AbstractDigital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson’s disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant’s own living environment.

摘要远程监测症状的数字生物标志物有可能通过对参与者自身生活环境中收集的症状和体征进行客观和反复的测量，彻底改变未来帕金森病（PD）疾病缓解试验的结果评估。

This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field.

该生物标志物领域正在迅速发展，以评估PD的运动特征，但非运动领域却落后。在这里，我们系统地回顾和评估正在开发的用于测量PD非运动症状的数字生物标志物。我们还考虑了PD领域之外的相关发展。

We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials.

我们专注于技术准备水平，并评估已识别的数字非运动生物标志物是否具有测量疾病进展的潜力，涵盖从前驱到晚期疾病阶段的范围。此外，我们为这些生物标志物在试验中的未来部署提供了前景。

We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest.

我们发现，各种可穿戴设备在测量自主神经功能，便秘和睡眠特征（包括REM睡眠行为障碍）方面显示出很高的前景。神经精神症状的生物标志物不太发达，但在非PD人群中显示出越来越高的准确性。大多数生物标志物尚未被验证用于PD的特定用途，并且它们对捕获疾病进展的敏感性尚未针对前驱PD进行测试，其中对数字进展生物标志物的需求最大。

External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice..

将非运动生物标志物整合到研究中，并最终整合到日常临床实践中，仍然需要在现实环境和大型纵向队列中进行外部验证。。

IntroductionSince the last decade, the quest for disease-modifying therapies in Parkinson’s disease (PD) has intensified1. Measuring clinical disease progression accurately and objectively during these trials is of great importance to assess treatment efficacy. Currently, gold-standard outcome measures for such trials are the Movement Disorders Society scales for motor symptoms and daily functioning2.

引言自过去十年以来，帕金森病（PD）对疾病缓解疗法的追求不断加强1。在这些试验中准确客观地测量临床疾病进展对于评估治疗效果非常重要。目前，此类试验的金标准结果指标是运动障碍协会运动症状和日常功能量表2。

Use of these scales comes with several challenges: they require substantial assessment time, are conducted episodically and are based on subjective interpretation, which leads to considerable measurement errors over time3.In the past decade, we have seen tangible advancements in the remote digital assessment of the motor symptoms of PD, both in clinical practice and in research settings4,5,6,7,8.

这些量表的使用带来了一些挑战：它们需要大量的评估时间，是偶发性的，并且基于主观解释，随着时间的推移会导致相当大的测量误差3。在过去的十年中，我们在远程数字评估方面取得了实实在在的进展。PD的运动症状，无论是在临床实践中还是在研究环境中4,5,6,7,8。

Digital sensors can monitor symptoms non-invasively and often passively (without need for active human intervention). The quantification of symptoms and signs at a higher frequency and for longer time frames (even continuously for several digital outcomes) makes such digital biomarkers a more objective, more convenient and potentially more sensitive alternative to the episodic in-clinic assessment of disease progression.

数字传感器可以无创地监测症状，通常是被动的（不需要主动的人为干预）。在更高的频率和更长的时间范围内（甚至连续用于几个数字结果）对症状和体征进行量化，使得这种数字生物标志物成为疾病进展临床评估中更客观，更方便且可能更敏感的替代方案。

As such, several digital biomarkers of motor signs have been included in research settings9,10,11.Much less attention has been paid to non-motor symptoms, in both research and clinical practice, apart from olfactory dysfunction as a supportive criterion in the MDS diagnostic criteria12. Yet, non-motor symptoms have a substantial negative impact on quality of life in affected individuals13, precede motor symptoms during the prodromal phase up to two decades14 and are subject to daily fluctuations just as motor symptoms, favoring longitudinal measurement over episod.

。然而，非运动症状对受影响个体的生活质量产生重大负面影响13，在前驱期运动症状之前长达二十年14，并且与运动症状一样每天都会出现波动，有利于纵向测量而不是episod。

Validity of the biomarker versus the (gold-)standard, with a specific focus on discriminant and criterion validity.

生物标志物与（金）标准的有效性，特别关注判别和标准有效性。

Reliability, based on reported test-retest reliability.

可靠性，基于报告的重测信度。

Feasibility, based on the following subdomains: user friendliness (including stigmatization), compliance, implementation and practicality (how easily is it deployed in the participant’s context), based on both quantitative variables and qualitative interpretation. This analysis was conducted together with patient researchers, informed by a roadmap for implementation of patient-centered digital outcomes172..

可行性，基于以下子域：基于定量变量和定性解释的用户友好性（包括污名化），合规性，实施性和实用性（在参与者的背景下部署有多容易）。这项分析是与患者研究人员一起进行的，并根据以患者为中心的数字成果实施路线图172进行的。。

Sensitivity to disease progression, as measured by serial measurements in a longitudinal study, if applicable.

如适用，通过纵向研究中的连续测量来测量对疾病进展的敏感性。

Based on these results, a grade for the stage of development within a specific symptom category was made. The stage of development was based on the Technological Readiness Level (TRL), as defined by the most recent European Union definitions which we adapted to fit the field of digital biomarkers and medical monitoring devices in general (Fig.

根据这些结果，对特定症状类别的发展阶段进行了评分。发展阶段是基于技术准备水平（TRL），正如最新的欧盟定义所定义的那样，我们适应了数字生物标志物和医疗监测设备领域（图）。

2)187. Developmental stages range from development or proof of concept (TRL1, lowest), to public availability or commercialization applied in a longitudinal study (TRL9, highest) via several early and late validation stages in either lab setting or free-living conditions. We assigned a TRL per non-motor symptom or sign separately for the prodromal phase and for the clinically manifest phase.

