Abstract：
BACKGROUND: Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson\'s disease (PD) and is measurable through smartphone.
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
摘要：
背景：言语功能障碍是帕金森氏病（PD）发展的初始运动表现之一，可以通过智能手机进行测量。
目的：目的是开发一种基于智能手机的全自动抗噪声系统，该系统可以在孤立的快速眼动睡眠行为障碍（iRBD）受试者中轻松筛查前驱帕金森病言语障碍。
方法：这项横断面研究定期评估，通过开发的智能手机应用程序，将iRBD患者的日常语音通话数据与早期PD患者和健康对照进行比较。参与者还进行了积极的，经常阅读他们的智能手机上的短文。在诊所进行标准的亲自评估后，连续收集智能手机数据长达3个月。
结果：从72名参与者中提取了3525个电话，这些电话导致了5990分钟的预处理语音，包括21名iRBD患者，26例PD患者，25个控制iRBD患者和对照组之间的曲线下面积为0.85，与使用高质量麦克风的实验室检查相比,被动和主动智能手机数据的组合提供了可比甚至更灵敏的评估.在iRBD中诱发前驱神经变性的最敏感特征包括电话中不精确的元音发音（P=0.03）和阅读中的单音发音（P=0.05）。对应于大约9个呼叫的18分钟的讲话足以获得最佳的筛选灵敏度。
结论：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，并在神经保护试验中具有未来的应用。深部脑刺激优化，神经精神病学,言语治疗,人群筛查,和超越。©2024作者（S）。由WileyPeriodicalsLLC代表国际帕金森症和运动障碍协会出版的运动障碍。
目的：目的是开发一种基于智能手机的全自动抗噪声系统，该系统可以在孤立的快速眼动睡眠行为障碍（iRBD）受试者中轻松筛查前驱帕金森病言语障碍。
方法：这项横断面研究定期评估，通过开发的智能手机应用程序，将iRBD患者的日常语音通话数据与早期PD患者和健康对照进行比较。参与者还进行了积极的，经常阅读他们的智能手机上的短文。在诊所进行标准的亲自评估后，连续收集智能手机数据长达3个月。
结果：从72名参与者中提取了3525个电话，这些电话导致了5990分钟的预处理语音，包括21名iRBD患者，26例PD患者，25个控制iRBD患者和对照组之间的曲线下面积为0.85，与使用高质量麦克风的实验室检查相比,被动和主动智能手机数据的组合提供了可比甚至更灵敏的评估.在iRBD中诱发前驱神经变性的最敏感特征包括电话中不精确的元音发音（P=0.03）和阅读中的单音发音（P=0.05）。对应于大约9个呼叫的18分钟的讲话足以获得最佳的筛选灵敏度。
结论：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，并在神经保护试验中具有未来的应用。深部脑刺激优化，神经精神病学,言语治疗,人群筛查,和超越。©2024作者（S）。由WileyPeriodicalsLLC代表国际帕金森症和运动障碍协会出版的运动障碍。
