AIMC Topic: Foot

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The Classification of Minor Gait Alterations Using Wearable Sensors and Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper describes how non-invasive wearable sensors can be used in combination with deep learning to classify artificially induced gait alterations without the requirement for a medical professional or gait analyst to be present. This a...

Automatic real-time gait event detection in children using deep neural networks.

PloS one
Annotation of foot-contact and foot-off events is the initial step in post-processing for most quantitative gait analysis workflows. If clean force plate strikes are present, the events can be automatically detected. Otherwise, annotation of gait eve...

Design and Feasibility Study of a Leg-exoskeleton Assistive Wheelchair Robot with Tests on Gluteus Medius Muscles.

Sensors (Basel, Switzerland)
The muscles of the lower limbs directly influence leg motion, therefore, lower limb muscle exercise is important for persons living with lower limb disabilities. This paper presents a medical assistive robot with leg exoskeletons for locomotion and l...

A convolutional neural network Cascade for plantar pressure images registration.

Gait & posture
BACKGROUND: Plantar pressure image (PPI) recorded in high spatial and temporal resolution is very useful in clinical gait analysis. For functional analysis of PPI, image registration is often performed to maximally correlate source image with a templ...

Automatic Classification of Gait Impairments Using a Markerless 2D Video-Based System.

Sensors (Basel, Switzerland)
Systemic disorders affecting an individual can cause gait impairments. Successful acquisition and evaluation of features representing such impairments make it possible to estimate the severity of those disorders, which is important information for mo...

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...