AIMC Topic: Biomechanical Phenomena
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Recognition of anxiety and depression using gait data recorded by the kinect sensor: a machine learning approach with data augmentation.
Scientific reports
Jul 2, 2025
Anxiety and depression disorders are increasingly common, necessitating methods for real-time assessment and early identification. This study investigates gait analysis as a potential indicator of mental health, using the Microsoft Kinect sensor to c...
Machine learning analysis of kinematic movement features during functional tasks to discriminate chronic neck pain patients from asymptomatic controls.
Scientific reports
Jul 1, 2025
This study evaluated the discriminative potential of a machine learning model using movement features during functional tasks to distinguish between patients with non-traumatic chronic neck pain and asymptomatic controls. The study included patients ...
Data augmentation of time-series data in human movement biomechanics: A scoping review.
PloS one
Jul 1, 2025
BACKGROUND: The integration of machine learning and deep learning methodologies has transformed data analytics in biomechanics. However, the field faces challenges such as limited large-scale data sets, high data acquisition costs, and restricted par...
OpenExo: An open-source modular exoskeleton to augment human function.
Science robotics
Jun 25, 2025
Although the field of wearable robotic exoskeletons is rapidly expanding, there are several barriers to entry that discourage many from pursuing research in this area, ultimately hindering growth. Chief among these is the lengthy and costly developme...
Accurate Tracking of Locomotory Kinematics in Mice Moving Freely in Three-Dimensional Environments.
eNeuro
Jun 25, 2025
Marker-based motion capture (MBMC) is a powerful tool for precise, high-speed, three-dimensional tracking of animal movements, enabling detailed study of behaviors ranging from subtle limb trajectories to broad spatial exploration. Despite its proven...
Performance of deep-learning models incorporating knee alignment information for predicting ground reaction force during walking.
Biomedical engineering online
Jun 24, 2025
BACKGROUND: Wearable sensors combined with deep-learning models are increasingly being used to predict biomechanical variables. Researchers have focused on either simple neural networks or complex pretrained models with multiple layers. In addition, ...
Test-retest reliability of kinematic and EEG low-beta spectral features in a robot-based arm movement task.
Biomedical physics & engineering express
Jun 18, 2025
Low-beta (L, 13-20 Hz) power plays a key role in upper-limb motor control and afferent processing, making it a strong candidate for a neurophysiological biomarker. We investigate the test-retest reliability of Lpower and kinematic features from a rob...
Unsupervised learning reveals rapid gait adaptation after leg loss and regrowth in spiders.
The Journal of experimental biology
Jun 17, 2025
Many invertebrates voluntarily lose (autotomize) limbs during antagonistic encounters, and some regenerate functional replacements. Because limb loss can have severe consequences on individual fitness, it is likely subject to significant selective pr...
Research on the evaluation and rehabilitation training system of upper limb motor function for poststroke patients based on artificial intelligence: a study protocol for a randomized controlled trial.
Trials
Jun 13, 2025
BACKGROUND: Stroke-induced upper limb dysfunction requires functional assessment and rehabilitation. The intelligent rehabilitation assessment and virtual reality training system for upper limb motor function in stroke can accurately and objectively ...
Study on the structural function and motion performance of pneumatic flexible tree-climbing robot.
PloS one
Jun 11, 2025
To enhance the adaptability of tree-climbing robots to changes in tree diameter and load capacity, an "I-shaped" pneumatic flexible tree - climbing robot was designed using self-developed pneumatic flexible joints and retractable needle anchors. The ...
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