AIMC Topic: Walking

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Unsupervised learning for real-time and continuous gait phase detection.

PloS one Nov 1, 2024
Individuals with lower limb impairment after a stroke or spinal cord injury require rehabilitation, but traditional methods can be challenging for both patients and therapists. Robotic systems have been developed to help; however, they currently cann...
Female Gait Fuzzy Logic Adult Humans Unsupervised Machine Learning Neural Networks, Computer Male Walking Algorithms
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Nature's All-in-One: Multitasking Robots Inspired by Dung Beetles.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Oct 30, 2024
Dung beetles impressively coordinate their 6 legs to effectively roll large dung balls. They can also roll dung balls varying in the weight on different terrains. The mechanisms underlying how their motor commands are adapted to walk and simultaneous...
Walking Behavior, Animal Locomotion Coleoptera Biomechanical Phenomena Animals Robotics
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Multi-Activity Step Counting Algorithm Using Deep Learning Foot Flat Detection with an IMU Inside the Sole of a Shoe.

Sensors (Basel, Switzerland) Oct 29, 2024
Step counting devices were previously shown to be efficient in a variety of applications such as athletic training or patient's care programs. Various sensor placements and algorithms were previously experimented, with a best mean absolute percentage...
Running Accelerometry Foot Shoes Middle Aged Deep Learning Walking Humans Algorithms Adult Male Female Young Adult
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Convolutional neural network based detection of early stage Parkinson's disease using the six minute walk test.

Scientific reports Sep 30, 2024
The heterogeneity of Parkinson's disease (PD) presents considerable challenges for accurate diagnosis, particularly during early-stage disease, when the symptoms may be extremely subtle. This study aimed to assess the accuracy of a convolutional neur...
Middle Aged Case-Control Studies Wearable Electronic Devices Gait Walk Test Parkinson Disease Walking Neural Networks, Computer Female Aged Male Humans
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Estimating intra- and inter-subject oxygen consumption in outdoor human gait using multiple neural network approaches.

PloS one Sep 27, 2024
Oxygen consumption ([Formula: see text]) is an important measure for exercise test, such as walking and running, that can be measured outdoors using portable spirometers or metabolic analyzers. However, these devices are not feasible for regular use ...
Oxygen Consumption Walking Gait Running Young Adult Adult Male Heart Rate Neural Networks, Computer Female Humans
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Early Detection of Parkinson's Disease Using Deep NeuroEnhanceNet With Smartphone Walking Recordings.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 27, 2024
With the development of digital medical technology, ubiquitous smartphones are emerging as valuable tools for the detection of complex and elusive diseases. This paper exploits smartphone walking recording for early detection of Parkinson's disease (...
False Negative Reactions Smartphone Parkinson Disease Walking Early Diagnosis Male Middle Aged Deep Learning Algorithms Biomarkers Female Aged Humans Neural Networks, Computer
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Virtual Obstacle Avoidance Strategy: Navigating through a Complex Environment While Interacting with Virtual and Physical Elements.

Sensors (Basel, Switzerland) Sep 25, 2024
Robotic walking devices can be used for intensive exercises to enhance gait rehabilitation therapies. Mixed Reality (MR) techniques may improve engagement through immersive and interactive environments. This article introduces an MR-based multimodal ...
Walking Gait Female Young Adult Adult Virtual Reality Robotics Male User-Computer Interface Humans
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Comparison of feed-forward control strategies for simplified vertical hopping model with intrinsic muscle properties.

Bioinspiration & biomimetics Sep 12, 2024
To analyse walking, running or hopping motions, models with high degrees of freedom are usually used. However simple reductionist models are advantageous within certain limits. In a simple manner, the hopping motion is generally modelled by a spring-...
Locomotion Muscle, Skeletal Robotics Walking Humans Models, Biological Computer Simulation Biomechanical Phenomena
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Prediction of poststroke independent walking using machine learning: a retrospective study.

BMC neurology Sep 10, 2024
BACKGROUND: Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (XGBoost),...
Retrospective Studies Female Predictive Value of Tests Stroke Humans Male Machine Learning Walking Middle Aged Prognosis Stroke Rehabilitation Support Vector Machine Aged Adult
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Machine Learning Based Abnormal Gait Classification with IMU Considering Joint Impairment.

Sensors (Basel, Switzerland) Aug 28, 2024
Gait analysis systems are critical for assessing motor function in rehabilitation and elderly care. This study aimed to develop and optimize an abnormal gait classification algorithm considering joint impairments using inertial measurement units (IMU...
Humans Machine Learning Adult Male Algorithms Young Adult Gait Gait Analysis Ankle Joint Support Vector Machine Knee Joint Walking
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