AI Medical Compendium Topic

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Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance.

Bioinspiration & biomimetics
Many wearable lower-limb robots for walking assistance have been developed in recent years. However, it remains unclear how they can be commanded in an intuitive and efficient way by their user. In particular, providing robotic assistance to neurolog...

Classification of Computed Tomography Images in Different Slice Positions Using Deep Learning.

Journal of healthcare engineering
This study aimed at elucidating the relationship between the number of computed tomography (CT) images, including data concerning the accuracy of models and contrast enhancement for classifying the images. We enrolled 1539 patients who underwent cont...

Robotic Spine Exoskeleton (RoSE): Characterizing the 3-D Stiffness of the Human Torso in the Treatment of Spine Deformity.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Spine deformity is typically treated with a brace that fits around the torso and hips to correct the abnormal curve of the spine. While bracing has been shown to curtail progression of abnormal spine curves, current braces impose several limitations ...

Wheelchair propulsion: Force orientation and amplitude prediction with Recurrent Neural Network.

Journal of biomechanics
The aim of this study was to use Recurrent Neural Network (RNN) to predict the orientation and amplitude of the applied force during the push phase of manual wheelchair propulsion. Trunk and the right-upper limb kinematics data were assessed with an ...

Automatically Evaluating Balance: A Machine Learning Approach.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Compared to in-clinic balance training, in-home training is not as effective. This is, in part, due to the lack of feedback from physical therapists (PTs). In this paper, we analyze the feasibility of using trunk sway data and machine learning (ML) t...

Decentralized control with cross-coupled sensory feedback between body and limbs in sprawling locomotion.

Bioinspiration & biomimetics
Quadrupeds achieve rapid and highly adaptive locomotion owing to the coordination between their legs and other body parts such as their trunk, head, and tail, i.e. body-limb coordination. Therefore, a better understanding of the mechanism underlying ...

The detection of age groups by dynamic gait outcomes using machine learning approaches.

Scientific reports
Prevalence of gait impairments increases with age and is associated with mobility decline, fall risk and loss of independence. For geriatric patients, the risk of having gait disorders is even higher. Consequently, gait assessment in the clinics has ...

A neural network method to predict task- and step-specific ground reaction force magnitudes from trunk accelerations during running activities.

Medical engineering & physics
Prediction of ground reaction force (GRF) magnitudes during running-based sports has several important applications, including optimal load prescription and injury prevention in athletes. Existing methods typically require information from multiple b...

Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach.

Sensors (Basel, Switzerland)
Nonspecific low back pain (NSLBP) constitutes a critical health challenge that impacts millions of people worldwide with devastating health and socioeconomic consequences. In today's clinical settings, practitioners continue to follow conventional gu...

Quantifying trunk neuromuscular control using seated balancing and stability threshold.

Journal of biomechanics
Performance during seated balancing is often used to assess trunk neuromuscular control, including evaluating impairments in back pain populations. Balancing in less challenging environments allows for flexibility in control, which may not depend on ...