Name
Title | ||
|---|---|---|
4.5 BioAIP: A Reconfigurable Biomedical AI Processor with Adaptive Learning for Versatile Intelligent Health Monitoring |
Abstract | ||
|---|---|---|
Intelligent health monitoring devices automatically detect abnormalities in users’ biomedical signals (e.g. arrhythmia from an ECG signal or a seizure from an EEG signal) through signal classification. Compared to conventional machine learning methods, neural-network-based AI classification methods are promising in achieving higher classification accuracy, but with significantly increased computational complexity, posing challenges to real-time performance and low power consumption. AI processors have been designed to accelerate neural networks for general AI applications such as image and voice recognition [1]. They are not suitable for biomedical AI processing, which requires a combination of biomedical and AI processing hardware. In addition, the design redundancy for general AI applications results in large power consumption making it unsuitable for ultra-low-power health monitoring devices. There are also some biomedical AI processors such as ECG/EEG/EMG AI processors [2] [3] [4]. However, they are customized for specific algorithms and tasks, prohibiting algorithm upgrades, limiting their applicability. In addition, prior designs lack adaptive learning to address the patient-to-patient variation issue. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISSCC42613.2021.9365996 | 2021 IEEE International Solid- State Circuits Conference (ISSCC) |
Keywords | DocType | Volume |
voice recognition,reconfigurable biomedical AI processor,intelligent health monitoring,signal classification,conventional machine learning,computational complexity,power consumption,ultralow-power health monitoring,neural-network-based AI classification,ECG-EEG-EMG AI processors,BioAlP,reconfigurable neural network,patient-to-patient variation,Al-based adaptive-learning,data compression | Conference | 64 |
ISSN | ISBN | Citations |
0193-6530 | 978-1-7281-9550-6 | 8 |
PageRank | References | Authors |
0.50 | 0 | 12 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| jiahao liu | 1 | 23 | 11.31 |
| Zhen Zhu | 2 | 8 | 1.51 |
| Yong Zhou | 3 | 8 | 0.50 |
| Ning Wang | 4 | 94 | 10.16 |
| Guanghai Dai | 5 | 19 | 1.38 |
| Qingsong Liu | 6 | 8 | 0.50 |
| Jianbiao Xiao | 7 | 17 | 2.02 |
| Yuxiang Xie | 8 | 24 | 2.94 |
| Zirui Zhong | 9 | 8 | 0.50 |
| Hongduo Liu | 10 | 8 | 0.50 |
| Liang Chang | 11 | 22 | 3.80 |
| Jun Zhou | 12 | 9 | 0.91 |