2） 187年。发展阶段包括从开发或概念验证（TRL1，最低），到在实验室环境或自由生活条件下通过几个早期和晚期验证阶段在纵向研究（TRL9，最高）中应用的公共可用性或商业化。我们分别为前驱期和临床表现期分配了每个非运动症状或体征的TRL。

Finally, using a structured process in which both performance metrics, TRL and applicability in PD were assessed, all authors agreed on a final top 3 of digital biomarkers per non-motor symptom to be presented in one main table. The remainder of the included studies was added to Supplementary Table 2.Fig.

最后，使用一个结构化的过程，其中评估了性能指标，TRL和PD的适用性，所有作者都同意在一个主表中列出每个非运动症状的数字生物标志物的最终前三名。其余纳入的研究被添加到补充表2中。

2Technological readiness level (TRL)190 for digital biomarkers in clinical trials.Full size image.

2临床试验中数字生物标志物的技术准备水平（TRL）190。全尺寸图像。

Data availability

数据可用性

All data generated or analyzed during this study are included in this published article and its supplementary materials. A reference manager file is available from the authors.

本研究期间生成或分析的所有数据均包含在本文及其补充材料中。作者提供了参考管理器文件。

ReferencesMcFarthing, K. et al. Parkinson’s Disease Drug Therapies in the Clinical Trial Pipeline: 2023 Update. J. Parkinsons Dis. 13, 427–439 (2023).CAS

参考文献McFarthing，K。等人。临床试验管道中的帕金森病药物治疗：2023年更新。J、 。13427-439（2023）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Goetz, C. G. et al. Movement Disorder Society‐sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS‐UPDRS): scale presentation and clinimetric testing results. Mov. Disord. 23, 2129–2170 (2008).PubMed

Goetz，C.G.等人，《运动障碍学会赞助的统一帕金森病评定量表（MDS-UPDRS）修订版：量表呈现和临床测试结果》。莫夫。混乱。232129-2170（2008）。PubMed出版社

Google Scholar

谷歌学者

Evers, L. J. W., Krijthe, J. H., Meinders, M. J., Bloem, B. R. & Heskes, T. M. Measuring Parkinson’s disease over time: The real-world within-subject reliability of the MDS-UPDRS. Mov. Disord. 34, 1480–1487 (2019).PubMed

Evers，L.J.W.，Krijthe，J.H.，Meinders，M.J.，Bloem，B.R.＆Heskes，T.M.测量帕金森病随时间的变化：MDS-UPDRS.Mov的真实受试者内部可靠性。混乱。341480-1487（2019）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Artusi, C. A. et al. Implementation of Mobile Health Technologies in Clinical Trials of Movement Disorders: Underutilized Potential. Neurotherapeutics 17, 1736–1746 (2020).PubMed

Artusi，C.A.等人，《移动健康技术在运动障碍临床试验中的应用：未充分利用的潜力》。神经治疗学171736-1746（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Warmerdam, E. et al. Long-term unsupervised mobility assessment in movement disorders. Lancet Neurol. 19, 462–470 (2020).PubMed

Warmerdam，E.等人。运动障碍的长期无监督流动性评估。柳叶刀神经学。19462-470（2020）。PubMed出版社

Google Scholar

谷歌学者

Zhan, A. et al. Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score. JAMA Neurol. 75, 876–880, (2018).PubMed

詹，A。等人。使用智能手机和机器学习来量化帕金森病的严重程度：移动帕金森病评分。JAMA Neurol。75876-880，（2018）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Burq, M. et al. Virtual exam for Parkinson’s disease enables frequent and reliable remote measurements of motor function. NPJ Digit. Med. 5, 65 (2022).PubMed

Burq，M。等人。帕金森病的虚拟检查可以频繁可靠地远程测量运动功能。NPJ数字。医学杂志5，65（2022）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Bloem, B. R., Post, E. & Hall, D. A. An Apple a Day to Keep the Parkinson’s Disease Doctor Away? Ann. Neurol. 93, 681–685 (2023).PubMed

Bloem，B.R.，Post，E.＆Hall，D.A.每天吃一个苹果来远离帕金森病医生？安。神经病学。93681-685（2023）。PubMed出版社

Google Scholar

谷歌学者

Lipsmeier, F. et al. Reliability and validity of the Roche PD Mobile Application for remote monitoring of early Parkinson’s disease. Sci. Rep. 12, 12081 (2022).CAS

Lipsmeier，F。等人。罗氏PD移动应用程序远程监测早期帕金森病的可靠性和有效性。科学。代表1212081（2022）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Mirelman, A. et al. Arm swing as a potential new prodromal marker of Parkinson’s disease. Mov. Disord. 31, 1527–1534 (2016).CAS

Mirelman，A。等人。手臂摆动作为帕金森病的潜在新前驱标志物。莫夫。混乱。311527-1534（2016）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Schalkamp, A. K., Peall, K. J., Harrison, N. A. & Sandor, C. Wearable movement-tracking data identify Parkinson’s disease years before clinical diagnosis. Nat. Med., https://doi.org/10.1038/s41591-023-02440-2 (2023).Postuma, R. B. et al. MDS clinical diagnostic criteria for Parkinson’s disease.

Schalkamp，A.K.，Peall，K.J.，Harrison，N.A。和Sandor，C。可穿戴运动跟踪数据在临床诊断前几年识别帕金森氏病。自然医学。，https://doi.org/10.1038/s41591-023-02440-2（2023年）。Postuma，R.B.等人，《帕金森病的MDS临床诊断标准》。

Mov. Disord. 30, 1591–1601 (2015).PubMed .

