AIMC Topic: Biomechanical Phenomena

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Using Deep Learning Models to Predict Prosthetic Ankle Torque.

Sensors (Basel, Switzerland)
Inverse dynamics from motion capture is the most common technique for acquiring biomechanical kinetic data. However, this method is time-intensive, limited to a gait laboratory setting, and requires a large array of reflective markers to be attached ...

Investigation with able-bodied subjects suggests Myosuit may potentially serve as a stair ascent training robot.

Scientific reports
Real world settings are seldomly just composed of level surfaces and stairs are frequently encountered in daily life. Unfortunately, ~ 90% of the elderly population use some sort of compensation pattern in order to negotiate stairs. Because the biome...

On the influence of head motion on the swimming kinematics of robotic fish.

Bioinspiration & biomimetics
Up to now bio-inspired fish-mimicking robots fail when competing with the swimming performance of real fish. While tail motion has been studied extensively, the influence of the head motion is still not fully understood and its active control is chal...

An unsupervised wavelet neural network model for approximating the solutions of non-linear nervous stomach model governed by tension, food and medicine.

Computer methods in biomechanics and biomedical engineering
The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forces and chemical reactions in order to release nutrients. All ingested items, including our nutrition, should first pass through the stomach, making it...

Robust deep learning-based gait event detection across various pathologies.

PloS one
The correct estimation of gait events is essential for the interpretation and calculation of 3D gait analysis (3DGA) data. Depending on the severity of the underlying pathology and the availability of force plates, gait events can be set either manua...

Decoding movement kinematics from EEG using an interpretable convolutional neural network.

Computers in biology and medicine
Continuous decoding of hand kinematics has been recently explored for the intuitive control of electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs). Deep neural networks (DNNs) are emerging as powerful decoders, for their ability to au...

Air-to-land transitions: from wingless animals and plant seeds to shuttlecocks and bio-inspired robots.

Bioinspiration & biomimetics
Recent observations of wingless animals, including jumping nematodes, springtails, insects, and wingless vertebrates like geckos, snakes, and salamanders, have shown that their adaptations and body morphing are essential for rapid self-righting and c...

Machine learning for lumbar and pelvis kinematics clustering.

Computer methods in biomechanics and biomedical engineering
Clustering algorithms such as k-means and agglomerative hierarchical clustering (HCA) may provide a unique opportunity to analyze time-series kinematic data. Here we present an approach for determining number of clusters and which clustering algorith...

Contact feedback helps snake robots propel against uneven terrain using vertical bending.

Bioinspiration & biomimetics
Snakes can bend their elongate bodies in various forms to traverse various environments. We understand well how snakes use lateral body bending to push against asperities on flat ground for propulsion, and snake robots can do so effectively. However,...

Evaluating adaptiveness of an active back exosuit for dynamic lifting and maximum range of motion.

Ergonomics
Back exosuits deliver mechanical assistance to reduce the risk of back injury, however, minimising restriction is critical for adoption. We developed the adaptive impedance controller to minimise restriction while maintaining assistance by modulating...