Cloud-Based Control System with Sensing and Actuating Textile-Based IoT Gloves for Telerehabilitation Applications.

Area of Science:

• Robotics
• Rehabilitation Engineering
• Internet of Things (IoT)

Background:

• Remote manipulation devices enhance treatment accessibility.
• Soft robotics offers safe human-robot collaboration in e-health.
• Internet of Things (IoT) integration is key for intelligent rehabilitation systems.

Purpose of the Study:

• To develop a wireless system combining a textile sensor glove with an air-driven soft robotic glove.
• To enable remote hand motion sensing and replication for rehabilitation.
• To create an artificial intelligence-based control system for the rehabilitation glove.

Main Methods:

• A textile glove with capacitive sensors captures hand movements.
• An air-driven soft robotic glove replicates the sensed movements.
• An AI system processes gestures and actuates the pneumatic glove wirelessly via an IoT architecture.

Main Results:

• The system achieved an average response time of 48.4 ms.
• Evaluation confirmed system feasibility, accuracy, and transmission quality.
• The integration of textile gloves into IoT infrastructure was verified.

Conclusions:

• The developed system enables remote motion sensing and actuation for hand rehabilitation.
• This AI-powered soft robotic glove system shows significant potential in e-health and remote therapy.
• The research validates the integration of smart textile gloves within IoT frameworks for advanced rehabilitation solutions.