莫夫。混乱。301591-1601（2015）。PubMed。

Google Scholar

谷歌学者

Martinez-Martin, P., Rodriguez-Blazquez, C., Kurtis, M. M., Chaudhuri, K. R. & Group, N. V. The impact of non-motor symptoms on health-related quality of life of patients with Parkinson’s disease. Mov. Disord. 26, 399–406 (2011).PubMed

Martinez-Martin，P.，Rodriguez-Blazquez，C.，Kurtis，M.M.，Chaudhuri，K.R。＆Group，N.V。非运动症状对帕金森病患者健康相关生活质量的影响。莫夫。混乱。26399-406（2011）。PubMed出版社

Google Scholar

谷歌学者

Berg, D. et al. MDS research criteria for prodromal Parkinson’s disease. Mov. Disord. 30, 1600–1611 (2015).PubMed

Berg，D.等人，《前驱帕金森病的MDS研究标准》。莫夫。混乱。301600-1611（2015）。PubMed出版社

Google Scholar

谷歌学者

Martinez-Fernandez, R., Schmitt, E., Martinez-Martin, P. & Krack, P. The hidden sister of motor fluctuations in Parkinson’s disease: A review on nonmotor fluctuations. Mov. Disord. 31, 1080–1094 (2016).CAS

Martinez-Fernandez，R.，Schmitt，E.，Martinez-Martin，P。＆Krack，P。帕金森病运动波动的隐藏姐妹：非运动波动的综述。莫夫。混乱。311080-1094（2016）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

FDA. Patient-Focused Drug Development Guidance Series for Enhancing the Incorporation of the Patient’s Voice in Medical Product Development and Regulatory Decision Making (FDA, 2023).FDA. Framework for the Use of Digital Health Technologies in Drug and Biological Product Development (FDA, 2023).van Wamelen, D.

FDA。以患者为中心的药物开发指导系列，用于增强患者在医疗产品开发和监管决策中的声音（FDA，2023）。FDA。数字健康技术在药物和生物制品开发中的应用框架（FDA，2023年）。van Wamelen，D。

J. et al. Digital health technology for non-motor symptoms in people with Parkinson’s disease: Futile or future? Parkinsonism Relat. Disord. 89, 186–194 (2021).PubMed .

J、 帕金森病患者非运动症状的数字健康技术：徒劳还是未来？帕金森病相关。混乱。89186-194（2021）。PubMed。

Google Scholar

谷歌学者

Merola, A. et al. Technology-based assessment of motor and nonmotor phenomena in Parkinson disease. Expert Rev. Neurother. 18, 825–845 (2018).CAS

Merola，A.等人。基于技术的帕金森病运动和非运动现象评估。专家Rev.Neurother。18825-845（2018）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

Sigcha, L. et al. Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review. Expert Syst. Appl. 229, 120541 (2023).

Sigcha，L.等人。用于帕金森病诊断和监测的深度学习和可穿戴传感器：系统综述。专家系统。应用。229120541（2023）。

Google Scholar

谷歌学者

Darweesh, S. K. et al. Trajectories of prediagnostic functioning in Parkinson’s disease. Brain 140, 429–441 (2017).PubMed

Darweesh，S.K.等人。帕金森病的诊断前功能轨迹。大脑140429-441（2017）。PubMed出版社

Google Scholar

谷歌学者

McGregor, S. et al. The use of accelerometry as a tool to measure disturbed nocturnal sleep in Parkinson’s disease. npj Parkinsons Dis. 4, 1 (2018).PubMed

McGregor，S.等人。使用加速度计作为测量帕金森氏病夜间睡眠紊乱的工具。npj帕金森病。4,1（2018）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Madrid-Navarro, C. J. et al. Validation of a Device for the Ambulatory Monitoring of Sleep Patterns: A Pilot Study on Parkinson’s Disease. Front Neurol. 10, 356 (2019).PubMed

Madrid Navarro，C.J.等人，《睡眠模式动态监测装置的验证：帕金森病的初步研究》。前神经。10356（2019）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Mirelman, A. et al. Tossing and Turning in Bed: Nocturnal Movements in Parkinson’s Disease. Mov. Disord. 35, 959–968 (2020).PubMed

Mirelman，A.等人，《床上翻来覆去：帕金森氏病的夜间运动》。莫夫。混乱。35959-968（2020）。PubMed出版社

Google Scholar

谷歌学者

O’Dowd, S. T. et al. Longitudinal assessment of sleep in an incident Parkinson’s disease cohort. Mov. Disord. 31, S117 (2016).

O'Dowd，S.T.等人。帕金森病队列事件中睡眠的纵向评估。莫夫。混乱。31，S117（2016）。

Google Scholar

谷歌学者

Breen, D. P. et al. Sleep and circadian rhythm regulation in early parkinson disease. JAMA Neurol. 71, 589–595 (2014).PubMed

Breen，D.P.等人，《早期帕金森病的睡眠和昼夜节律调节》。JAMA Neurol。71589-595（2014）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Carlson, C. et al. Bed-based instrumentation for unobtrusive sleep quality assessment in severely disabled autistic children. Annu Int Conf. IEEE Eng. Med Biol. Soc. 2016, 4909–4912 (2016).PubMed

Carlson，C.等人。基于床的仪器，用于严重残疾自闭症儿童的无干扰睡眠质量评估。Annu Int Conf.IEEE工程医学生物学。Soc.20164909-4912（2016）。PubMed出版社

Google Scholar

谷歌学者

Li, S. & Chiu, C. A Smart Pillow for Health Sensing System Based on Temperature and Humidity Sensors. Sensors 18, https://doi.org/10.3390/s18113664 (2018).Filardi, M. et al. Objective rest-activity cycle analysis by actigraphy identifies isolated rapid eye movement sleep behavior disorder.

