Inertial-Based Dual-Task Gait Normalcy Index at Turns: A Potential Novel Gait Biomarker for Early-Stage Parkinson’s Disease

IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-01-29 DOI:10.1109/TNSRE.2025.3535696
Lin Meng;Xiaofei Zhang;Yu Shi;Xinge Li;Jun Pang;Lei Chen;Xiaodong Zhu;Rui Xu;Dong Ming
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Abstract

As one of the main motor indicators of Parkinson’s disease (PD), postural instability and gait disorder (PIGD) might manifest in various but subtle symptoms at early stage resulting in relatively high misdiagnosis rate. Quantitative gait assessment under dual task or complex motor task (i.e., turning) may contribute to better understanding of PIGD and provide a better diagnostic indicator of early-stage PD. However, few studies have explored gait deviation evaluation algorithms under a complex dual task that reflect disease specificity. In this work, we proposed a novel inertial-based gait normalcy index (GNI) based on inertial-based quantitative gait assessment model to characterize the overall gait performance during both straight walking and turning with or without serial-3 subtraction task. The factor of group and task on the GNI variable was investigated and the feasibility of GNI to improve early-stage PD diagnostic performance was validated. The experimental results showed that the task paradigm is a significant factor on GNI performance where the dual-task GNI at turn had the best discriminating ability between early PD and HC (AUC =0.992) and was significantly correlated with UPDRS III (r =0.81), MMSE(r =0.57) and Mini-BEST(r =0.65). We also observed that the turning-based GNI has larger effect size compared to clinical scales, demonstrating that GNI during turning can reflect the changes of functional mobility in rehabilitation for the early PD. Our work offers an innovative and potential gait biomarker for early-stage PD diagnostics and provides a new perspective into gait performance of complex dual task and its application in early PD.
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基于惯性的双任务步态正常指数:早期帕金森病的一种潜在的新型步态生物标志物
作为帕金森病(PD)的主要运动指标之一,姿势不稳定和步态障碍(PIGD)在早期可能表现为多种但不易察觉的症状,误诊率较高。双任务或复杂运动任务(如转身)下的定量步态评估可能有助于更好地了解PIGD,并为早期PD提供更好的诊断指标。然而,很少有研究探索反映疾病特异性的复杂双重任务下的步态偏差评估算法。在这项工作中,我们提出了一种基于惯性定量步态评估模型的新的基于惯性的步态正常指数(GNI)来表征在有或没有串行-3减法任务时直线行走和转弯的整体步态性能。研究了群体和任务对GNI变量的影响,验证了GNI提高早期PD诊断效能的可行性。实验结果表明,任务范式是影响GNI表现的重要因素,其中双任务GNI对早期PD和HC的区分能力最佳(AUC =0.992),与UPDRS III (r =0.81)、MMSE(r =0.57)和Mini-BEST(r =0.65)显著相关。我们还观察到,与临床量表相比,基于旋转的GNI具有更大的效应量,说明旋转过程中的GNI可以反映早期PD康复过程中功能活动能力的变化。本研究为帕金森病早期诊断提供了一种具有创新潜力的步态生物标志物,为研究复杂双重任务的步态表现及其在早期帕金森病中的应用提供了新的视角。
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
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
期刊最新文献
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