AIMC Topic: Algorithms

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A Machine Learning Approach for Prediction of Sedentary Behavior Based on Daily Step Counts.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sedentary behavior is considered as a major public health challenge, linked with many chronic diseases and premature mortality. In this paper, we propose a steps counting -based machine learning approach for the prediction of sedentary behavior. Our ...

An Approach for Deep Learning in ECG Classification Tasks in the Presence of Noisy Labels.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cardiovascular disease (CVD) is a serial of diseases with global leading causes of death. Electrocardiogram (ECG) is the most commonly used basis for CVD diagnosis due to its low cost and no injury. Due to the great performance shown in classificatio...

Insights of 3D Input CNN in EEG-based Emotion Recognition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electroencephalogram (EEG) signals have shown to be a good source of information for emotion recognition algorithms in Human-Brain interaction applications. In this paper, a reproducible framework is proposed for classifying human emotions based on E...

ECG-based Biometric Recognition without QRS Segmentation: A Deep Learning-Based Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electrocardiogram (ECG)-based identification systems have been widely studied in the literature. Usually, an ECG trace needs to be segmented according to the detected R peaks to enable feature extraction from the ECGs of duration equal to nearly one ...

Crackle Detection In Lung Sounds Using Transfer Learning And Multi-Input Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Large annotated lung sound databases are publicly available and might be used to train algorithms for diagnosis systems. However, it might be a challenge to develop a well-performing algorithm for small non-public data, which have only a few subjects...

Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer Mapping.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Motion recognition based on surface electromyogram (sEMG) recorded from the forearm is attracting attention for its applicability because it easily integrates with wearable devices and has a high signal-to-noise ratio. Inter-subject variability and i...

Simplified description of dynamics in neuromorphic resonant tunneling diodes.

Chaos (Woodbury, N.Y.)
In this article, the standard theoretical model accounting for a double barrier quantum well resonant tunneling diode (RTD) connected to a direct current source of voltage is simplified by representing its current-voltage characteristic with an analy...

Model reduction in acoustic inversion by artificial neural network.

The Journal of the Acoustical Society of America
In ultrasound tomography, the speed of sound inside an object is estimated based on acoustic measurements carried out by sensors surrounding the object. An accurate forward model is a prominent factor for high-quality image reconstruction, but it can...

A causal and talker-independent speaker separation/dereverberation deep learning algorithm: Cost associated with conversion to real-time capable operation.

The Journal of the Acoustical Society of America
The fundamental requirement for real-time operation of a speech-processing algorithm is causality-that it operate without utilizing future time frames. In the present study, the performance of a fully causal deep computational auditory scene analysis...

An optimized pulse coupled neural network image de-noising method for a field-programmable gate array based polarization camera.

The Review of scientific instruments
The quality of polarization images is easy to be affected by the noise in the image acquired by a polarization camera. Consequently, a de-noising method optimized with a Pulse Coupled Neural Network (PCNN) for polarization images is proposed for a Fi...