AIMC Topic: Signal Processing, Computer-Assisted

Clear Filters Showing 2031 to 2040 of 2081 articles

Restoring speech following total removal of the larynx by a learned transformation from sensor data to acoustics.

The Journal of the Acoustical Society of America
Total removal of the larynx may be required to treat laryngeal cancer: speech is lost. This article shows that it may be possible to restore speech by sensing movement of the remaining speech articulators and use machine learning algorithms to derive...

Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners.

The Journal of the Acoustical Society of America
Machine-learning based approaches to speech enhancement have recently shown great promise for improving speech intelligibility for hearing-impaired listeners. Here, the performance of three machine-learning algorithms and one classical algorithm, Wie...

Speaker-dependent multipitch tracking using deep neural networks.

The Journal of the Acoustical Society of America
Multipitch tracking is important for speech and signal processing. However, it is challenging to design an algorithm that achieves accurate pitch estimation and correct speaker assignment at the same time. In this paper, deep neural networks (DNNs) a...

S1 and S2 Heart Sound Recognition Using Deep Neural Networks.

IEEE transactions on bio-medical engineering
OBJECTIVE: This study focuses on the first (S1) and second (S2) heart sound recognition based only on acoustic characteristics; the assumptions of the individual durations of S1 and S2 and time intervals of S1-S2 and S2-S1 are not involved in the rec...

Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series.

Studies in health technology and informatics
The purpose of this work is to evaluate methods from deep learning for application to Magnetic Resonance Fingerprinting (MRF). MRF is a recently proposed measurement technique for generating quantitative parameter maps. In MRF a non-steady state sign...

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

Bio-medical materials and engineering
BACKGROUND AND OBJECTIVE: Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure de...

Features extraction and multi-classification of sEMG using a GPU-Accelerated GA/MLP hybrid algorithm.

Journal of X-ray science and technology
BACKGROUND: Surface electromyography (sEMG) signal is the combined effect of superficial muscle EMG and neural electrical activity. In recent years, researchers did large amount of human-machine system studies by using the physiological signals as co...

Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.

Journal of X-ray science and technology
BACKGROUND: Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important...

[Research on Control System of an Exoskeleton Upper-limb Rehabilitation Robot].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In order to help the patients with upper-limb disfunction go on rehabilitation training,this paper proposed an upper-limb exoskeleton rehabilitation robot with four degrees of freedom(DOF),and realized two control schemes,i.e.,voice control and elect...

[A Classification Algorithm for Epileptic Electroencephalogram Based on Wavelet Multiscale Analysis and Extreme Learning Machine].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The automatic classification of epileptic electroencephalogram(EEG)is significant in the diagnosis and therapy of epilepsy.A classification algorithm for epileptic EEG based on wavelet multiscale analysis and extreme learning machine(ELM)is proposed ...