On-fpga spiking neural networks for end-to-end neural decoding
In the last decades, deep learning neural decoding algorithms have gained momentum in
the field of neural interfaces and neural processing systems. However, to be deployed on …
the field of neural interfaces and neural processing systems. However, to be deployed on …
Continuous Motion Intention Prediction Using sEMG for Upper-Limb Rehabilitation: A Systematic Review of Model-Based and Model-Free Approaches
Upper limb functional impairments persisting after stroke significantly affect patients' quality
of life. Precise adjustment of robotic assistance levels based on patients' motion intentions …
of life. Precise adjustment of robotic assistance levels based on patients' motion intentions …
Spiking neural networks for physiological and speech signals: a review
Abstract The integration of Spiking Neural Networks (SNNs) into the analysis and
interpretation of physiological and speech signals has emerged as a groundbreaking …
interpretation of physiological and speech signals has emerged as a groundbreaking …
On-FPGA spiking neural networks for multi-variable end-to-end neural decoding
In the field of brain-machine interface (BMI), deep learning algorithms have been steadily
advancing as the go-to instrument for the key task of neural decoding. However, to function …
advancing as the go-to instrument for the key task of neural decoding. However, to function …
Spiking Neural Networks for Integrated Reach-to-Grasp Decoding on FPGAs
Deep learning algorithms have been gaining pace in the domain of BMI and neural
decoding. However, these algorithms need to be optimized for power efficiency and …
decoding. However, these algorithms need to be optimized for power efficiency and …
Real-Time sEMG Processing with Spiking Neural Networks on a Low-Power 5K-LUT FPGA
The accurate modeling of hand movement based on the analysis of surface
electromyographic (sEMG) signals offers exciting opportunities for the development of …
electromyographic (sEMG) signals offers exciting opportunities for the development of …
Learning-Based Multimodal Control for a Supernumerary Robotic System in Human-Robot Collaborative Sorting
In this letter, a multi-modal learning and control framework is proposed for the control of a
supernumerary robotic limb (SRL). The SRL is a wearable robotic arm designed to enhance …
supernumerary robotic limb (SRL). The SRL is a wearable robotic arm designed to enhance …
Exploring the potential of spiking neural networks in biomedical applications: advantages, limitations, and future perspectives
E Kim, Y Kim - Biomedical Engineering Letters, 2024 - Springer
In this paper, a comprehensive exploration is undertaken to elucidate the utilization of
Spiking Neural Networks (SNNs) within the biomedical domain. The investigation delves …
Spiking Neural Networks (SNNs) within the biomedical domain. The investigation delves …
Implementasi Convolutional Neural Network Pada Lengan Prostetik Bionik Berbasis Wearable Electromyography Armband Sensor
MA Daniswara, ER Widasari - Jurnal Pengembangan Teknologi …, 2025 - j-ptiik.ub.ac.id
Kehilangan tangan akibat amputasi dapat mempengaruhi kesehatan fisiologis dan
psikologis penderitanya. Jumlah penyandang disabilitas di Indonesia mencapai 22, 97 juta …
psikologis penderitanya. Jumlah penyandang disabilitas di Indonesia mencapai 22, 97 juta …
Implementasi Fuzzy Mamdani Untuk Mengoptimalkan Gerakan Jari Pada Lengan Prostetik Bionik
FR Ksatria, ER Widasari - Jurnal Pengembangan Teknologi Informasi …, 2025 - j-ptiik.ub.ac.id
Penyandang disabilitas, terutama mereka yang kehilangan fungsi lengan, sering
menghadapi kesulitan dalam kehidupan sehari-hari. Di Indonesia, dengan jumlah …
menghadapi kesulitan dalam kehidupan sehari-hari. Di Indonesia, dengan jumlah …