# Data fusion of multivariate time series: Application to noisy 12-lead ECG signals

arXiv: https://arxiv.org/abs/1803.01488 · HTML: https://mlsanity.com/paper/1803.01488/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Mar 2018.

## Built on by (most cited first, 1 of 1)

- [PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series](https://mlsanity.com/paper/2110.00071/) (2021)

## Abstract (arXiv)

12-lead ECG signals fusion is crucial for further ECG signal processing. In this paper, a novel fusion data algorithm is proposed. In the method, 12-lead ECG signals are appropriately converted to a single-lead physiological signal via the idea of the local weighted linear prediction algorithm. For effectively inheriting the quality characteristics of the 12-lead ECG signals, the fuzzy inference system is rationally designed to estimate the weighted coefficient in our algorithm. Experimental results indicate that the algorithm can obtain desirable results on synthetic ECG signals, noisy ECG signals and realistic ECG signals.