radiomic-feature-selection-using-gradient-loss-deep-neural-network

Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection

Radiomics enables the extraction of quantitative imaging biomarkers from medical images and has become an important tool for computer-aided cancer ...

Global College of Engineering and Technology

Robotic hand design is multifaceted, with the design of robotic thumbs often oversimplified to facilitate ease of manufacture, control, and reliability. Despite the extensive development of robotic hands, the need for a more dexterous and anthropomorphic thumb design remains significant, particularly for applications in prosthetics and rehabilitation robotics, where naturalistic movement and adaptability are essential. This paper addresses this gap by exploring the conception, evolution, and evaluation of a unique biomimetic soft thumb. The thumb plays a vital role in hand function, and its unique range of motion is enabled by the carpometacarpal (CMC) saddle joint. By harnessing the biologically accurate mechanisms of the CMC joint, this research aims to enhance the functionality of tendon-driven robotic hands, offering improved dexterity and adaptability for tasks such as grasping and manipulation. The introduced  is a biomimetic soft robotic thumb that provides a comprehensive range of motion at the thumb's base while ensuring cost efficiency and reduced mechanical complexity. A comparative analysis with existing robotic thumb designs highlights the advancements of the , particularly in terms of range of motion and cost-effectiveness. Additionally, we discuss the long-term durability and maintenance requirements of the soft robotic materials and components used. When subjected to the Kapandji physiotherapy test, the design secured a commendable score of 9 of 10, with 10 representing the highest level of dexterity achievable by a human thumb. The findings affirm that employing biomimetic soft-structured robotic CMC saddle joints is a promising strategy to address the challenges associated with robotic thumb development in robotic hands.

Javeed Hussain

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