AIMC Topic: Signal Processing, Computer-Assisted

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Fault-Tolerant Sensor Detection of sEMG signals: Quality Analysis Using a Two-Class Support Vector Machine.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The capacity to identify the contamination in surface electromyography (sEMG) signals is necessary for applying the sEMG controlled prosthesis over time. In this paper, the method for the automatic identification of commonly occurring contaminant typ...

Noise Detection in Electrocardiography Signal for Robust Heart Rate Variability Analysis: A Deep Learning Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Heart rate variability (HRV) analysis is widely used to assess the sympathetic and parasympathetic tones. However, the quality of the derived HRV features is heavily dependent on the accuracy of QRS detection. Noisy electrocardiography (ECG) signals,...

Deep learning models to remix music for cochlear implant users.

The Journal of the Acoustical Society of America
The severe hearing loss problems that some people suffer can be treated by providing them with a surgically implanted electrical device called cochlear implant (CI). CI users struggle to perceive complex audio signals such as music; however, previous...

An Adaptive Neural Spike Processor With Embedded Active Learning for Improved Unsupervised Sorting Accuracy.

IEEE transactions on biomedical circuits and systems
There is a need for integrated spike sorting processors in implantable devices with low power consumption that have improved accuracy. Learning the characteristics of the variable input neural signals and adapting the functionality of the sorting pro...

Learning-Based Compressive MRI.

IEEE transactions on medical imaging
In the area of magnetic resonance imaging (MRI), an extensive range of non-linear reconstruction algorithms has been proposed which can be used with general Fourier subsampling patterns. However, the design of these subsampling patterns has typically...

Context encoding enables machine learning-based quantitative photoacoustics.

Journal of biomedical optics
Real-time monitoring of functional tissue parameters, such as local blood oxygenation, based on optical imaging could provide groundbreaking advances in the diagnosis and interventional therapy of various diseases. Although photoacoustic (PA) imaging...

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning.

GigaScience
Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex elec...

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signa...

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

IEEE transactions on biomedical circuits and systems
Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim t...

Artificial neural network detects human uncertainty.

Chaos (Woodbury, N.Y.)
Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allo...