Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: LSTM-Based ECG Classification for Continuous Monitoring on Personal
  Wearable Devices   Objective: A novel ECG classification algorithm is proposed for continuous
cardiac monitoring on wearable devices with limited processing capacity.
Methods: The proposed solution employs a novel architecture consisting of
wavelet transform and multiple LSTM recurrent neural networks. Results:
Experimental evaluations show superior ECG classification performance compared
to previous works. Measurements on different hardware platforms show the
proposed algorithm meets timing requirements for continuous and real-time
execution on wearable devices. Conclusion: In contrast to many
compute-intensive deep-learning based approaches, the proposed algorithm is
lightweight, and therefore, brings continuous monitoring with accurate
LSTM-based ECG classification to wearable devices. Significance: The proposed
algorithm is both accurate and lightweight. The source code is available online
[1].

29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin