Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Department of Mathematics, Informatics and Cybernetics, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Czech Republic.
Mov Disord. 2024 Oct;39(10):1752-1762. doi: 10.1002/mds.29921. Epub 2024 Jul 12.
Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone.
The aim was to develop a fully automated and noise-resistant smartphone-based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real-world scenario.
This cross-sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in-person assessments at the clinic.
A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high-quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening.
We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
言语障碍是帕金森病（PD）最初出现的运动表现之一，可以通过智能手机进行测量。
旨在开发一种完全自动化且抗噪的基于智能手机的系统，该系统可以在现实场景中对孤立性快速眼动睡眠行为障碍（iRBD）患者进行无干扰的帕金森病前驱言语障碍筛查。
这项横断面研究通过开发的智能手机应用程序，比较了 iRBD 个体的日常语音通话数据与早期 PD 患者和健康对照者的语音通话数据。参与者还在智能手机上主动、常规地阅读一段短文。智能手机数据在诊所的标准现场评估后最多持续收集 3 个月。
从 72 名参与者中提取了 3525 个电话，共 5990 分钟的预处理语音，其中包括 21 名 iRBD 患者、26 名 PD 患者和 25 名对照者。iRBD 患者和对照组之间的曲线下面积高达 0.85，表明被动和主动智能手机数据的组合提供了与使用高质量麦克风的实验室检查相当甚至更敏感的评估。在 iRBD 中最敏感的特征包括电话通话中不准确的元音发音（P=0.03）和阅读时的单音（P=0.05），可以诱发前驱神经退行性变。大约 9 个电话对应 18 分钟的语音就足以获得最佳的筛查敏感性。
我们认为所开发的工具广泛适用于深度纵向数字表型数据，未来可应用于神经保护试验、深部脑刺激优化、神经精神病学、言语治疗、人群筛查等领域。 © 2024 作者。运动障碍由 Wiley 期刊公司代表国际帕金森和运动障碍协会出版。