Li，S。＆Chiu，C。一种基于温度和湿度传感器的健康传感系统智能枕头。传感器18，https://doi.org/10.3390/s18113664（2018年）。Filardi，M。等人。通过活动描记术进行的客观休息-活动周期分析可识别孤立的快速眼动睡眠行为障碍。

Eur. J. Neurol. 27, 1848–1855 (2020).CAS .

欧洲神经科学杂志。27, 1848–1855 (2020).CAS。

PubMed

PubMed

Google Scholar

谷歌学者

Kemlink, D., Perinova, P., Dusek, P., Ruzicka, E. & Sonka, K. Actigraphic screening for the rapid eye movement sleep behavior disorder in Czech population. Sleep. Med. 40, e155 (2017).

Kemlink，D.，Perinova，P.，Dusek，P.，Ruzicka，E。＆Sonka，K。捷克人群快速眼动睡眠行为障碍的活动筛查。睡觉。医学40，e155（2017）。

Google Scholar

谷歌学者

Louter, M., Arends, J. B., Bloem, B. R. & Overeem, S. Actigraphy as a diagnostic aid for REM sleep behavior disorder in Parkinson’s disease. BMC Neurol. 14, 76 (2014).PubMed

Louter，M.，Arends，J.B.，Bloem，B.R。和Overeem，S。活动描记术作为帕金森病REM睡眠行为障碍的诊断辅助手段。BMC神经病学。14，76（2014）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Moerman, C. et al. Towards a handy screening tool for REM sleep behaviour disorder: RDBAct algorithm from wrist actigraphy data. J. Sleep Res. 29, https://doi.org/10.1111/jsr.13181 (2020).Raschella, F., Scafa, S., Puiatti, A., Martin Moraud, E. & Ratti, P. L. Actigraphy Enables Home Screening of Rapid Eye Movement Behavior Disorder in Parkinson’s Disease.

Moerman，C.等人。REM睡眠行为障碍的便捷筛查工具：来自手腕活动图数据的RDBAct算法。J、 Sleep Res.29，https://doi.org/10.1111/jsr.13181（2020年）。Raschella，F.，Scafa，S.，Puiatti，A.，Martin Moraud，E。＆Ratti，P.L。活动描记术可以在家中筛查帕金森氏病的快速眼动行为障碍。

Ann. Neurol., https://doi.org/10.1002/ana.26517 (2022).Stefani, A. et al. Screening for idiopathic REM sleep behavior disorder: Usefulness of actigraphy. Sleep 41, https://doi.org/10.1093/sleep/zsy053 (2018).Naismith, S. L., Rogers, N. L., Mackenzie, J., Hickie, I. B. & Lewis, S. J. The relationship between actigraphically defined sleep disturbance and REM sleep behaviour disorder in Parkinson’s Disease.

神经科。，https://doi.org/10.1002/ana.26517（2022年）。Stefani，A。等人。特发性REM睡眠行为障碍的筛查：活动描记术的有用性。睡眠41，https://doi.org/10.1093/sleep/zsy053（2018年）。Naismith，S.L.，Rogers，N.L.，Mackenzie，J.，Hickie，I.B。＆Lewis，S.J。帕金森病中活动定义的睡眠障碍与REM睡眠行为障碍之间的关系。

Clin. Neurol. Neurosurg. 112, 420–423 (2010).PubMed .

临床。神经病学。神经外科杂志112420-423（2010）。PubMed。

Google Scholar

谷歌学者

Kemlink, D., Perinova, P., Dusek, P., Ruzicka, E. & Sonka, K. Actigraphic differences in the rapid eye movement sleep behavior disorder patients. J. Sleep. Res. 27, 51 (2018).

。J、 睡觉。第27、51（2018）号决议。

Google Scholar

谷歌学者

Bolitho, S. J. et al. Objective measurement of daytime napping, cognitive dysfunction and subjective sleepiness in Parkinson’s disease. PLoS One 8, e81233 (2013).PubMed

Bolitho，S.J.等人。帕金森病患者白天午睡、认知功能障碍和主观嗜睡的客观测量。PLoS One 8，e81233（2013）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Kotschet, K. et al. Daytime sleep in Parkinson’s disease measured by episodes of immobility. Parkinsonism Relat. Disord. 20, 578–583 (2014).CAS

Kotschet，K。等人。帕金森氏病的白天睡眠通过不动发作来衡量。帕金森病相关。混乱。20578-583（2014）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

Kundinger, T., Sofra, N. & Riener, A. Assessment of the Potential of Wrist-Worn Wearable Sensors for Driver Drowsiness Detection. Sensors 20, https://doi.org/10.3390/s20041029 (2020).Leng, Y. et al. Excessive daytime sleepiness, objective napping and 11-year risk of Parkinson’s disease in older men.

Kundinger，T.，Sofra，N。＆Riener，A。评估手腕佩戴的可穿戴传感器用于驾驶员嗜睡检测的潜力。传感器20，https://doi.org/10.3390/s20041029（2020年）。Leng，Y.等人。老年男性白天过度嗜睡、客观打盹和患帕金森病11年的风险。

Int J. Epidemiol. 47, 1679–1686 (2018).PubMed .

国际流行病学杂志。47, 1679–1686 (2018).PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Memon, A. et al. Relationship between subjective and objective measures of sleepiness in Parkinson’s disease. In Movement Disorders. Conference: 1st Pan American Parkinson’s Disease and Movement Disorders Congress. Miami, FL United States 32, https://doi.org/10.1002/mds.26972 (2017).Huang, S., Li, J., Zhang, P.

