AI Medical Compendium Topic

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

Shoes

Showing 11 to 20 of 34 articles

Clear Filters

DeepBBWAE-Net: A CNN-RNN Based Deep SuperLearner for Estimating Lower Extremity Sagittal Plane Joint Kinematics Using Shoe-Mounted IMU Sensors in Daily Living.

IEEE journal of biomedical and health informatics
Measurement of human body movement is an essential step in biomechanical analysis. The current standard for human motion capture systems uses infrared cameras to track reflective markers placed on a subject. While these systems can accurately track j...

Design and Implementation of a Smart Insole System to Measure Plantar Pressure and Temperature.

Sensors (Basel, Switzerland)
An intelligent insole system may monitor the individual's foot pressure and temperature in real-time from the comfort of their home, which can help capture foot problems in their earliest stages. Constant monitoring for foot complications is essentia...

Prediction of knee adduction moment using innovative instrumented insole and deep learning neural networks in healthy female individuals.

The Knee
BACKGROUND: The knee adduction moment, a biomechanical risk factor of knee osteoarthritis, is typically measured in a gait laboratory with expensive equipment and inverse dynamics modeling software. We aimed to develop a framework for a portable knee...

Deep Neural Network for the Detections of Fall and Physical Activities Using Foot Pressures and Inertial Sensing.

Sensors (Basel, Switzerland)
Fall detection and physical activity (PA) classification are important health maintenance issues for the elderly and people with mobility dysfunctions. The literature review showed that most studies concerning fall detection and PA classification add...

A Deep Learning Model for 3D Ground Reaction Force Estimation Using Shoes with Three Uniaxial Load Cells.

Sensors (Basel, Switzerland)
Ground reaction force (GRF) is essential for estimating muscle strength and joint torque in inverse dynamic analysis. Typically, it is measured using a force plate. However, force plates have spatial limitations, and studies of gaits involve numerous...

Comparison of four machine learning algorithms for a pre-impact fall detection system.

Medical & biological engineering & computing
In recent years, real-time health monitoring using wearable sensors has been an active area of research. This paper presents an efficient and low-cost fall detection system based on a pair of shoes equipped with inertial sensors and plantar pressure ...

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: The relationship between physical function, musculoskeletal disorders and sarcopenia is intricate. Current physical function tests, such as the gait speed test and the chair stand test, have limitations in eliminating subjective influence...

Machine learning prediction of footwear slip resistance on glycerol-contaminated surfaces: A pilot study.

Applied ergonomics
Slippery surfaces due to oil spills pose a significant risk in various environments, including industrial workplaces, kitchens, garages, and outdoor areas. These situations can lead to accidents and falls, resulting in injuries that range from minor ...

Predicting Musculoskeletal Loading at Common Running Injury Locations Using Machine Learning and Instrumented Insoles.

Medicine and science in sports and exercise
INTRODUCTION: Wearables have the potential to provide accurate estimates of tissue loads at common running injury locations. Here we investigate the accuracy by which commercially available instrumented insoles (ARION; ATO-GEAR, Eindhoven, The Nether...

Calibrating Low-Cost Smart Insole Sensors with Recurrent Neural Networks for Accurate Prediction of Center of Pressure.

Sensors (Basel, Switzerland)
This paper proposes a scheme for predicting ground reaction force (GRF) and center of pressure (CoP) using low-cost FSR sensors. GRF and CoP data are commonly collected from smart insoles to analyze the wearer's gait and diagnose balance issues. This...