Systems, methods, apparatuses and devices for detecting facial expression and for tracking movement and location in at least one of a virtual and augmented reality system
Tej Tadi, Lausanne (CH); Robert Leeb, Lausanne (CH); Nicolas Bourdaud, Lausanne (CH); Leandre Bolomey, Lausanne (CH); Gangadhar Garipelli, Lausanne (CH); Skander Mensi, Lausanne (CH); Julien Pilet, Lausanne (CH); Dat Ngo, Lausanne (CH); Yann Lebrun, Lausanne (CH); Arthur Giroux, Lausanne (CH); Sylvain Cardin, Lausanne (CH); and Nicolas Merlini, Lausanne (CH)
Assigned to MINDMAZE GROUP SA, Lausanne. (CH)
Filed by MINDMAZE GROUP SA, Lausanne (CH)
Filed on Jan. 29, 2021, as Appl. No. 17/163,327.
Application 17/163,327 is a continuation of application No. 16/678,163, filed on Nov. 8, 2019, abandoned.
Application 16/678,163 is a continuation of application No. 16/261,693, filed on Jan. 30, 2019, granted, now 10,521,014, issued on Dec. 31, 2019.
Application 16/261,693 is a continuation in part of application No. PCT/IB2018/000524, filed on Jan. 19, 2019.
Claims priority of provisional application 62/481,760, filed on Apr. 5, 2017.
Claims priority of provisional application 62/448,373, filed on Jan. 19, 2017.
Prior Publication US 2022/0011864 A1, Jan. 13, 2022 Prior Publication US 2023/0367389 A9, Nov. 16, 2023
1. A facial muscle activity determination system for determining a underlying facial activity of a user comprising: an apparatus comprising a plurality of EMG (electromyography) electrodes configured for contact with the face of the user, said apparatus comprising an electrode interface; a mask which contacts an upper portion of the face of the user, said mask including an electrode plate attached to at least eight EMG electrodes and one reference electrode such that said EMG electrodes contact said upper portion of the face of the user, wherein said electrode interface is operatively coupled to said EMG electrodes and a hardware processor, said electrode interface for providing said EMG signals from said EMG electrodes to said hardware processor; and a computational device configured to receive a plurality of EMG signals from said EMG electrodes, and comprising said hardware processor and a memory having instructions thereon operable by said hardware processor to cause the computational device to: receive said EMG signals; process said EMG signals to form processed EMG signals and to determine at least one feature of said EMG signals in said processed EMG signals; determine a roughness of said processed EMG signals according to a defined window, said determining a roughness comprising calculating an EMG-dipole and determining a movement of said processed EMG signals according to said EMG-dipole, and performing a nonlinear transformation of said processed EMG signals to enhance high-frequency contents of said processed EMG signals; classify, using a classifier, an underlying muscle capability of said user according to said at least one feature of said EMG signals and according to said roughness.
