the virtual domain. XR displays and surface alignments did not impact text input speed and error rate. However, sentence complexities did, with participants achieving higher input speeds and fewer errors for simple sentences (17.85 WPM, 0.51% MSD ER) than complex sentences (15.07 WPM, 1.74% MSD ER). Handwriting on physically aligned surfaces showed higher learnability and lower physical demand, making them more suitable for prolonged handwriting sessions. Handwriting on mid-air surfaces yielded higher novelty and stimulation ratings, which might diminish with more experience. Surface alignments and sentence complexities significantly affected handwriting style, leading to enlarged and more connected cursive writing in both mid-air and for simple sentences. The study also demonstrated the benefits of using XR controllers in a pen-like posture to mimic styluses and pressure-sensitive tips on physical surfaces for input detection. We additionally provide a phrase set of simple and complex sentences as a basis for future text input studies, which can be expanded and adapted.

@article{10460576, abstract = {Text input is desirable across various eXtended Reality (XR) use cases and is particularly crucial for knowledge and office work. This article compares handwriting text input between Virtual Reality (VR) and Video See-Through Augmented Reality (VST AR), facilitated by physically aligned and mid-air surfaces when writing simple and complex sentences. In a 2x2x2 experimental design, 72 participants performed two ten-minute handwriting sessions, each including ten simple and ten complex sentences representing text input in real-world scenarios. Our developed handwriting application supports different XR displays, surface alignments, and handwriting recognition based on digital ink. We evaluated usability, user experience, task load, text input performance, and handwriting style. Our results indicate high usability with a successful transfer of handwriting skills to the virtual domain. XR displays and surface alignments did not impact text input speed and error rate. However, sentence complexities did, with participants achieving higher input speeds and fewer errors for simple sentences (17.85 WPM, 0.51% MSD ER) than complex sentences (15.07 WPM, 1.74% MSD ER). Handwriting on physically aligned surfaces showed higher learnability and lower physical demand, making them more suitable for prolonged handwriting sessions. Handwriting on mid-air surfaces yielded higher novelty and stimulation ratings, which might diminish with more experience. Surface alignments and sentence complexities significantly affected handwriting style, leading to enlarged and more connected cursive writing in both mid-air and for simple sentences. The study also demonstrated the benefits of using XR controllers in a pen-like posture to mimic styluses and pressure-sensitive tips on physical surfaces for input detection. We additionally provide a phrase set of simple and complex sentences as a basis for future text input studies, which can be expanded and adapted.}, added-at = {2024-03-13T07:02:52.000+0100}, author = {Kern, Florian and Tschanter, Jonathan and Latoschik, Marc Erich}, biburl = {https://www.bibsonomy.org/bibtex/229db42bd53abe81c6bd29b0452d32ddd/hci-uwb}, doi = {10.1109/TVCG.2024.3372124}, interhash = {7cd0ba25f348b55bb3ef06a0d0700d6f}, intrahash = {29db42bd53abe81c6bd29b0452d32ddd}, issn = {1941-0506}, journal = {IEEE Transactions on Visualization and Computer Graphics}, keywords = {myown vilearn xrhub}, pages = {1-11}, timestamp = {2024-03-13T07:04:22.000+0100}, title = {Handwriting for Text Input and the Impact of XR Displays, Surface Alignments, and Sentence Complexities}, url = {https://ieeexplore.ieee.org/document/10460576}, year = 2024 }