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

Showing 31 to 40 of 132 articles

Multidirectional Associative Memory Neural Network Circuit Based on Memristor.

IEEE transactions on biomedical circuits and systems
Multidirectional associative memory neural network(MAMNN) is a direct extension of bidirectional associative memory neural network, which can handle multiple associations. In this work, a circuit of MAMNN based on memristor is proposed, which simulat...

A 0.99-to-4.38 uJ/class Event-Driven Hybrid Neural Network Processor for Full-Spectrum Neural Signal Analyses.

IEEE transactions on biomedical circuits and systems
Versatile and energy-efficient neural signal processors are in high demand in brain-machine interfaces and closed-loop neuromodulation applications. In this paper, we propose an energy-efficient processor for neural signal analyses. The proposed proc...

FPGA-Based In-Vivo Calcium Image Decoding for Closed-Loop Feedback Applications.

IEEE transactions on biomedical circuits and systems
Miniaturized calcium imaging is an emerging neural recording technique that has been widely used for monitoring neural activity on a large scale at a specific brain region of rats or mice. Most existing calcium-image analysis pipelines operate offlin...

In-Sensor Artificial Intelligence and Fusion With Electronic Medical Records for At-Home Monitoring.

IEEE transactions on biomedical circuits and systems
This work presents an artificial intelligence (AI) framework for real-time, personalized sepsis prediction four hours before onset through fusion of electrocardiogram (ECG) and patient electronic medical record. An on-chip classifier combines analog ...

A 5.3 pJ/Spike CMOS Neural Array Employing Time-Modulated Axon-Sharing and Background Mismatch Calibration Techniques.

IEEE transactions on biomedical circuits and systems
Inspired by the human brain, spiking neuron networks are promising to realize energy-efficient and low-latency neuromorphic computing. However, even state-of-the-art silicon neurons are orders of magnitude worse than biological neurons in terms of ar...

A Review of Emerging Electromagnetic-Acoustic Sensing Techniques for Healthcare Monitoring.

IEEE transactions on biomedical circuits and systems
Conventional electromagnetic (EM) sensing techniques such as radar and LiDAR are widely used for remote sensing, vehicle applications, weather monitoring, and clinical monitoring. Acoustic techniques such as sonar and ultrasound sensors are also used...

An Extended Spatial Transformer Convolutional Neural Network for Gesture Recognition and Self-Calibration Based on Sparse sEMG Electrodes.

IEEE transactions on biomedical circuits and systems
sEMG-based gesture recognition is widely applied in human-machine interaction system by its unique advantages. However, the accuracy of recognition drops significantly as electrodes shift. Besides, in applications such as VR, virtual hands should be ...

Analog Gated Recurrent Unit Neural Network for Detecting Chewing Events.

IEEE transactions on biomedical circuits and systems
We present a novel gated recurrent neural network to detect when a person is chewing on food. We implemented the neural network as a custom analog integrated circuit in a 0.18 μm CMOS technology. The neural network was trained on 6.4 hours of data co...

Memristor Neural Network Circuit Based on Operant Conditioning With Immediacy and Satiety.

IEEE transactions on biomedical circuits and systems
Most of the operant conditioning only consider the basic theory, but the influencing factors such as immediacy and satiety are ignored. In this paper, a memristor neural network circuit based on operant conditioning with immediacy and satiety is prop...

A Co-Designed Neuromorphic Chip With Compact (17.9K F) and Weak Neuron Number-Dependent Neuron/Synapse Modules.

IEEE transactions on biomedical circuits and systems
Many efforts have been made to improve the neuron integration efficiency on neuromorphic chips, such as using emerging memory devices and shrinking CMOS technology nodes. However, in the fully connected (FC) neuromorphic core, increasing the number o...