PURPOSE: This study develops a newly facial EMG human-computer interface for people with disabilities for controllng the movement of the cursor on a computer screen. METHOD: We access the computer cursor according to different facial muscle activity patterns. In order to exactly detect the muscle activity threshold, this study adopts continuous wavelet transformation to estimate the single motor unit action potentials dynamically. RESULT: The experiment indicates that the accuracy of using the facial mouse is greater than 80%, and this result indicates the feasibility of the proposed system. Moreover, the subject can improve performance of manipulation by repeated training. CONCLUSION: Compared with previous works, the proposed system achieves complete cursor function and provides an inexpensive solution. Although there are still some drawbacks in the facial EMG-based human-computer interface, the facial mouse can provide an alternative among other expensive and complicated assistive technologies.
PURPOSE: This study develops a newly facial EMG human-computer interface for people with disabilities for controllng the movement of the cursor on a computer screen. METHOD: We access the computer cursor according to different facial muscle activity patterns. In order to exactly detect the muscle activity threshold, this study adopts continuous wavelet transformation to estimate the single motor unit action potentials dynamically. RESULT: The experiment indicates that the accuracy of using the facial mouse is greater than 80%, and this result indicates the feasibility of the proposed system. Moreover, the subject can improve performance of manipulation by repeated training. CONCLUSION: Compared with previous works, the proposed system achieves complete cursor function and provides an inexpensive solution. Although there are still some drawbacks in the facial EMG-based human-computer interface, the facial mouse can provide an alternative among other expensive and complicated assistive technologies.
Authors: Matti D Groll; Surbhi Hablani; Jennifer M Vojtech; Cara E Stepp Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2020-07 Impact factor: 3.802
Authors: Carlos G Pinheiro; Eduardo L M Naves; Pierre Pino; Etienne Losson; Adriano O Andrade; Guy Bourhis Journal: Biomed Eng Online Date: 2011-04-20 Impact factor: 2.819
Authors: Wheidima Carneiro de Melo; Eddie Batista de Lima Filho; Waldir Sabino da Silva Júnior Journal: Biomed Eng Online Date: 2016-04-18 Impact factor: 2.819