Smartphone Sensor Dataset for Online Reading Analysis

Citation Author(s):
Dr Vishwanath Karad MIT World Peace University
Dr Vishwanath Karad MIT World Peace University
Submitted by:
Priyanka Bhatele
Last updated:
Fri, 05/17/2024 - 10:50
Data Format:
Research Article Link:
0 ratings - Please login to submit your rating.


Popularity of smartphones also popularized, reading content using smartphones. Reading using smartphones quite differs from reading using desktop system. Mouse and Keyboard are the peripherals associated with the reading in desktop systems. Study of the handling of such devices has led to provide implicit feedback of the content read. Similar study in smartphones to get implicit feedback remains to be a huge gap. Reading using smartphones involves screen gestures like pinch to zoom, tap, scroll, orientation change and screen capture. User reading behavior and intent can be done by screen gestures.  Smartphones have sensors like gyroscope and accelerometer that continuously capture data without permissions from the users. To analyze screen gestures, a dataset has been created. Dataset is organized into accelerometer and gyroscope folders. This dataset can act as an input to train, test and validate, machine learning models to analyze smartphone reading behavior and user intent.


The dataset and its manuscript are submitted together in this submission


Dataset Manuscript

Submitted by Priyanka Bhatele on Mon, 04/22/2024 - 06:50