Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Novel Blood Pressure Waveform Reconstruction from Photoplethysmography
  using Cycle Generative Adversarial Networks   Continuous monitoring of blood pressure (BP)can help individuals manage their
chronic diseases such as hypertension, requiring non-invasive measurement
methods in free-living conditions. Recent approaches fuse Photoplethysmograph
(PPG) and electrocardiographic (ECG) signals using different machine and deep
learning approaches to non-invasively estimate BP; however, they fail to
reconstruct the complete signal, leading to less accurate models. In this
paper, we propose a cycle generative adversarial network (CycleGAN) based
approach to extract a BP signal known as ambulatory blood pressure (ABP) from a
clean PPG signal. Our approach uses a cycle generative adversarial network that
extends theGAN architecture for domain translation, and outperforms
state-of-the-art approaches by up to 2x in BP estimation.

21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph