Motion Tracking Pen


  • Chahak Tyagi Student, Department of Electronics and Communication Engineering, JSS Academy of Technical Education, Noida.


Arduino, Machine Learning, PyGARL, Python, MPU 6050


This paper aims at creating a working prototype for a Smart Pen that can be used for storing handwritten text and display it on your computer
screens. We have provided it in English language, but it is not language specific, you can customize it and train it according to your ease.
Using Machine Learning algorithms and arduino, the stores movement is analyzed and matched with the best suited trained model to give
the desired result. The movement will be recorded and stored. With Python, the movement also can be displayed on your device’s screen.
With a small and convenient button, the recording function can start and finish very flexibly. Users also can attach our device on other things to
track their movements, too. Therefore, our device provides a workable solution for handwriting tracking, movement tracking etc.



LeapFrog: OnlineLeapfrog.

Berque D, Bonebright T, Whitesell M. Using pen-based computers across the computer science curriculum. In: ACM SIGCSE Bulletin 2004; 36: 61-65. ACM.

Miura M, Kunifuji S, Shizuki B et al. Airtransnote: augmented class- rooms with digital pen devices and rfid tags. In: IEEE International Workshop on Wireless

and Mobile Technologies in Education 2005 (WMTE2005) IEEE 2005; 56-58.

Sugihara T, Miura T, Miura M et al. Examining the effects of the simultaneous display of students’ responses using a digital pen system on class activity-a case study of an early elementary school in Japan. In: 2010 IEEE 10th International Conference on Advanced Learning Technologies (ICALT) IEEE 2010; 294-296.

Miura M, Sugihara T, Kunifuji S. Improvement of digital pen learning system for daily use in classrooms. Educ.Technol. Res. 2011; 34: 49-57. 6. Sellen A, Harper R. The Myth of the Paperless Office.MIT Press.

Mueller PA, Oppenheimer DM. The pen is mightier than the keyboard advantages of longhand over 7 laptop note taking. Psychological science 2003;


Ozok AA, Benson D, Chakraborty J et al. A comparative study between tablet and laptop pcs: user satisfaction and preferences. Int. J. Hum.-Comput. Interact. 2008 ;

(3): 329-352. Cross Ref Google Scholar

James WB, Gardner DL. Learning styles: implications for distance learning. New Dir. Adult Continuing Educ.1995; (67): 19-31. CrossRef Google Scholar https://doi.


Livescribe: Echo smartpen.

Anoto: The Pattern. (2014)


Ana Belén Lago Vilariño and Iván Pretel García. An E-Learning Platform for Integrated Management of

Documents Based on Automatic Digitization.

Da Silva & Da Rocha. InkBlog: A Pen-Based Blog Tool for e-Learning Environments.

Benlloch J, Buendía F, Cano J. Tablet PC-based learning approach on a first-year computer engineering course. Proceedings of the 9th IEEE International Conference on Advanced Learning Technologies, Riga, Latvia 2009; 86-87. doi: 10.1109/ICALT.2009.155