Literature DB >> 33903610

Classification of patients with Alzheimer's disease using the arterial pulse spectrum and a multilayer-perceptron analysis.

Shun-Ku Lin1,2,3, Hsin Hsiu4,5, Hsi-Sheng Chen6, Chang-Jen Yang6.   

Abstract

Cerebrovascular atherosclerosis has been identified as a prominent pathological feature of Alzheimer's disease (AD); the link between vessel pathology and AD risk may also extend to extracranial arteries. This study aimed to determine the effectiveness of using arterial pulse-wave measurements and multilayer perceptron (MLP) analysis in distinguishing between AD and control subjects. Radial blood pressure waveform (BPW) and finger photoplethysmography signals were measured noninvasively for 3 min in 87 AD patients and 74 control subjects. The 5-layer MLP algorithm employed evaluated the following 40 harmonic pulse indices: amplitude proportion and its coefficient of variation, and phase angle and its standard deviation. The BPW indices differed significantly between the AD patients (6247 pulses) and control subjects (6626 pulses). Significant intergroup differences were found between mild, moderate, and severe AD (defined by Mini-Mental-State-Examination scores). The hold-out test results indicated an accuracy of 82.86%, a specificity of 92.31%, and a 0.83 AUC of ROC curve when using the MLP-based classification between AD and Control. The identified differences can be partly attributed to AD-induced changes in vascular elastic properties. The present findings may be meaningful in facilitating the development of a noninvasive, rapid, inexpensive, and objective method for detecting and monitoring the AD status.

Entities:  

Year:  2021        PMID: 33903610     DOI: 10.1038/s41598-021-87903-7

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  1 in total

Review 1.  Pulse wave analysis and arterial stiffness.

Authors:  I B Wilkinson; J R Cockcroft; D J Webb
Journal:  J Cardiovasc Pharmacol       Date:  1998       Impact factor: 3.105

  1 in total
  2 in total

1.  Discrimination of the Cognitive Function of Community Subjects Using the Arterial Pulse Spectrum and Machine-Learning Analysis.

Authors:  Hsin Hsiu; Shun-Ku Lin; Wan-Ling Weng; Chaw-Mew Hung; Che-Kai Chang; Chia-Chien Lee; Chao-Tsung Chen
Journal:  Sensors (Basel)       Date:  2022-01-21       Impact factor: 3.576

2.  Multi-Dimensional and Objective Assessment of Motion Sickness Susceptibility Based on Machine Learning.

Authors:  Cong-Cong Li; Zhuo-Ru Zhang; Yu-Hui Liu; Tao Zhang; Xu-Tao Zhang; Han Wang; Xiao-Cheng Wang
Journal:  Front Neurol       Date:  2022-04-01       Impact factor: 4.086

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.