AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Foot

Showing 71 to 80 of 107 articles

Clear Filters

Gait Estimation from Anatomical Foot Parameters Measured by a Foot Feature Measurement System using a Deep Neural Network Model.

Scientific reports
An accurate and credible measurement of human gait is essential in multiple areas of medical science and rehabilitation. Yet, the methods currently available are not only arduous but also costly. Researchers who investigated the relationship between ...

Acral melanoma detection using a convolutional neural network for dermoscopy images.

PloS one
BACKGROUND/PURPOSE: Acral melanoma is the most common type of melanoma in Asians, and usually results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the h...

Bipedal robotic walking control derived from analysis of human locomotion.

Biological cybernetics
This paper proposes the design of a bipedal robotic controller where the function between the sensory input and motor output is treated as a black box derived from human data. In order to achieve this, we investigated the causal relationship between ...

Analysis of Spatio-Temporal Representations for Robust Footstep Recognition with Deep Residual Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
Human footsteps can provide a unique behavioural pattern for robust biometric systems. We propose spatio-temporal footstep representations from floor-only sensor data in advanced computational models for automatic biometric verification. Our models d...

Reactive balance control in older adults with diabetes.

Gait & posture
Diabetes mellitus is a major health problem for older adults worldwide and could be associated with impaired ability to recover balance after postural disturbances. This study compared reactive balance control in three groups of adults, young (YA), h...

A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.

IEEE transactions on bio-medical engineering
OBJECTIVE: Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Nold...

Continuous sweep versus discrete step protocols for studying effects of wearable robot assistance magnitude.

Journal of neuroengineering and rehabilitation
BACKGROUND: Different groups developed wearable robots for walking assistance, but there is still a need for methods to quickly tune actuation parameters for each robot and population or sometimes even for individual users. Protocols where parameters...

Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks.

Computational and mathematical methods in medicine
Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue prop...

Sensor-Based Gait Parameter Extraction With Deep Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Measurement of stride-related, biomechanical parameters is the common rationale for objective gait impairment scoring. State-of-the-art double-integration approaches to extract these parameters from inertial sensor data are, however, limited in their...

A Novel Elastic Force-Field to Influence Mediolateral Foot Placement During Walking.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Bipedal gait can be stabilized through mechanically-appropriate mediolateral foot placement, although this strategy is disrupted in a subset of neurologically injured individuals with balance deficits. The goal of the present work was to develop a de...