Filters








13 Hits in 12.7 sec

Ultra Low-Power and Real-time ECG Classification Based on STDP and R-STDP Neural Networks for Wearable Devices [article]

Alireza Amirshahi, Matin Hashemi
2019 arXiv   pre-print
This paper presents a novel ECG classification algorithm for real-time cardiac monitoring on ultra low-power wearable devices.  ...  The proposed solution is based on spiking neural networks which are the third generation of neural networks.  ...  This paper proposes a novel SNN-based ECG classification algorithm for real-time operation on ultra low-power wearable devices. The overall view of the proposed solution is shown in Fig. 1 .  ... 
arXiv:1905.02954v3 fatcat:wp6obeqvuzfz7aqdi3cyyzkcce

A Compact Online-Learning Spiking Neuromorphic Biosignal Processor [article]

Chaoming Fang, Ziyang Shen, Fengshi Tian, Jie Yang, Mohamad Sawan
2022 arXiv   pre-print
Real-time biosignal processing on wearable devices has attracted worldwide attention for its potential in healthcare applications.  ...  A trace-based Spiking-Timing-Dependent-Plasticity (STDP) lgorithm is applied to realize hardware-friendly online learning of a single-layer excitatory-inhibitory spiking neural network.  ...  ACKNOWLEDGEMENT The authors would like to acknowledge the financial support and tools received from Westlake University and Zhejiang Key R&D Program No. 2021C03002 to support this project.  ... 
arXiv:2209.12384v1 fatcat:hayuxygj6na3vlqv4z7j73mvqi

Table of Contents

2019 IEEE Transactions on Biomedical Circuits and Systems  
Chen 1471 ECG Classification Algorithm Based on STDP and R-STDP Neural Networks for Real-Time Monitoring on Ultra Low-Power Personal Wearable Devices . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Bai 1563 Real-Time Ultra-Low Power ECG Anomaly Detection Using an Event-Driven Neuromorphic Processor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tbcas.2019.2961550 fatcat:hqa2tvaic5dfzeybrqz677nkiu

Table of contents

2017 2017 IEEE International Symposium on Circuits and Systems (ISCAS)  
Finger SensationA Charge-Based Ultra-Low Power Continuous-Time ADC for Data Driven Neural Spike ProcessingAnalysis of Passive Charge Balancing for Safe Current-Mode Neural StimulationA Novel Wavelet-Based  ...  R-56 -A 170nW CMOS Wake-Up Receiver with -60 dBm Sensitivity Using AlN High-Q Piezoelectric Resonators R-57 -High Temperature VCO Based on GaN Devices for Downhole Communications R-58 -A 9.4 pJ/  ... 
doi:10.1109/iscas.2017.8049750 fatcat:csazlovzq5g4bmzlf7uss65sy4

MSPAN: A Memristive Spike-Based Computing Engine With Adaptive Neuron for Edge Arrhythmia Detection

Jingwen Jiang, Fengshi Tian, Jinhao Liang, Ziyang Shen, Yirui Liu, Jiapei Zheng, Hui Wu, Zhiyuan Zhang, Chaoming Fang, Yifan Zhao, Jiahe Shi, Xiaoyong Xue (+1 others)
2021 Frontiers in Neuroscience  
A multi-layer deep integrative spiking neural network (DiSNN) is first designed with an accuracy of 93.6% in 4-class ECG classification tasks.  ...  By evaluation, the overall system achieves an accuracy of over 92.25% on the MIT-BIH dataset while the area is 3.438 mm2 and the power consumption is 0.178 μJ per heartbeat at a clock frequency of 500  ...  ., and Hashemi, M. (2019). ECG classification algorithm based on STDP and R-STDP neural networks for real-time monitoring on ultra low-power personal wearable devices. IEEE Trans. Biomed.  ... 
doi:10.3389/fnins.2021.761127 pmid:34975373 pmcid:PMC8715923 fatcat:tkgcnfj355ffbdihyvqmwtahzm

2020 Index IEEE Transactions on Biomedical Circuits and Systems Vol. 14

2020 IEEE Transactions on Biomedical Circuits and Systems  
., 1333-1345 J Jafari, R., see  ...  Fiorelli, R., +, TBCAS June 2020 606-619 ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression.  ...  ., +, TBCAS Aug. 2020 681-691 ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression.  ... 
doi:10.1109/tbcas.2021.3059009 fatcat:rthgi6nrxzeaxkkwqwx753nrze

