AIMC Topic: Vibration

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Advance signal processing and machine learning approach for analysis and classification of knee osteoarthritis vibroarthrographic signals.

Medical engineering & physics
Osteoarthritis is a common cause of disability among elderly significantly affecting their quality of life due to pain and functional limitations. This study proposes a novel, non-invasive, and cost-effective diagnostic technique using vibroarthrogra...

Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique.

PloS one
Road surface roughness is the cause of vehicle vibration, which is considered a system disturbance. Previous studies on suspension system control often ignore the influence of disturbances while designing the controller, leading to system performance...

A bioinspired fish fin webbing for proprioceptive feedback.

Bioinspiration & biomimetics
The propulsive fins of ray-finned fish are used for large scale locomotion and fine maneuvering, yet also provide sensory feedback regarding hydrodynamic loading and the surrounding environment. This information is gathered via nerve cells in the web...

Machine learning models based on FEM simulation of hoop mode vibrations to enable ultrasonic cuffless measurement of blood pressure.

Medical & biological engineering & computing
Blood pressure (BP) is one of the vital physiological parameters, and its measurement is done routinely for almost all patients who visit hospitals. Cuffless BP measurement has been of great research interest over the last few years. In this paper, w...

Haptiknit: Distributed stiffness knitting for wearable haptics.

Science robotics
Haptic devices typically rely on rigid actuators and bulky power supply systems, limiting wearability. Soft materials improve comfort, but careful distribution of stiffness is required to ground actuation forces and enable load transfer to the skin. ...

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning.

IEEE journal of biomedical and health informatics
Detecting gait abnormalities is crucial for assessing fall risks and early identification of neuromusculoskeletal disorders such as Parkinson's and stroke. Traditional assessments in gait clinics are infrequent and pose barriers, particularly for dis...

Finite-time optimal control for MMCPS via a novel preassigned-time performance approach.

Neural networks : the official journal of the International Neural Network Society
This paper studies the finite-time optimal stabilization problem of the macro-micro composite positioning stage (MMCPS). The dynamic model of the MMCPS is established as an interconnected system according to the Newton's second law. Different from ex...

Evaluation of physical risk factors by fuzzy failure mode and effects analysis: an apparel mill example.

International journal of occupational safety and ergonomics : JOSE
This study investigates the evaluation of risks faced by employees in a selected large-scale apparel mill using a risk assessment method with a fuzzy logic approach. The study found that risk assessment in the apparel industry is more accurate and re...

A fault diagnosis method based on an improved diffusion model under limited sample conditions.

PloS one
As a critical component in mechanical systems, the operational status of rolling bearings plays a pivotal role in ensuring the stability and safety of the entire system. However, in practical applications, the fault diagnosis of rolling bearings ofte...

Cross-domain zero-shot learning for enhanced fault diagnosis in high-voltage circuit breakers.

Neural networks : the official journal of the International Neural Network Society
Ensuring the stability of high-voltage circuit breakers (HVCBs) is crucial for maintaining an uninterrupted supply of electricity. Existing fault diagnosis methods typically rely on extensive labeled datasets, which are challenging to obtain due to t...