Wireless Smartphone Control using Electromyography and Automated Gesture Recognition
| Autor: | Matthew L. Johnston, Hayden Bialek, Jacob Dawes, Makenzie Brian |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Gestures medicine.diagnostic_test Electromyography Computer science business.industry Control (management) Wearable computer 02 engineering and technology Pattern Recognition Automated 020901 industrial engineering & automation Gesture recognition Pattern recognition (psychology) medicine Humans Wireless Computer vision Smartphone Artificial intelligence business Wireless Technology Algorithms Gesture |
| Zdroj: | EMBC |
| DOI: | 10.1109/embc.2018.8513640 |
| Popis: | In this paper, a wearable, wireless system is demonstrated using electromyography (EMG) signals for realtime control of a smartphone device. The system allows gesturebased control of a smartphone or tablet computer without physical contact, direct line of sight, or significant movement. Additionally, automated gesture detection is shifted to the smartphone, eliminating the need for robust computing hardware. The electronic system and gesture prediction algorithm are described, and measured results are presented and for multiple users. The system demonstrates a maximum true positive detection rate of 92% for a trained user, using three distinct hand gestures. The EMG-based detection system serves as a proof-of-concept for providing wireless, gesture-based control of computer interfaces using low-cost consumer hardware. |
| Databáze: | OpenAIRE |
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