Latest AI and machine learning research in sports medicine for healthcare professionals.
The idea of this Special Issue arose from the technological advances in bionic, robotic, and neural rehabilitation systems and the common need to comprehend in detail how human anatomical structures can be replicated or controlled. Motor control theories, among others, include the generalized control program theory, the equilibrium point hypothesis, or the optimal control approach in which neural ...
The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual segmentation times. Recently, machine learning, and more specifically, convolutional neural networks, have shown potential to alleviate this bottleneck...
PURPOSE: Rehabilitation robots with intent recognition are helping people with dysfunction to enjoy better lives. Many rehabilitation robots with inte...
OBJECTIVE: Robot-assisted gait training (RAGT) is often used as a rehabilitation tool for neurological impairments. The purpose of this study is to in...
BACKGROUND: Few, if any estimates of cost-effectiveness for locomotor training strategies following spinal cord injury (SCI) are available. The purpos...
Some encouraging uses for AI in medicine will lead to potentially novel legal liability issues. Complex algorithms involve an opacity that creates pro...
Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for a...
The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf...
PURPOSE: Robotic gait training is relatively new in the world of pediatric rehabilitation. Preliminary feasibility studies and case reports include st...
This paper presents the development and application of a multiplexed intensity variation-based sensor system for multiplane shape reconstruction. The ...
The COVID-19 pandemic created the need for telerehabilitation development, while Industry 4.0 brought the key technology. As motor therapy often requi...
Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural injury which are crucial targets for therapeutic inte...
BACKGROUND: Robot-assisted training is used as a new rehabilitation training method for the treatment of motor dysfunction in neurological diseases. R...
Accurate segregation of retinal blood vessels network plays a crucial role in clinical assessments, treatments, and rehabilitation process. Owing to t...
The measurement and prediction of breast skin deformation are key research directions in health-related research areas, such as cosmetic and reconstru...
Functional rehabilitation of the hand is a complex and difficult process involving a large number of degrees of freedom (DOFs). Soft wearable hand-reh...
In this study we propose a "hand gesture + face expression" human machine interaction technique, and apply this technique to bedridden rehabilitation ...
Flexible sensing devices (FSDs) fabricated using conductive hydrogels have attracted researchers' extensive enthusiasm in recent years due to their ve...
INTRODUCTION: Improving lower extremity motor function is the focus and difficulty of post-stroke rehabilitation treatment. More recently, robot-assis...
We present a test technique and an accompanying computational framework to obtain data-driven, surrogate constitutive models that capture the response...