AIMC Topic: Movement

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Relationships between motor and cognitive functions and subsequent post-stroke mood disorders revealed by machine learning analysis.

Scientific reports Nov 11, 2020
Mood disorders (e.g. depression, apathy, and anxiety) are often observed in stroke patients, exhibiting a negative impact on functional recovery associated with various physical disorders and cognitive dysfunction. Consequently, post-stroke symptoms ...
Humans Aged Male Middle Aged Neural Networks, Computer Machine Learning Female Mood Disorders Movement Stroke Rehabilitation ROC Curve Cognition Stroke
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Ultra-sensitive and resilient compliant strain gauges for soft machines.

Nature Nov 11, 2020
Soft machines are a promising design paradigm for human-centric devices and systems required to interact gently with their environment. To enable soft machines to respond intelligently to their surroundings, compliant sensory feedback mechanisms are ...
Pliability Textiles Motion Movement Feedback, Sensory Humans Wearable Electronic Devices User-Computer Interface Robotics Hand
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Machine Learning Improvements to Human Motion Tracking with IMUs.

Sensors (Basel, Switzerland) Nov 9, 2020
Inertial Measurement Units (IMUs) have become a popular solution for tracking human motion. The main problem of using IMU data for deriving the position of different body segments throughout time is related to the accumulation of the errors in the in...
Neural Networks, Computer Machine Learning Support Vector Machine Humans Acceleration Movement
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Classification of Aggressive Movements Using Smartwatches.

Sensors (Basel, Switzerland) Nov 9, 2020
Recognizing aggressive movements is a challenging task in human activity recognition. Wearable smartwatch technology with machine learning may be a viable approach for human aggressive behavior classification. This research identified a viable classi...
Aggression Support Vector Machine Bayes Theorem Movement Neural Networks, Computer Wearable Electronic Devices Humans
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Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration.

Sensors (Basel, Switzerland) Nov 8, 2020
The human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for an effective human-robot collaboration. This study aims to investigate the differences in visuomotor control between the dominant (DH) and non-dominan...
Humans Hand Female Movement Young Adult Male Adult Virtual Reality Robotics Feedback Biomechanical Phenomena
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Smartphone Motion Sensor-Based Complex Human Activity Identification Using Deep Stacked Autoencoder Algorithm for Enhanced Smart Healthcare System.

Sensors (Basel, Switzerland) Nov 5, 2020
Human motion analysis using a smartphone-embedded accelerometer sensor provided important context for the identification of static, dynamic, and complex sequence of activities. Research in smartphone-based motion analysis are implemented for tasks, s...
Humans Smartphone Movement Human Activities Machine Learning Algorithms Delivery of Health Care
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Learning Three Dimensional Tennis Shots Using Graph Convolutional Networks.

Sensors (Basel, Switzerland) Oct 27, 2020
Human movement analysis is very often applied to sport, which has seen great achievements in assessing an athlete's progress, giving further training tips and in movement recognition. In tennis, there are two basic shots: forehand and backhand, which...
Tennis Machine Learning Humans Biomechanical Phenomena Neural Networks, Computer Movement
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Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification.

Sensors (Basel, Switzerland) Oct 22, 2020
Observation of neuromotor development at an early stage of an infant's life allows for early diagnosis of deficits and the beginning of the therapeutic process. General movement assessment is a method of spontaneous movement observation, which is the...
Video Recording Movement Humans Machine Learning Algorithms Infant, Newborn Diagnosis, Computer-Assisted
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Deep learning-assisted comparative analysis of animal trajectories with DeepHL.

Nature communications Oct 20, 2020
A comparative analysis of animal behavior (e.g., male vs. female groups) has been widely used to elucidate behavior specific to one group since pre-Darwinian times. However, big data generated by new sensing technologies, e.g., GPS, makes it difficul...
Software Ursidae Female Insecta Animals Birds Neural Networks, Computer Behavior, Animal Deep Learning Movement Mice
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Machine learning discriminates a movement disorder in a zebrafish model of Parkinson's disease.

Disease models & mechanisms Oct 16, 2020
Animal models of human disease provide an system that can reveal molecular mechanisms by which mutations cause pathology, and, moreover, have the potential to provide a valuable tool for drug development. Here, we have developed a zebrafish model of...
Disease Models, Animal Parkinson Disease Mutation Alleles Zebrafish Base Sequence Brain Animals Gene Targeting Machine Learning Gene Expression Profiling Protein Deglycase DJ-1 Algorithms Movement Dopaminergic Neurons Movement Disorders
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