Dear Impossible Readers,
Somehow, I always seem to forget to have a pen and paper with me, and I end up borrowing one quickly and scribbling all over my hand. And when that space is not enough, well, I am literally an arm’s length away. There are only so many ways to write. We have been writing on anything, from stone tablets to parchment and papyrus, penned with quills. Writing has always evolved with technology. The printing press brought words to the masses, the mechanical typewriter made writing faster and more uniform, and digital keyboards and tablets transformed how we draft, edit, and share ideas. Writing is no longer limited by paper.
What if we could write inklessly and surfacelessly all at once? I know, I know, those are not real words, but you got my point, right? No more, which tablet size would be good? Should I go for an iPad or one of these Androids? How about neither? Even with three monitors, still, I end up writing something on a piece of paper. Perhaps I am just old-fashioned.
But that feeling of holding a very nice, slick pen… Writing the words down by hand almost feels like second nature. Instead of settling for a digital writing surface, which would require an additional digital pen, I think I will settle for a pen that just allows me to write on pretty much anything I want, whenever I want.
How do you actually see what you write? Most of these pens work with an app, displaying your strokes in real time on a smartphone, tablet, or computer. Some use projection technology, casting your writing onto a nearby surface. Others experiment with haptic feedback, simulating the feel of a pen on paper while your text appears digitally. In the future, augmented reality (AR) overlays could allow your notes to float right above whatever surface you write on. Your words will be visible, just perfectly ink- and surface-free.
Writing on uneven surfaces can be a challenging task. Accuracy is key. At the same time, the pen should feel natural while being durable with a long-lasting battery life. Smart pens combine motion sensors, accelerometers, and gyroscopes to track every movement. AI-powered handwriting recognition cleans up your strokes and converts them into editable text. Some pens add projection or haptic systems to make writing feel natural. AI and engineering bridge the gap between the analogue pleasure of writing and the convenience of digital storage.
Inklessly, surfacelessly, and intelligently,
Yours Possibly
Further Reading
Alemayoh, T.T., Shintani, M., Lee, J.H. and Okamoto, S., 2022. Deep-learning-based character recognition from handwriting motion data captured using IMU and force sensors. Sensors, 22(20), p.7840.
Balaji, A.N. and Peh, L.S., 2021, May. AI-on-Skin: Enabling on-body AI inference for wearable artificial skin interfaces. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-7).
Cho, Y., Bianchi, A., Marquardt, N. and Bianchi-Berthouze, N., 2016, October. RealPen: Providing realism in handwriting tasks on touch surfaces using auditory-tactile feedback. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (pp. 195-205).
Ji, X., Wang, M., Wang, W. and Liu, Q., 2025. Enhancing small object detection for HCI: BRA-YOLO algorithm with RealSense 3D trajectory tracking. Franklin Open, p.100325.
Lee, J.C., Dietz, P.H., Leigh, D., Yerazunis, W.S. and Hudson, S.E., 2004, October. Haptic pen: a tactile feedback stylus for touch screens. In Proceedings of the 17th annual ACM symposium on User interface software and technology (pp. 291-294).
Li, J., Hamann, T., Barth, J., Kaempf, P., Zanca, D. and Eskofier, B., 2025. Robust and Efficient Writer-Independent IMU-Based Handwriting Recognization. arXiv preprint arXiv:2502.20954.
Lüthi, G., Fender, A.R. and Holz, C., 2022, October. DeltaPen: A device with integrated high-precision translation and rotation sensing on passive surfaces. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (pp. 1-12).
Ott, F., Wehbi, M., Hamann, T., Barth, J., Eskofier, B. and Mutschler, C., 2020. The onhw dataset: Online handwriting recognition from imu-enhanced ballpoint pens with machine learning. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(3), pp.1-20.
Wang, F., Song, D., Zhou, C., Li, X., Huang, Y., Xu, W., Liu, G. and Zhou, S., 2024. MXene-based skin-like hydrogel sensor and machine learning-assisted handwriting recognition. ACS Applied Materials & Interfaces, 16(31), pp.41583-41595.
Wehbi, M., Hamann, T., Barth, J., Kaempf, P., Zanca, D. and Eskofier, B., 2021, September. Towards an imu-based pen online handwriting recognizer. In International conference on document analysis and recognition (pp. 289-303). Cham: Springer International Publishing.
Xiang, S., Tang, J., Yang, L., Guo, Y., Zhao, Z. and Zhang, W., 2022. Deep learning-enabled real-time personal handwriting electronic skin with dynamic thermoregulating ability. npj Flexible Electronics, 6(1), p.59.

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