Memon，A。等人。帕金森病嗜睡的主观和客观测量之间的关系。在运动障碍中。会议：第一届泛美帕金森病和运动障碍大会。美国佛罗里达州迈阿密32，https://doi.org/10.1002/mds.26972（2017年）。黄S.，李J.，张P。

& Zhang, W. Detection of mental fatigue state with wearable ECG devices. Int. J. Med. Inform. 119, 39–46 (2018).PubMed .

&Zhang，W。使用可穿戴心电图设备检测精神疲劳状态。国际医学通报。119,39-46（2018）。PubMed。

Google Scholar

谷歌学者

Zeng, Z. et al. Nonintrusive Monitoring of Mental Fatigue Status Using Epidermal Electronic Systems and Machine-Learning Algorithms. ACS Sens. 5, 1305–1313 (2020).CAS

Zeng，Z.等人。使用表皮电子系统和机器学习算法对精神疲劳状态进行非侵入性监测。ACS Sens.51305–1313（2020）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

Jeklin, A. T. et al. The association between heart rate variability, reaction time, and indicators of workplace fatigue in wildland firefighters. Int. Arch. Occup. Environ. health 94, 823–831 (2021).PubMed

Jeklin，A.T.等人，《野地消防员心率变异性、反应时间与工作场所疲劳指标之间的关系》。内景拱门。占领。环境。健康94823-831（2021）。PubMed出版社

Google Scholar

谷歌学者

Tseng, V. W. S., Valliappan, N., Ramachandran, V., Choudhury, T. & Navalpakkam, V. Digital biomarker of mental fatigue. npj Digital Med. 4, https://doi.org/10.1038/s41746-021-00415-6 (2021).Aqajari, S. A. H. et al. Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study.

Tseng，V.W.S.，Valliappan，N.，Ramachandran，V.，Choudhury，T。＆Navalpakkam，V。精神疲劳的数字生物标志物。npj数字医学4，https://doi.org/10.1038/s41746-021-00415-6（2021年）。Aqajari，S.A.H.等人。术后患者皮肤电活动疼痛评估工具：方法验证研究。

JMIR mHealth uHealth 9, e25258 (2021).PubMed .

JMIR mHealth uHealth 9，e25258（2021）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Atee, M., Hoti, K., Parsons, R. & Hughes, J. D. Pain Assessment in Dementia: Evaluation of a Point-of-Care Technological Solution. J. Alzheimers Dis. 60, 137–150 (2017).PubMed

Atee，M.，Hoti，K.，Parsons，R。＆Hughes，J.D。痴呆症的疼痛评估：对即时护理技术解决方案的评估。J、 阿尔茨海默病。60137-150（2017）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Jacobson, N. C. & O’Cleirigh, C. Objective digital phenotypes of worry severity, pain severity and pain chronicity in persons living with HIV. Br. J. Psychiatry 218, 165–167 (2021).PubMed

Jacobson，N.C。＆O'Cleirigh，C。HIV感染者担忧严重程度，疼痛严重程度和疼痛慢性的客观数字表型。Br.J.精神病学218165-167（2021）。PubMed出版社

Google Scholar

谷歌学者

Wallen, M. B., Hasson, D., Theorell, T., Canlon, B. & Osika, W. Possibilities and limitations of the Polar RS800 in measuring heart rate variability at rest. Eur. J. Appl Physiol. 112, 1153–1165 (2012).PubMed

Wallen，M.B.，Hasson，D.，Theorell，T.，Canlon，B。＆Osika，W。Polar RS800在测量静息心率变异性方面的可能性和局限性。Eur.J.Appl Physiol。1121153-1165（2012）。PubMed出版社

Google Scholar

谷歌学者

Gamelin, F. X., Berthoin, S. & Bosquet, L. Validity of the polar S810 heart rate monitor to measure R-R intervals at rest. Med Sci. Sports Exerc 38, 887–893 (2006).PubMed

Gamelin，F.X.，Berthoin，S。和Bosquet，L。polar S810心率监测仪测量静息时R-R间期的有效性。医学科学。体育锻炼38887-893（2006）。PubMed出版社

Google Scholar

谷歌学者

Nunan, D. et al. Levels of agreement for RR intervals and short-term heart rate variability obtained from the Polar S810 and an alternative system. Eur. J. Appl Physiol. 103, 529–537 (2008).PubMed

Nunan，D.等人。从Polar S810和替代系统获得的RR间期和短期心率变异性的一致性水平。Eur.J.Appl Physiol。103529-537（2008）。PubMed出版社

Google Scholar

谷歌学者

Stone, J. D. et al. Assessing the Accuracy of Popular Commercial Technologies That Measure Resting Heart Rate and Heart Rate Variability. Front. Sports Act. Living 3, 585870 (2021).PubMed

Stone，J.D.等人，《评估测量静息心率和心率变异性的流行商业技术的准确性》。正面。体育法案。《活着》3585870（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Kunkels, Y. K., van Roon, A. M., Wichers, M. & Riese, H. Cross-instrument feasibility, validity, and reproducibility of wireless heart rate monitors: Novel opportunities for extended daily life monitoring. Psychophysiology 58, e13898 (2021).PubMed

Kunkels，Y.K.，van Roon，A.M.，Wichers，M。＆Riese，H。无线心率监护仪的跨仪器可行性，有效性和可重复性：延长日常生活监测的新机会。心理生理学58，e13898（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Sagl, G. et al. Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors. Sensors 19, https://doi.org/10.3390/s19204448 (2019).Schuurmans, A. A. T. et al. Validity of the Empatica E4 Wristband to Measure Heart Rate Variability (HRV) Parameters: a Comparison to Electrocardiography (ECG).

