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Event-based sampled ECG morphology reconstruction through self-similarity
In this work, we leverage the self-similarity of the electrocardiogram (ECG) signal to recover missing features in event-based sampled ECG signals, dynamically selecting patient-representative templates together with a novel dynamic time warping algorithm to infer the morphology of event-based sampled heartbeats.
An Error-Based Approximation Sensing Circuit for Event-Triggered, Low Power Wearable Sensors
At the same time, multi-channel signals (like the six-dimensional accelerometer signal) can still benefit from the designed circuit, achieving a reduction factor up to 80% with minor performance degradation.
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