Back to Finger-Writing: Fingertip Writing Technology Based on Pressure Sensing

Gaddi Blumrosen, Katsuyuki Sakuma, John Jeremy Rice, John Knickerbocker

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Handwriting was since the start of the history, a higher expression of human skills, and was used for documentation of experiences, and for communication. Existing writing technology require a writing tool, like a pen, and a dedicated writing surface, like paper, or more recently an electronic tablet. These accessories of writing, of writing tool and service, are not available in many daily life situations. Furthermore, the writing accessories, are not natural, in many cases are not ergonomic, and thus can cause fatigue, and in extreme cases contribute to muscular and neurological diseases. In this work, we suggest to step back in history and step forward in technology, and to create, for the first time, an alternate writing solution without any accessories, using one own finger as writing tool, and write on almost any surface. For this, we used directional pressure sensors attached to the fingernail. Changes in the pressure induced on the fingertip in different directions while writing, are projected to the fingernail, and then assessed as a voltage pattern by the sensor. Decoding the pattern, can reveal symbols like letters, punctuations, and writing commands. In this paper, we describe the new pressure sensing modality and tailor processing methods. We tested the new technology on two subjects having different writing patterns while writing alphabet and sentences on different surfaces. We reached letter detection of over 80% while writing on a table, and the word detection rate, was near 70%, after applying the correction algorithm include language priors. The results of this work can revolutionize the way people write and communicate using more convenient, and more approachable, finger-tip writing.

Original languageEnglish
Article number8995580
Pages (from-to)35455-35468
Number of pages14
JournalIEEE Access
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2013 IEEE.


  • Handwriting recognition
  • human machine interface
  • natural language processing


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