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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...

Gait Segmentation of Data Collected by Instrumented Shoes Using a Recurrent Neural Network Classifier.

Physical medicine and rehabilitation clinics of North America
The authors present a Recurrent Neural Network classifier model that segments the walking data recorded with instrumented footwear. The signals from 3 piezoresistive sensors, a 3-axis accelerometer, and Euler angles are used to generate temporal gait...

Can Ensemble Deep Learning Identify People by Their Gait Using Data Collected from Multi-Modal Sensors in Their Insole?

Sensors (Basel, Switzerland)
Gait is a characteristic that has been utilized for identifying individuals. As human gait information is now able to be captured by several types of devices, many studies have proposed biometric identification methods using gait information. As rese...

Combining wearable sensor signals, machine learning and biomechanics to estimate tibial bone force and damage during running.

Human movement science
There are tremendous opportunities to advance science, clinical care, sports performance, and societal health if we are able to develop tools for monitoring musculoskeletal loading (e.g., forces on bones or muscles) outside the lab. While wearable se...

Deep Neural Network for Slip Detection on Ice Surface.

Sensors (Basel, Switzerland)
Slip-induced falls are among the most common causes of major occupational injuries and economic loss in Canada. Identifying the risk factors associated with slip events is key to developing preventive solutions to reduce falls. One factor is the slip...

Indirect Estimation of Vertical Ground Reaction Force from a Body-Mounted INS/GPS Using Machine Learning.

Sensors (Basel, Switzerland)
Vertical ground reaction force (vGRF) can be measured by force plates or instrumented treadmills, but their application is limited to indoor environments. Insoles remove this restriction but suffer from low durability (several hundred hours). Therefo...

Deep learning analysis and age prediction from shoeprints.

Forensic science international
Human gaits are the patterns of limb movements which involve both the upper and lower body parts. These patterns in terms of step rate, gait speed, stance widening, stride, and bipedal forces are influenced by different factors including environmenta...

Deep Learning-Based Optimal Smart Shoes Sensor Selection for Energy Expenditure and Heart Rate Estimation.

Sensors (Basel, Switzerland)
Wearable technologies are known to improve our quality of life. Among the various wearable devices, shoes are non-intrusive, lightweight, and can be used for outdoor activities. In this study, we estimated the energy consumption and heart rate in an ...

Walking-induced exposure of biological particles simulated by a children robot with different shoes on public floors.

Environment international
Inhalation exposure to the resuspended biological particles from public places can cause adverse effects on human health. In this work, carpet dust samples were first collected from twenty example conference and hotel rooms by a vacuum cleaner. A bip...

Deep learning approach to estimate foot pressure distribution in walking with application for a cost-effective insole system.

Journal of neuroengineering and rehabilitation
BACKGROUND: Foot pressure distribution can be used as a quantitative parameter for evaluating anatomical deformity of the foot and for diagnosing and treating pathological gait, falling, and pressure sores in diabetes. The objective of this study was...