Deep learning (DL) models for real-time wearable sleep staging often rely on long-kernel temporal convolutions, a requirement that current accelerators struggle to support efficiently. To overcome this, we present an FPGA-based CNN-BiLSTM accelerator that incorporates several algorithm-hardware co-design techniques to...
Aaron Zhou, Ya-Qian Xu, Chen Chen et al.· 1 citation
This letter presents a mixed-precision CNN–LSTM accelerator for EEG-based sleep staging. To efficiently execute long temporal convolutions, a serpentine dataflow propagates activations between neighboring processing elements (PEs), reducing memory accesses by <inline-formula> <tex-math notation="LaTeX">$6.2\times $ </t...
With state-of-the-art approaches for achieving biocompatibility, remote powering, and wireless data transmission, the next generation of subdermal biosensors can be developed for unmet needs in chronic disease monitoring.
Haoyuan Zhu, Lin Du, Xilin Liu et al.· Annals of Biomedical Enginee...· 0 citations
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