Clinical Challenges in Soft Robotics
This review explores the exciting field of soft robots for medical applications. It delves into the critical challenges facing their development, including material selection, cytotoxicity, and locomotion limitations. The review then examines promising avenues for overcoming these hurdles and achieving clinical translation.
Kailas Mahipal Malappuram+3 more
wiley +1 more source
Recent Advances in Variable‐Stiffness Robotic Systems Enabled by Phase‐Change Materials
Phase‐change materials (PCMs), such as shape memory alloys, hydrogels, shape memory polymers, liquid crystal elastomers, and low‐melting‐point alloys, are driving advancements in stiffness‐tunable robotic systems across a wide range of applications. This review highlights recent progress in PCM‐enabled robotics, focusing on their underlying mechanisms,
Sukrit Gaira+5 more
wiley +1 more source
MDCT evaluation of dynamic changes in aortic root parameters during the cardiac cycle in patients with aortic regurgitation. [PDF]
Zhang S, Huang T, Lu Y, Guo X, Shang Q.
europepmc +1 more source
Automatic Detection of Atrial Fibrillation from Single-Lead ECG Using Deep Learning of the Cardiac Cycle. [PDF]
Dubatovka A, Buhmann JM.
europepmc +1 more source
Intrinsically Soft Implantable Electronics for Long‐term Biosensing Applications
Intrinsically soft implantable biosensors address the mechanical mismatch of conventional rigid implants, improving biocompatibility and stability. This review explores soft encapsulation matrices, stretchable conductors, implantation strategies, and chronic fixation techniques.
Su Hyeon Lee+5 more
wiley +1 more source
Cardiac cycle modulates alpha and beta suppression during motor imagery. [PDF]
Lai G+4 more
europepmc +1 more source
A Fluid-Structure Interaction Study of Different Bicuspid Aortic Valve Phenotypes Throughout the Cardiac Cycle. [PDF]
Yan W, Li J, Wang W, Wei L, Wang S.
europepmc +1 more source
This review examines recent advancements in multimodal bioelectronics, emphasizing machine learning integration to enhance functionality. The application of machine learning methodologies improving biosignal processing, device adaptability, and diagnostic accuracy is discussed to introduce Machine Learning enhanced bioelectronics as a pathway toward ...
Myoungjae Oh+11 more
wiley +1 more source
Abdominal aortic aneurysm classification based on dynamic intraluminal thrombus analysis during cardiac cycle. [PDF]
Guest A+4 more
europepmc +1 more source