Sagl，G.等人，《可穿戴设备与量化自我：生理传感器的系统基准测试》。传感器19，https://doi.org/10.3390/s19204448（2019年）。Schuurmans，A.A.T.等人。Empatica E4腕带测量心率变异性（HRV）参数的有效性：与心电图（ECG）的比较。

J. Med. Syst. 44, https://doi.org/10.1007/s10916-020-01648-w (2020).Niwa, F., Kuriyama, N., Nakagawa, M. & Imanishi, J. Circadian rhythm of rest activity and autonomic nervous system activity at different stages in Parkinson’s disease. Auton. Neurosci. 165, 195–200 (2011).PubMed .

J、 医学系统。44岁，https://doi.org/10.1007/s10916-020-01648-w（2020年）。Niwa，F.，Kuriyama，N.，Nakagawa，M。＆Imanishi，J。帕金森病不同阶段休息活动和自主神经系统活动的昼夜节律。自动。。165195-200（2011）。PubMed。

Google Scholar

谷歌学者

Barbosa, M. P., da Silva, N. T., de Azevedo, F. M., Pastre, C. M. & Vanderlei, L. C. Comparison of Polar(R) RS800G3 heart rate monitor with Polar(R) S810i and electrocardiogram to obtain the series of RR intervals and analysis of heart rate variability at rest. Clin. Physiol. Funct. Imaging 36, 112–117 (2016).PubMed .

Barbosa，M.P.，da Silva，N.T.，de Azevedo，F.M.，Pastre，C.M。＆Vanderlei，L.C。Polar（R）RS800G3心率监护仪与Polar（R）S810i和心电图的比较，以获得一系列RR间期并分析静息时的心率变异性。临床。生理学。函数。成像36112-117（2016）。PubMed。

Google Scholar

谷歌学者

Santarelli, L. et al. Development of a Novel Wearable Ring-Shaped Biosensor. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2018, 3750–3753 (2018).CAS

Santarelli，L.等人。新型可穿戴环形生物传感器的开发。年。国际会议IEEE工程医学生物学。Soc.20183750-3753（2018）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

Nardelli, M., Vanello, N., Galperti, G., Greco, A. & Scilingo, E. P. Assessing the Quality of Heart Rate Variability Estimated from Wrist and Finger PPG: A Novel Approach Based on Cross-Mapping Method. Sensors 20, https://doi.org/10.3390/s20113156 (2020).Pandian, P. S. et al. Smart Vest: wearable multi-parameter remote physiological monitoring system.

Nardelli，M.，Vanello，N.，Galperti，G.，Greco，A。＆Scilingo，E.P。评估手腕和手指PPG估计的心率变异性质量：一种基于交叉映射方法的新方法。传感器20，https://doi.org/10.3390/s20113156（2020年）。Pandian，P.S。等。智能背心：可穿戴的多参数远程生理监测系统。

Med Eng. Phys. 30, 466–477 (2008).CAS .

与Eng.Phys。30, 466-477 (2008).CAS。

PubMed

PubMed

Google Scholar

谷歌学者

Sarhaddi, F. et al. A comprehensive accuracy assessment of Samsung smartwatch heart rate and heart rate variability. PLoS One 17, e0268361 (2022).CAS

Sarhaddi，F.等人。三星智能手表心率和心率变异性的综合准确性评估。《公共科学图书馆·综合》17，e0268361（2022）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Kinnunen, H., Rantanen, A., Kentta, T. & Koskimaki, H. Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG. Physiological Meas. 41, 04NT01 (2020).

Kinnunen，H.，Rantanen，A.，Kentta，T。＆Koskimaki，H。恢复和心血管健康的可行评估：与医学级心电图相比，通过ring PPG评估的夜间HR和HRV的准确性。生理测量。4104NT01（2020）。

Google Scholar

谷歌学者

Reali, P., Tacchino, G., Rocco, G., Cerutti, S. & Bianchi, A. M. Heart Rate Variability from Wearables: A Comparative Analysis Among Standard ECG, a Smart Shirt and a Wristband. Stud. Health Technol. Inform. 261, 128–133 (2019).PubMed

Reali，P.，Tacchino，G.，Rocco，G.，Cerutti，S.＆Bianchi，A.M。可穿戴设备的心率变异性：标准心电图，智能衬衫和腕带之间的比较分析。螺柱健康技术。通知。261128-133（2019）。PubMed出版社

Google Scholar

谷歌学者

Bloem, B. R. et al. The Personalized Parkinson Project: examining disease progression through broad biomarkers in early Parkinson’s disease. BMC Neurol. 19, 160 (2019).CAS

Bloem，B.R.等人，《个性化帕金森病项目：通过早期帕金森病的广泛生物标志物检查疾病进展》。BMC神经病学。19160（2019）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Darweesh, S. K. L. ClinicalTrials.gov. Slow-SPEED-NL: Slowing Parkinson’s Early Through Exercise Dosage-Netherlands (Slow-SPEED-NL), 2024.Park, S. M. et al. A mountable toilet system for personalized health monitoring via the analysis of excreta. Nat. Biomed. Eng. 4, 624–635 (2020).PubMed .

