AI Medical Compendium Journal:
IEEE transactions on biomedical circuits and systems

Showing 71 to 80 of 132 articles

ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression.

IEEE transactions on biomedical circuits and systems
Biometrics such as facial features, fingerprint, and iris are being used increasingly in modern authentication systems. These methods are now popular and have found their way into many portable electronics such as smartphones, tablets, and laptops. F...

A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications.

IEEE transactions on biomedical circuits and systems
This paper reviews the state of the arts and trends of the AI-Based biomedical processing algorithms and hardware. The algorithms and hardware for different biomedical applications such as ECG, EEG and hearing aid have been reviewed and discussed. Fo...

Accurate, Very Low Computational Complexity Spike Sorting Using Unsupervised Matched Subspace Learning.

IEEE transactions on biomedical circuits and systems
This paper presents an adaptable dictionary-based feature extraction approach for spike sorting offering high accuracy and low computational complexity for implantable applications. It extracts and learns identifiable features from evolving subspaces...

An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.

IEEE transactions on biomedical circuits and systems
In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition a...

The Design of Memristive Circuit for Affective Multi-Associative Learning.

IEEE transactions on biomedical circuits and systems
In this work, a memristive circuit with affective multi-associative learning function is proposed, which mimics the process of human affective formation. It mainly contains three modules: affective associative learning, affective formation, affective...

Robust Real-Time Embedded EMG Recognition Framework Using Temporal Convolutional Networks on a Multicore IoT Processor.

IEEE transactions on biomedical circuits and systems
Hand movement classification via surface electromyographic (sEMG) signal is a well-established approach for advanced Human-Computer Interaction. However, sEMG movement recognition has to deal with the long-term reliability of sEMG-based control, limi...

Deep Learning Approach for Epileptic Focus Localization.

IEEE transactions on biomedical circuits and systems
The task of epileptic focus localization receives great attention due to its role in an effective epileptic surgery. The clinicians highly depend on the intracranial EEG data to make a surgical decision related to epileptic subjects suffering from un...

Who is the Winner? Memristive-CMOS Hybrid Modules: CNN-LSTM Versus HTM.

IEEE transactions on biomedical circuits and systems
Hierarchical, modular and sparse information processing are signature characteristics of biological neural networks. These aspects have been the backbone of several artificial neural network designs of the brain-like networks, including Hierarchical ...

A 13.34 μW Event-Driven Patient-Specific ANN Cardiac Arrhythmia Classifier for Wearable ECG Sensors.

IEEE transactions on biomedical circuits and systems
Artificial neural network (ANN) and its variants are favored algorithm in designing cardiac arrhythmia classifier (CAC) for its high accuracy. However, the implementation of ultralow power ANN-CAC is challenging due to the intensive computations. Mor...

A Fully Embedded Adaptive Real-Time Hand Gesture Classifier Leveraging HD-sEMG and Deep Learning.

IEEE transactions on biomedical circuits and systems
This paper presents a real-time fine gesture recognition system for multi-articulating hand prosthesis control, using an embedded convolutional neural network (CNN) to classify hand-muscle contractions sensed at the forearm. The sensor consists in a ...