An Accelerometer Based Calculator for Visually Impaired People Using Mobile Devices
This addresses the problem of inaccessible touch-screen interfaces for visually impaired people, offering an incremental improvement in human-computer interaction through sensor-based gesture recognition.
The study tackled the accessibility barrier of touch-screen devices for visually impaired people by developing a gesture recognition system using an iPhone's accelerometer, achieving 96.7% accuracy with normal-visioned users and 95.5% with visually impaired users in a calculator application.
Recent trend of touch-screen devices produces an accessibility barrier for visually impaired people. On the other hand, these devices come with sensors such as accelerometer. This calls for new approaches to human computer interface (HCI). In this study, our aim is to find an alternative approach to classify 20 different hand gestures captured by iPhone 3GS's built-in accelerometer and make high accuracy on user-independent classifications using Dynamic Time Warping (DTW) with dynamic warping window sizes. 20 gestures with 1,100 gesture data are collected from 15 normal-visioned people. This data set is used for training. Experiment-1 based on this data set produced an accuracy rate of 96.7~\%. In order for visually impaired people to use the system, a gesture recognition based "talking" calculator is implemented. In Experiment-2, 4 visually impaired end-users used the calculator and obtained 95.5~\% accuracy rate among 17 gestures with 720 gesture data totally. Contributions of the techniques to the end result is also investigated. Dynamic warping window size is found to be the most effective one. The data and the code is available.