Darweesh，S.K.L.ClinicalTrials.gov。慢速NL：通过运动剂量荷兰（慢速NL）减缓帕金森氏症的早期发作，2024年。Park，S.M.等人。一种可安装的厕所系统，用于通过排泄物分析进行个性化健康监测。自然生物医学。工程4624–635（2020）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Molavi, B., Shadgan, B., Macnab, A. J. & Dumont, G. A. Noninvasive Optical Monitoring of Bladder Filling to Capacity Using a Wireless Near Infrared Spectroscopy Device. IEEE Trans. Biomed. Circuits Syst. 8, 325–333 (2014).PubMed

Molavi，B.，Shadgan，B.，Macnab，A.J。和Dumont，G.A。使用无线近红外光谱仪对膀胱充盈进行无创光学监测。IEEE Trans。生物医学。电路系统。8325-333（2014）。PubMed出版社

Google Scholar

谷歌学者

El Helou, E. et al. Mobile sonouroflowmetry using voiding sound and volume. Sci. Rep. 11, 11250 (2021).CAS

El Helou，E。等人。使用排尿声音和体积的移动超声尿流计。科学。代表1111250（2021）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Schultz, R. E. Smartphone App for In-home Uroflowmetry. Urol. Pr. 9, 524–530 (2022).

Schultz，R.E。智能手机应用程序，用于家庭尿流率测定。乌洛尔。第9524-530页（2022年）。

Google Scholar

谷歌学者

Baker, L. B. et al. Skin-interfaced microfluidic system with personalized sweating rate and sweat chloride analytics for sports science applications. Sci. Adv. 6, https://doi.org/10.1126/sciadv.abe3929 (2020).Nyein, H. Y. Y. et al. A wearable patch for continuous analysis of thermoregulatory sweat at rest.

Baker，L.B.等人。具有个性化出汗率和汗液氯化物分析的皮肤界面微流体系统，用于体育科学应用。科学。广告6，https://doi.org/10.1126/sciadv.abe3929（2020年）。。

Nat. Commun. 12, 1823 (2021).CAS .

Nat.普通。1823年12月（2021年）。案例。

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Gil, B., Anastasova, S. & Yang, G. Z. A Smart Wireless Ear-Worn Device for Cardiovascular and Sweat Parameter Monitoring During Physical Exercise: Design and Performance Results. Sensors 19, https://doi.org/10.3390/s19071616 (2019).Sim, J. K., Yoon, S. & Cho, Y. H. Wearable Sweat Rate Sensors for Human Thermal Comfort Monitoring.

Gil，B.，Anastasova，S。＆Yang，G.Z。一种用于体育锻炼期间心血管和汗液参数监测的智能无线耳戴设备：设计和性能结果。传感器19，https://doi.org/10.3390/s19071616（2019年）。Sim，J.K.，Yoon，S。＆Cho，Y.H。用于人体热舒适监测的可穿戴式出汗率传感器。

Sci. Rep. 8, 1181 (2018).PubMed .

滑雪众议员8，1181（2018）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Ummel, J. D. et al. Kick Ring LL: A Multi-Sensor Ring Capturing Respiration, Electrocardiogram, Oxygen Saturation, and Skin Temperature(1). Annu Int Conf. IEEE Eng. Med Biol. Soc. 2020, 4394–4397 (2020).PubMed

Ummel，J.D.等人。Kick Ring LL：一种多传感器环，可捕获呼吸，心电图，血氧饱和度和皮肤温度（1）。Annu Int Conf.IEEE工程医学生物学。Soc.2020、4394–4397（2020）。PubMed出版社

Google Scholar

谷歌学者

Madrid-Navarro, C. J. et al. Multidimensional Circadian Monitoring by Wearable Biosensors in Parkinson’s Disease. Front Neurol. 9, 157 (2018).PubMed

马德里·纳瓦罗（Madrid Navarro，C.J.）等。帕金森病中可穿戴生物传感器的多维昼夜节律监测。前神经。9157（2018）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Kim, H. et al. Smart Patch for Skin Temperature: Preliminary Study to Evaluate Psychometrics and Feasibility. Sensors 21, https://doi.org/10.3390/s21051855 (2021).van Marken Lichtenbelt, W. D. et al. Evaluation of wireless determination of skin temperature using iButtons. Physiol. Behav.

Kim，H.等人，《皮肤温度智能贴片：评估心理测量学和可行性的初步研究》。，https://doi.org/10.3390/s21051855（2021）。van Marken Lichtenbelt，W.D.等人。使用iButtons无线测定皮肤温度的评估。生理学。行为。

88, 489–497 (2006).PubMed .

88, 489–497 (2006).Pub Med。

Google Scholar

谷歌学者

Ibrahim, B. & Jafari, R. Cuffless Blood Pressure Monitoring from an Array of Wrist Bio-Impedance Sensors Using Subject-Specific Regression Models: Proof of Concept. IEEE Trans. Biomed. Circuits Syst. 13, 1723–1735 (2019).PubMed

Ibrahim，B。＆Jafari，R。Cuffless血压监测使用特定于主题的回归模型从一系列腕部生物阻抗传感器进行监测：概念验证。IEEE Trans。生物医学。电路系统。131723-1735（2019）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Narasimhan, R., Parlikar, T., Verghesel, G. & McConnell, M. V. Finger-Wearable Blood Pressure Monitor. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2018, 3792–3795 (2018).PubMed

Narasimhan，R.，Parlikar，T.，Verghesel，G。＆McConnell，M.V。手指可穿戴血压监测仪。年。国际会议IEEE工程医学生物学。Soc.20183792-3795（2018）。PubMed出版社

Google Scholar

谷歌学者

Nachman, D. et al. Comparing blood pressure measurements between a photoplethysmography-based and a standard cuff-based manometry device. Sci. Rep. 10, 16116 (2020).CAS

Nachman，D.等人比较了基于光体积描记法和基于标准袖带的测压装置之间的血压测量值。科学。代表1016116（2020）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Sola, J. et al. Validation of the optical Aktiia bracelet in different body positions for the persistent monitoring of blood pressure. Sci. Rep. 11, 20644 (2021).CAS

