Electrocardiogram (ECG) heartbeat classification plays a vital role in early diagnosis and effective treatment, which provide opportunities for earlier prevention and intervention. In an effort to continuously monitor and detect abnormalities in patients’ ECG signals on portable devices, this paper present a lightweight ECG heartbeat classification method based on a spiking neural network (SNN), a relatively shallow SNN model integrated with a channel-wise attentional module. We further explore the best-optimized architecture, which benefits from leveraging the full advantages of the SNN potential with the attention mechanism to process the classification task at low power and capture prominent features concerning the time, morphology, and multi-channel representations of the ECG signal. Results show that our model achieves overall classification accuracy of 98.26%, sensitivity of 94.75%, and F1 score of 89.09% on the MIT-BIH database, with energy consumption of 346.33 μJ per beat and runtime of 1.37 ms. Moreover, we have conducted multiple experiments to compare against current state-of-the-art methods using their assessment strategies to evaluate our model implementation on FPGA. So far, our work achieves comparable overall performance with all the literature in terms of classification accuracy, energy consumption, and real-time capability.

Neuroinflammation plays a crucial role in the pathogenesis and progression of Alzheimer's disease (AD). The Sterile Alpha and Toll Interleukin Receptor Motif-containing protein 1 (SARM1) has been shown to promote axonal degeneration and is involved in neuroinflammation. However, the role of SARM1 in AD remains unclear. In this study, we found that SARM1 was reduced in hippocampal neurons of AD model mice. Interestingly, conditional knockout (CKO) of SARM1 in the central nervous system (CNS, SARM1 Nestin -CKO mice) delayed the cognitive decline in APP/PS1 AD model mice. Furthermore, SARM1 deletion reduced the Aβ deposition and inflammatory infiltration in the hippocampus and inhibited neurodegeneration in APP/PS1 AD model mice. Further investigation into the underlying mechanisms revealed that the signaling of tumor necrosis factor-α (TNF-α) was downregulated in the hippocampus tissues of APP/PS1;SARM1 Nestin -CKO mice, thereby alleviating the cognitive decline, Aβ deposition and inflammatory infiltration. These findings identify unrecognized functions of SARM1 in promoting AD and reveal the SARM1-TNF-α pathway in AD model mice.