Fig. 6: Experimental demonstration and scalability of f-MDPE for ECG diagnosis. | Nature Communications

Fig. 6: Experimental demonstration and scalability of f-MDPE for ECG diagnosis.

From: Flexible self-rectifying synapse array for energy-efficient edge multiplication in electrocardiogram diagnosis

Fig. 6

a Photograph of the integrated system: ECG sensor, f-MDPE, and f-MDPE controller integrated on a control PC. ECG diagnosis of N pulses from the b MIT-BIH dataset and c personal signals acquired from the ECG sensor. d Schematics of the scaled-up 1D convolutional neural network (1D CNN). e Recognition rates of ECG diagnosis for the proposed 1D CNN architectures. The recognition rate is saturated in the 2k model. f Energy consumption comparisons of the f-MDPE algorithm and conventional processors (CPU and GPU) for inferring a single heartbeat signal from the 2k model. g Energy consumption per bit and area per cell comparisons of the f-MDPE and flexible or stretchable memristive arrays. The green squares represent flexible arrays, and the blue rectangles represent stretchable arrays.

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