Personalized Voice Activated Grasping System for a Robotic Exoskeleton Glove ^★

Area of Science:

• Robotics
• Human-Machine Interaction
• Biomedical Engineering

Background:

• Rehabilitation robotic exoskeletons require intuitive and secure control systems.
• Existing control methods for exoskeleton gloves can be cumbersome and lack personalization.
• Voice command integration presents a potential for enhanced user interaction.

Purpose of the Study:

• To propose a novel human-machine interface (HMI) and electronics system for controlling a rehabilitation robotic exoskeleton glove.
• To develop a system activated by voice commands with real-time biometric authentication.
• To design a modular, plug-and-play electronics system independent of the exoskeleton.

Main Methods:

• Development of a novel human-machine interface (HMI) and electronics system.
• Implementation of voice command recognition and processing.
• Integration of real-time biometric voice authentication.
• Design of a stand-alone, modulated, plug-and-play electronics system.

Main Results:

• The proposed system enables voice activation and biometric authentication for exoskeleton glove control.
• The system performs command recognition and authentication in real-time with limited computing power.
• The modular electronics design is independent of the exoskeleton.
• The personalized voice-activated grasping system demonstrates superior wearability, lower latency, and improved security.

Conclusions:

• The novel HMI and electronics system offers a secure and efficient method for controlling rehabilitation robotic exoskeleton gloves.
• Voice-activated control with biometric authentication enhances user experience and system security.
• The plug-and-play design promotes versatility and ease of integration with existing or future exoskeleton systems.