对不同运动亚型帕金森病患者进行基于可穿戴传感器的步态定量分析

IF 12.4 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Weishan Zhang, Yun Ling, Zhonglue Chen, Kang Ren, Shengdi Chen, Pei Huang, Yuyan Tan
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引用次数: 0

摘要

步态障碍是帕金森病最常见的致残性症状之一,并随着病情的发展而加重。对亚型特异性步态障碍的早期检测和诊断以及进展监测有助于对帕金森病患者实施有效的预防性个性化治疗。然而,目前尚未对帕金森病及其运动亚型的步态特征进行全面研究。为了全面客观地描述步态改变的特征,并确定用于早期诊断、亚型区分和疾病严重程度监测的潜在步态生物标志物。我们使用可穿戴传感器分析了 24 名震颤主导型(TD)和 20 名姿势不稳定步态困难(PIGD)主导型早期帕金森病患者以及 39 名匹配的健康对照组(HC)在定时起立和前进测试中与上肢/下肢、躯干和腰部以及姿势转换相关的步态参数。结果显示:(1)TD 组和 PIGD 组均表现出双侧下肢和多患侧(MAS)手臂的后摆幅度受限、躯干和腰部在冠状面上的旋转幅度减小以及转弯效率低。接受者操作特征(ROC)分析表明,这些客观步态特征在区分 PD 和 HC 亚型方面具有很高的鉴别价值,其曲线下面积(AUC)值为 0.7~0.9 (p < 0.01)。(2)TD 和 PIGD 患者在出现临床明显的步态障碍之前存在微妙但可测量的步态差异。(3)在TD和PIGD亚型中,特定步态参数与疾病严重程度显著相关。基于可穿戴传感器的客观步态生物标志物可通过早期诊断、亚型区分和疾病严重程度监测,促进对帕金森病亚型进行及时和个性化的步态治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Wearable sensor-based quantitative gait analysis in Parkinson’s disease patients with different motor subtypes

Wearable sensor-based quantitative gait analysis in Parkinson’s disease patients with different motor subtypes

Wearable sensor-based quantitative gait analysis in Parkinson’s disease patients with different motor subtypes
Gait impairments are among the most common and disabling symptoms of Parkinson’s disease and worsen as the disease progresses. Early detection and diagnosis of subtype-specific gait deficits, as well as progression monitoring, can help to implement effective and preventive personalized treatment for PD patients. Yet, the gait features have not been fully studied in PD and its motor subtypes. To characterize comprehensive and objective gait alterations and to identify the potential gait biomarkers for early diagnosis, subtype differentiation, and disease severity monitoring. We analyzed gait parameters related to upper/lower limbs, trunk and lumbar, and postural transitions from 24 tremor-dominant (TD) and 20 postural instability gait difficulty (PIGD) dominant PD patients who were in early stage and 39 matched healthy controls (HC) during the Timed Up and Go test using wearable sensors. Results show: (1) Both TD and PIGD groups showed restricted backswing range in bilateral lower extremities and more affected side (MAS) arm, reduced trunk and lumbar rotation range in the coronal plane, and low turning efficiency. The receiver operating characteristic (ROC) analysis revealed these objective gait features had high discriminative value in distinguishing both PD subtypes from the HC with the area under the curve (AUC) values of 0.7~0.9 (p < 0.01). (2) Subtle but measurable gait differences existed between TD and PIGD patients before the onset of clinically apparent gait impairment. (3) Specific gait parameters were significantly associated with disease severity in TD and PIGD subtypes. Objective gait biomarkers based on wearable sensors may facilitate timely and personalized gait treatments in PD subtypes through early diagnosis, subtype differentiation, and disease severity monitoring.
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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