A review of emergent intelligent systems for the detection of Parkinson's disease.

IF 3.2 4区医学 Q2 ENGINEERING, BIOMEDICAL Biomedical Engineering Letters Pub Date : 2023-09-20 eCollection Date: 2023-11-01 DOI:10.1007/s13534-023-00319-2

Samiappan Dhanalakshmi, Ramesh Sai Maanasaa, Ramesh Sai Maalikaa, Ramalingam Senthil

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Abstract

Parkinson's disease (PD) is a neurodegenerative disorder affecting people worldwide. The PD symptoms are divided into motor and non-motor symptoms. Detection of PD is very crucial and essential. Such challenges can be overcome by applying artificial intelligence to diagnose PD. Many studies have also proposed the implementation of computer-aided diagnosis for the detection of PD. This systematic review comprehensively analyzed all appropriate algorithms for detecting and assessing PD based on the literature from 2012 to 2023 which are conducted as per PRISMA model. This review focused on motor symptoms, namely handwriting dynamics, voice impairments and gait, multimodal features, and brain observation using single photon emission computed tomography, magnetic resonance and electroencephalogram signals. The significant challenges are critically analyzed, and appropriate recommendations are provided. The critical discussion of this review article can be helpful in today's PD community in such a way that it allows clinicians to provide proper treatment and timely medication.

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帕金森病检测的紧急智能系统综述。

帕金森病（PD）是一种影响全世界的神经退行性疾病。帕金森病症状分为运动症状和非运动症状。PD的检测是至关重要的。将人工智能应用于PD诊断可以克服这些挑战。许多研究也提出了应用计算机辅助诊断来检测PD。本系统综述基于2012年至2023年根据PRISMA模型进行的文献，全面分析了检测和评估PD的所有适当算法。这篇综述的重点是运动症状，即笔迹动力学、语音障碍和步态、多模式特征，以及使用单光子发射计算机断层扫描、磁共振和脑电图信号进行的大脑观察。对重大挑战进行了批判性分析，并提出了适当的建议。这篇综述文章的批判性讨论可以帮助当今的帕金森病社区，使临床医生能够提供适当的治疗和及时的药物治疗。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biomedical Engineering Letters ENGINEERING, BIOMEDICAL-

CiteScore

6.80

自引率

0.00%

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期刊介绍： Biomedical Engineering Letters (BMEL) aims to present the innovative experimental science and technological development in the biomedical field as well as clinical application of new development. The article must contain original biomedical engineering content, defined as development, theoretical analysis, and evaluation/validation of a new technique. BMEL publishes the following types of papers: original articles, review articles, editorials, and letters to the editor. All the papers are reviewed in single-blind fashion.