AIMC Topic: Signal Processing, Computer-Assisted

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Piezoresistive Tactile Sensor Discriminating Multidirectional Forces.

Sensors (Basel, Switzerland)
Flexible tactile sensors capable of detecting the magnitude and direction of the applied force together are of great interest for application in human-interactive robots, prosthetics, and bionic arms/feet. Human skin contains excellent tactile sensin...

EEG Signals Analysis Using Multiscale Entropy for Depth of Anesthesia Monitoring during Surgery through Artificial Neural Networks.

Computational and mathematical methods in medicine
In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms have been proposed in recent years, one of which is sample entropy (SampEn), a commonly used and important tool to measure the regularity of data series. How...

An automatic method for arterial pulse waveform recognition using KNN and SVM classifiers.

Medical & biological engineering & computing
The measurement and analysis of the arterial pulse waveform (APW) are the means for cardiovascular risk assessment. Optical sensors represent an attractive instrumental solution to APW assessment due to their truly non-contact nature that makes the m...

A Fuzzy Inference System for Closed-Loop Deep Brain Stimulation in Parkinson's Disease.

Journal of medical systems
Parkinsons disease is a complex neurodegenerative disorder for which patients present many symptoms, tremor being the main one. In advanced stages of the disease, Deep Brain Stimulation is a generalized therapy which can significantly improve the mot...

Discriminating preictal and interictal brain states in intracranial EEG by sample entropy and extreme learning machine.

Journal of neuroscience methods
BACKGROUND: Epilepsy is one of the most common neurological disorders approximately one in every 100 people worldwide are suffering from it. Uncontrolled epilepsy poses a significant burden to society due to associated healthcare cost to treat and co...

A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals.

Biomedical engineering online
BACKGROUND: A brain-machine interface (BMI) should be able to help people with disabilities by replacing their lost motor functions. To replace lost functions, robot arms have been developed that are controlled by invasive neural signals. Although in...

Sleep stage classification with ECG and respiratory effort.

Physiological measurement
Automatic sleep stage classification with cardiorespiratory signals has attracted increasing attention. In contrast to the traditional manual scoring based on polysomnography, these signals can be measured using advanced unobtrusive techniques that a...

Real-Time Classification of Bladder Events for Effective Diagnosis and Treatment of Urinary Incontinence.

IEEE transactions on bio-medical engineering
Diagnosis of lower urinary tract dysfunction with urodynamics has historically relied on data acquired from multiple sensors using nonphysiologically fast cystometric filling. In addition, state-of-the-art neuromodulation approaches to restore bladde...

Automated Cognitive Health Assessment From Smart Home-Based Behavior Data.

IEEE journal of biomedical and health informatics
Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and well-being assessment. In this paper, we examine the actual benefits of smart home-based analysis by monitoring daily behavior in the home a...