基于 FPGA 的低功耗尖峰神经网络用于皮层内神经活动的实时解码

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Luca Martis;Gianluca Leone;Luigi Raffo;Paolo Meloni
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引用次数: 0

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Low-Power FPGA-Based Spiking Neural Networks for Real-Time Decoding of Intracortical Neural Activity
Brain-machine interfaces (BMIs) are systems designed to decode neural signals and translate them into commands for external devices. Intracortical microelectrode arrays (MEAs) represent a significant advancement in this field, offering unprecedented spatial and temporal resolutions for monitoring brain activity. However, processing data from MEAs presents challenges due to high data rates and computing power requirements. To address these challenges, we propose a novel solution leveraging spiking neural networks (SNNs) that, due to their similarity to biological neural networks and their event-based nature, promise high compatibility with neural signals and low energy consumption. In this study, we introduce a real-time neural decoding system based on an SNN, deployed on a Lattice iCE40UP5k FPGA. This system is capable of reconstructing multiple target variables, related to the kinematics and kinetics of hand motion, from iEEG signals recorded by a 96-channel MEA. We evaluated the system using two different public datasets, achieving results similar to state-of-the-art neural decoders that use more complex deep learning models. This was obtained while maintaining an average power consumption of 13.9 mW and an average energy consumption per inference of 13.9 uJ.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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