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

Mostafa Rahimiazghadi, Corey Lammie, Jason Kamranr Eshraghian, Melika Payvand, Elisa Donati, Bernabe Linares-Barranco, Giacomo Indiveri
2020 IEEE Transactions on Biomedical Circuits and Systems  
With the advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors, new opportunities are emerging for applying deep and Spiking Neural Network (SNN) algorithms to healthcare and  ...  After providing the required background, we unify the sparsely distributed research on neural network and neuromorphic hardware implementations as applied to the healthcare domain.  ...  deploying healthcare devices closer to the edge, paving the way for low-power and low-cost DL accelerators for PoC devices and healthcare IoT.  ... 
doi:10.1109/tbcas.2020.3036081 pmid:33156792 fatcat:rjwfjd7vmvglpk762mqeyiteqq

2021 Index IEEE Transactions on Circuits and Systems I: Regular Papers Vol. 68

2021 IEEE Transactions on Circuits and Systems Part 1: Regular Papers  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TCSI May 2021 1814-1826 Efficient Hardware Architecture of Convolutional Neural Network for ECG Classification in Wearable Healthcare Device.  ... 
doi:10.1109/tcsi.2021.3134605 fatcat:txqhqj7nvnh6pp5dqloynq5jku

2022 Roadmap on Neuromorphic Computing and Engineering [article]

Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano (+47 others)
2022 arXiv   pre-print
Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically  ...  Modern computation based on the von Neumann architecture is today a mature cutting-edge science.  ...  This new class of extremely low-power and lowlatency artificial intelligence systems could, In a world where power-hungry deep learning techniques are becoming a commodity, and at the same time, environmental  ... 
arXiv:2105.05956v3 fatcat:pqir5infojfpvdzdwgmwdhsdi4

2020 Index IEEE Transactions on Circuits and Systems II: Express Briefs Vol. 67

2020 IEEE Transactions on Circuits and Systems - II - Express Briefs  
Chip PWM Driver Circuit for Inverter Welding Power Source; TCSII April 2020 720-724 Jacobsson, S., see Castaneda, O., TCSII May 2020 891-895 Jafari, E., and Binazadeh, T., Robust Output Regulation in  ...  , M., see Kari Dolatabadi, A., TCSII Oct. 2020 1740-1744 Jalili, M., see Fang, X., TCSII March 2020 511-515 Jana, B., Roy, A.S., Saha, G., and Banerjee, S., A Low-Error, Memory-Based Fast Binary Logarithmic  ...  ., +, TCSII Dec. 2020 3387-3391 VLSI Implementation of Lossless ECG Compression Algorithm for Low Power Devices.  ... 
doi:10.1109/tcsii.2020.3047305 fatcat:ifjzekeyczfrbp5b7wrzandm7e

Novel Concepts for Organic Transistors: Physics, Device Design, and Applications [article]

Hans Kleemann
2021 arXiv   pre-print
In particular, the combination of OECTs acting as sensor units and self-learning neural networks at once enables the development of intelligent tags for medical applications.  ...  In this context, mixed ionic-electronic conductors and organic electro-chemical transistors (OECTs) are identified as highly promising approaches for electronic bio-interfaces enabling ultra-sensitive  ...  Thanks also to Shen and Jonas for their work on the organic photodetectors. Furthermore, I am grateful to Micha and Felix for proof-reading.  ... 
arXiv:2111.09430v1 fatcat:hemjnbscwvfo7l3i33f7se3gru

Green Materials and Technologies for Sustainable Organic Transistors

Fabrizio Torricelli, Ivano Alessandri, Eleonora Macchia, Irene Vassalini, Marina Maddaloni, Luisa Torsi
2021 Advanced Materials Technologies  
Acknowledgements F.T. and I.A. contributed equally to this work.  ...  Low-voltage and high-frequency operation are very important features when organic transistors are used in portable applications relying on mobile power supplies and harvesting devices.  ...  33] medical and implantable devices, [34, 35] and neural interfaces, [36] [37] [38] [39] to name a few.  ... 
doi:10.1002/admt.202100445 fatcat:x3x7wdpr6bgjjktxq466seqara

2022 roadmap on neuromorphic computing and engineering

Dennis Valbjørn Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano (+12 others)
2022
Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically  ...  Modern computation based on von Neumann architecture is now a mature cutting-edge science.  ...  Acknowledgements The author thanks the CNRS for support. Acknowledgements The author would like to thank E Donati for fun and insightful discussions and brainstorming on the topic.  ... 
doi:10.3929/ethz-b-000529282 fatcat:x5s5lalqqbbn7fb6gmpqmbqkxu