Title :
Using EMG to anticipate head motion for virtual-environment applications
Author :
Barniv, Yair ; Aguilar, Mario ; Hasanbelliu, Erion
Author_Institution :
Human Inf. Process. Res. Branch, Nat. Aeronaut. & Space Adm., Moffett Field, CA, USA
fDate :
6/1/2005 12:00:00 AM
Abstract :
In virtual environment (VE) applications, where virtual objects are presented in a see-through head-mounted display, virtual images must be continuously stabilized in space in response to user\´s head motion. Time delays in head-motion compensation cause virtual objects to "swim" around instead of being stable in space which results in misalignment errors when overlaying virtual and real objects. Visual update delays are a critical technical obstacle for implementing head-mounted displays in applications such as battlefield simulation/training, telerobotics, and telemedicine. Head motion is currently measurable by a head-mounted 6-degrees-of-freedom inertial measurement unit. However, even given this information, overall VE-system latencies cannot be reduced under about 25 ms. We present a novel approach to eliminating latencies, which is premised on the fact that myoelectric signals from a muscle precede its exertion of force, thereby limb or head acceleration. We thus suggest utilizing neck-muscles\´ myoelectric signals to anticipate head motion. We trained a neural network to map such signals onto equivalent time-advanced inertial outputs. The resulting network can achieve time advances of up to 70 ms.
Keywords :
biomechanics; electromyography; medical signal processing; neural nets; virtual reality; EMG; battlefield simulation; battlefield training; head motion compensation; myoelectric signals; neck muscle; neural network; see-through head-mounted display; telemedicine; telerobotics; time delays; time-advanced inertial outputs; virtual environment; visual update delays; Current measurement; Delay effects; Displays; Electromyography; Head; Measurement units; Motion measurement; Telemedicine; Telerobotics; Virtual environment; Electromyogram; head-mounted display (HMD); neural networks; pattern recognition; virtual environment (VE); Adult; Algorithms; Artificial Intelligence; Computer Simulation; Diagnosis, Computer-Assisted; Electromyography; Environment; Female; Head Movements; Humans; Male; Models, Neurological; Neck Muscles; User-Computer Interface;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2005.848378