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Multi Stage based Time Series Analysis of User Activity on Touch Sensitive Surfaces in Highly Noise Susceptible Environments

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 105 - Number 16
Year of Publication: 2014
Sandeep Vanga
Sachin Jaganade

Sandeep Vanga and Sachin Jaganade. Article: Multi Stage based Time Series Analysis of User Activity on Touch Sensitive Surfaces in Highly Noise Susceptible Environments. International Journal of Computer Applications 105(16):23-31, November 2014. Full text available. BibTeX

	author = {Sandeep Vanga and Sachin Jaganade},
	title = {Article: Multi Stage based Time Series Analysis of User Activity on Touch Sensitive Surfaces in Highly Noise Susceptible Environments},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {105},
	number = {16},
	pages = {23-31},
	month = {November},
	note = {Full text available}


This article proposes a multistage framework for time series analysis of user activity on touch sensitive surfaces in noisy environments. Here multiple methods are put together in multi stage framework; including moving average, moving median, linear regression, kernel density estimation, partial differential equations and Kalman filter. The proposed three stage filter consisting of partial differential equation based denoising, Kalman filter and moving average method provides ~25% better noise reduction than other methods according to Mean Squared Error (MSE) criterion in highly noise susceptible environments. Apart from synthetic data, we also obtained real world data like hand writing, finger/stylus drags etc. on touch screens in the presence of high noise such as unauthorized charger noise or display noise and validated our algorithms. Furthermore, the proposed algorithm performs qualitatively better than the existing solutions for touch panels of the high end hand held devices available in the consumer electronics market qualitatively.


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