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How can a hand rehabilitation glove be designed to best assist patients with hand injuries? 


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A hand rehabilitation glove can be designed to best assist patients with hand injuries by incorporating features such as personalized training modes, real-time monitoring, and feedback on finger movement data . The glove should also prioritize safety by including bending sensors to track finger movement angles and ensure they stay within a safe range . Additionally, the glove can benefit from hybrid actuators that combine silicone flexion actuators with shape memory alloy (SMA) springs to provide both extension and flexion forces . The use of guided bending bellows actuators (GBBAs) made of thermoplastic elastomer (TPE) materials can enhance the range of motion and rehabilitation strength of the finger joints . Furthermore, a soft pneumatic glove with multiple rehabilitation postures and assisted grasping modes can be effective in restoring hand function and motor control ability .

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The paper describes the design of a wearable rehabilitation glove with a bionic actuator that restores hand function and motor control ability lost by stroke patients.
The paper proposes a soft pneumatic glove with multiple rehabilitation postures and assisted grasping modes to assist patients with hand injuries.
The paper discusses the design of a soft pneumatic glove actuated by guided bending bellows actuators (GBBAs) for finger-knuckle rehabilitation. The GBBAs provide force, range of motion, and multi-action coordination for hand dysfunction rehabilitation.
The paper presents a design for a bidirectional soft glove for hand rehabilitation-assistance tasks. It combines a silicone flexion actuator with a shape memory alloy (SMA) spring actuator to provide extension force. The glove was evaluated in trials with stroke patients and showed significant improvement in finger bending angles and increased maximum friction.
The paper describes a soft rehabilitation training glove that provides personalized training modes and real-time monitoring of finger movement data to assist patients with hand injuries.

Related Questions

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