Loading...
Please wait, while we are loading the content...
Handwriting Recognition Based on 3D Accelerometer Data by Deep Learning
| Content Provider | MDPI |
|---|---|
| Author | Lopez-Rodriguez, Pedro Avina-Cervantes, Juan Gabriel Contreras-Hernandez, Jose Luis Correa, Rodrigo Ruiz-Pinales, Jose |
| Copyright Year | 2022 |
| Description | Online handwriting recognition has been the subject of research for many years. Despite that, a limited number of practical applications are currently available. The widespread use of devices such as smartphones, smartwatches, and tablets has not been enough to convince the user to use pen-based interfaces. This implies that more research on the pen interface and recognition methods is still necessary. This paper proposes a handwritten character recognition system based on 3D accelerometer signal processing using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM). First, a user wearing an MYO armband on the forearm writes a multi-stroke freestyle character on a touchpad by using the finger or a pen. Next, the 3D accelerometer signals generated during the writing process are fed into a CNN, LSTM, or CNN-LSTM network for recognition. The convolutional backbone obtains spatial features in order to feed an LSTM that extracts short-term temporal information. The system was evaluated on a proprietary dataset of 3D accelerometer data collected from multiple users with an armband device, corresponding to handwritten English lowercase letters (a–z) and digits (0–9) in a freestyle. The results show that the proposed system overcomes other systems from the state of the art by 0.53%. |
| Starting Page | 6707 |
| e-ISSN | 20763417 |
| DOI | 10.3390/app12136707 |
| Journal | Applied Sciences |
| Issue Number | 13 |
| Volume Number | 12 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-07-02 |
| Access Restriction | Open |
| Subject Keyword | Applied Sciences Industrial Engineering 3d Accelerometer Data Handwritten Character Recognition Convolutional Neural Networks (cnn) Long Short-term Memory (lstm) 3d Signal Processing |
| Content Type | Text |
| Resource Type | Article |
