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一种新的腕部佩戴工具,用于支持帕金森运动综合征的诊断。

A New Wrist-Worn Tool Supporting the Diagnosis of Parkinsonian Motor Syndromes.

机构信息

Faculty of Medicine and Surgery, Catholic University of the Sacred Heart, Sede di Potenza, 85100 Potenza, Italy.

R&D Department, Biomedical Lab SRL, 85100 Potenza, Italy.

出版信息

Sensors (Basel). 2024 Mar 19;24(6):1965. doi: 10.3390/s24061965.

DOI:10.3390/s24061965
PMID:38544228
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10975887/
Abstract

To date, clinical expert opinion is the gold standard diagnostic technique for Parkinson's disease (PD), and continuous monitoring is a promising candidate marker. This study assesses the feasibility and performance of a new wearable tool for supporting the diagnosis of Parkinsonian motor syndromes. The proposed method is based on the use of a wrist-worn measuring system, the execution of a passive, continuous recording session, and a computation of two digital biomarkers (i.e., motor activity and rest tremor index). Based on the execution of some motor tests, a second step is provided for the confirmation of the results of passive recording. In this study, fifty-nine early PD patients and forty-one healthy controls were recruited. The results of this study show that: (a) motor activity was higher in controls than in PD with slight tremors at rest and did not significantly differ between controls and PD with mild-to-moderate tremor rest; (b) the tremor index was smaller in controls than in PD with mild-to-moderate tremor rest and did not significantly differ between controls and PD patients with slight tremor rest; (c) the combination of the said two motor parameters improved the performances in differentiating controls from PD. These preliminary findings demonstrate that the combination of said two digital biomarkers allowed us to differentiate controls from early PD.

摘要

迄今为止,临床专家意见是帕金森病 (PD) 的金标准诊断技术,而连续监测是一种很有前途的候选标志物。本研究评估了一种新的可穿戴工具在支持帕金森运动综合征诊断方面的可行性和性能。该方法基于使用腕戴式测量系统,执行被动、连续的记录过程,并计算两个数字生物标志物(即运动活动和静止震颤指数)。基于执行一些运动测试,为被动记录结果的确认提供了第二步。在这项研究中,招募了 59 名早期帕金森病患者和 41 名健康对照者。研究结果表明:(a) 运动活动在有轻微静止震颤的对照组中高于 PD 组,而在有轻度至中度静止震颤的对照组和 PD 组之间没有显著差异;(b) 震颤指数在有轻度至中度静止震颤的对照组中小于 PD 组,而在有轻微静止震颤的对照组和 PD 组之间没有显著差异;(c) 这两个运动参数的组合提高了区分对照组和 PD 的性能。这些初步发现表明,这两个数字生物标志物的组合使我们能够区分对照组和早期 PD。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/1e1967400f4d/sensors-24-01965-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/3f3e4db46bd9/sensors-24-01965-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/2d5d8698fe85/sensors-24-01965-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/6606bb01f0d7/sensors-24-01965-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/12dbdedf091c/sensors-24-01965-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/1e1967400f4d/sensors-24-01965-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/3f3e4db46bd9/sensors-24-01965-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/2d5d8698fe85/sensors-24-01965-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/6606bb01f0d7/sensors-24-01965-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/12dbdedf091c/sensors-24-01965-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d921/10975887/1e1967400f4d/sensors-24-01965-g005.jpg

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Machine Learning-Assisted Speech Analysis for Early Detection of Parkinson's Disease: A Study on Speaker Diarization and Classification Techniques.基于机器学习的帕金森病早期检测语音分析:说话人分割和分类技术研究。
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Clinical assessment of a new wearable tool for continuous and objective recording of motor fluctuations and ON/OFF states in patients with Parkinson's disease.
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