Network architecture of the classification model.

<p>The first 1D-CNN block had 4 parallel branches, including 1 × 1, 1 × 3 and 1 × 5 convolutions, along with a 1 × 3 max pooling branch, each with 8 filters used for convolution. The outputs of the four branches were combined with the original input through residual connections. The second 1D-...

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Bibliographic Details
Main Author:	Zhaohui Zhu (349376) (author)
Other Authors:	E Wu (1520830) (author), Pengfei Leng (643486) (author), Jiajun Sun (8815641) (author), Mingming Ma (584228) (author), Zhigeng Pan (12663910) (author)
Published:	2025
Subjects:	Developmental Biology Science Policy Biological Sciences not elsewhere classified recruited 58 age instantaneous movement speed compatible method requires clinical rating scales analyze movement abnormalities analyze motion data 30 healthy controls based drawing tasks analyze drawing tasks using parallel 1d convenient pd assessment based digital assessments 2 %&# 8722 tasks achieved 91 spiral drawing tasks finger drawing pd ), independent assessments hybrid 1d 2 %) xlink "> wave lines wave ). two smartphone technical feasibility study establishes study developed spiral drawings smartphone screens sampling frequency resting tremor remote healthcare patient monitoring neuroimaging modalities matched participants manifests clinically grade smartphones finger interactions finger drawings facilitates cost existing approaches enables operator early detection convolutional branches bidirectional grus aging populations 7 years 60 hz 43 %)
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Network architecture of the classification model.

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