dc.contributor.author	Guo, Yunfei	en
dc.contributor.committeechair	Ben-Tzvi, Pinhas	en
dc.contributor.committeemember	Zhu, Yunhui	en
dc.contributor.committeemember	Gerdes, Ryan M.	en
dc.contributor.department	Electrical and Computer Engineering	en
dc.date.accessioned	2021-01-06T09:00:31Z	en
dc.date.available	2021-01-06T09:00:31Z	en
dc.date.issued	2021-01-05	en
dc.description.abstract	Controlling an exoskeleton glove with a highly efficient human-machine interface (HMI), while accurately applying force to each joint remains a hot topic. This paper proposes a fast, secure, accurate, and portable solution to control an exoskeleton glove. This state of the art solution includes both hardware and software components. The exoskeleton glove uses a modified serial elastic actuator (SEA) to achieve accurate force sensing. A portable electronic system is designed based on the SEA to allow force measurement, force application, slip detection, cloud computing, and a power supply to provide over 2 hours of continuous usage. A voice-control-based HMI referred to as the integrated trigger-word configurable voice activation and speaker verification system (CVASV), is integrated into a robotic exoskeleton glove to perform high-level control. The CVASV HMI is designed for embedded systems with limited computing power to perform voice-activation and voice-verification simultaneously. The system uses MobileNet as the feature extractor to reduce computational cost. The HMI is tuned to allow better performance in grasping daily objects. This study focuses on applying the CVASV HMI to the exoskeleton glove to perform a stable grasp with force-control and slip-detection using SEA based exoskeleton glove. This research found that using MobileNet as the speaker verification neural network can increase the speed of processing while maintaining similar verification accuracy.	en
dc.description.abstractgeneral	The robotic exoskeleton glove used in this research is designed to help patients with hand disabilities. This thesis proposes a voice-activated grasping system to control the exoskeleton glove. Here, the user can use a self-defined keyword to activate the exoskeleton and use voice to control the exoskeleton. The voice command system can distinguish between different users' voices, thereby improving the safety of the glove control. A smartphone is used to process the voice commands and send them to an onboard computer on the exoskeleton glove. The exoskeleton glove then accurately applies force to each fingertip using a force feedback actuator.This study focused on designing a state of the art human machine interface to control an exoskeleton glove and perform an accurate and stable grasp.	en
dc.description.degree	Master of Science	en
dc.format.medium	ETD	en
dc.identifier.other	vt_gsexam:28443	en
dc.identifier.uri	http://hdl.handle.net/10919/101751	en
dc.publisher	Virginia Tech	en
dc.rights	In Copyright	en
dc.rights.uri	http://rightsstatements.org/vocab/InC/1.0/	en
dc.subject	Exoskeleton glove	en
dc.subject	Human Machine Interfacing	en
dc.subject	Embedded System	en
dc.subject	Voice activation	en
dc.subject	Speaker Verification	en
dc.title	Personalized Voice Activated Grasping System for a Robotic Exoskeleton Glove	en
dc.type	Thesis	en
thesis.degree.discipline	Computer Engineering	en
thesis.degree.grantor	Virginia Polytechnic Institute and State University	en
thesis.degree.level	masters	en
thesis.degree.name	Master of Science	en

Personalized Voice Activated Grasping System for a Robotic Exoskeleton Glove

Files

Original bundle

Collections