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Hands-Free Human-Computer Interface Based on Facial Myoelectric Pattern Recognition
Conclusion A facial movement-machine interface was developed in this study in order to help users with limited hand function manipulate electronic devices. Facial movements were detected using four EMG sensors, and five movement patterns were classified using myoelectric pattern recognition algorithms. The results from 10 able-bodied subjects show that facial movements can be detected and classified at high accuracies. The pattern-based continuous mapping between facial movements and cursor actions achieved high performance in both a typing task and a drawing task. Ethics Statement This study was approved by the Committ...
Source: Frontiers in Neurology - April 29, 2019 Category: Neurology Source Type: research