Sola，J.等人在不同身体位置验证光学Aktia手镯用于持续监测血压。科学。代表1120644（2021）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Gaurav, A., Maheedhar, M., Tiwari, V. N. & Narayanan, R. Cuff-less PPG based continuous blood pressure monitoring: a smartphone based approach. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2016, 607–610 (2016).PubMed

Gaurav，A.，Maheedhar，M.，Tiwari，V.N。和Narayanan，R。基于无袖带PPG的连续血压监测：基于智能手机的方法。年。国际会议IEEE工程医学生物学。Soc.2016607-610（2016）。PubMed出版社

Google Scholar

谷歌学者

Rachim, V. P. & Chung, W. Y. Multimodal Wrist Biosensor for Wearable Cuff-less Blood Pressure Monitoring System. Sci. Rep. 9, 7947 (2019).PubMed

Rachim，V。P。和Chung，W。Y。用于可穿戴无袖带血压监测系统的多模式腕部生物传感器。科学。代表97947（2019）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Mark, E. B. et al. Ambulatory assessment of colonic motility using the electromagnetic capsule tracking system. Neurogastroenterol. Motil. 31, e13451 (2019).PubMed

Mark，E.B.等人。使用电磁胶囊跟踪系统对结肠运动进行动态评估。神经胃肠道。运动型。31，e13451（2019）。PubMed出版社

Google Scholar

谷歌学者

Axelrod, L., Axelrod, S., Navalgund, A. & Triadafilopoulos, G. Pilot Validation of a New Wireless Patch System as an Ambulatory, Noninvasive Tool That Measures Gut Myoelectrical Signals: Physiologic and Disease Correlations. Digestive Dis. Sci. 66, 3505–3515 (2021).

Axelrod，L.，Axelrod，S.，Navalgund，A。和Triadafilopoulos，G。试点验证一种新的无线贴片系统，作为一种测量肠道肌电信号的非侵入性工具：生理和疾病相关性。消化疾病。科学。663505-3515（2021）。

Google Scholar

谷歌学者

Su, A., Gandhy, R., Barlow, C. & Triadafilopoulos, G. Utility of high-resolution anorectal manometry and wireless motility capsule in the evaluation of patients with Parkinson’s disease and chronic constipation. BMJ Open Gastroenterol. 3, e000118 (2016).PubMed

Su，A.，Gandhy，R.，Barlow，C。＆Triadafilopoulos，G。高分辨率肛门直肠测压和无线运动胶囊在评估帕金森病和慢性便秘患者中的应用。BMJ开放胃肠道。3，e000118（2016）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Maqbool, S., Parkman, H. P. & Friedenberg, F. K. Wireless capsule motility: comparison of the SmartPill GI monitoring system with scintigraphy for measuring whole gut transit. Dig. Dis. Sci. 54, 2167–2174 (2009).PubMed

Maqbool，S.，Parkman，H.P。＆Friedenberg，F.K。无线胶囊运动：SmartPill GI监测系统与闪烁扫描测量整个肠道运输的比较。挖掘。Dis。科学。542167-2174（2009）。PubMed出版社

Google Scholar

谷歌学者

Pehlivan, M. et al. An electronic device measuring the frequency of spontaneous swallowing: digital phagometer. Dysphagia 11, 259–264 (1996).CAS

Pehlivan，M.等人。一种测量自发吞咽频率的电子设备：数字吞咽仪。吞咽困难11259-264（1996）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

Hadley, A. J., Krival, K. R., Ridgel, A. L., Hahn, E. C. & Tyler, D. J. Neural network pattern recognition of lingual-palatal pressure for automated detection of swallow. Dysphagia 30, 176–187 (2015).PubMed

Hadley，A.J.，Krival，K.R.，Ridgel，A.L.，Hahn，E.C。＆Tyler，D.J。用于自动检测吞咽的舌腭压力的神经网络模式识别。吞咽困难30176-187（2015）。PubMed出版社

Google Scholar

谷歌学者

O’Brien, M. K. et al. Advanced Machine Learning Tools to Monitor Biomarkers of Dysphagia: A Wearable Sensor Proof-of-Concept Study. Digital Biomark. 5, 167–175 (2021).

O'Brien，M.K.等人。用于监测吞咽困难生物标志物的先进机器学习工具：可穿戴传感器概念验证研究。数字生物标志5167-175（2021）。

Google Scholar

谷歌学者

Jayatilake, D. et al. Smartphone-Based Real-time Assessment of Swallowing Ability from the Swallowing Sound. IEEE J. Transl. Eng. Health Med. 3, https://doi.org/10.1109/JTEHM.2015.2500562 (2015).Kantarcigil, C. et al. Validation of a Novel Wearable Electromyography Patch for Monitoring Submental Muscle Activity During Swallowing: A Randomized Crossover Trial.

Jayatilake，D。等人。基于智能手机的吞咽声音实时评估吞咽能力。IEEE J.Transl。工程健康医学3，https://doi.org/10.1109/JTEHM.2015.2500562（2015年）。Kantarcigil，C。等人。用于监测吞咽过程中颏下肌肉活动的新型可穿戴肌电图贴片的验证：一项随机交叉试验。

J. Speech Lang. Hearing Res. 63, 3293–3310 (2020)..

J、 演讲语言。听力第633293-3310号决议（2020年）。。

Google Scholar

谷歌学者

Li, P. et al. Circadian disturbances in Alzheimer’s disease progression: a prospective observational cohort study of community-based older adults. Lancet Healthy Longev. 1, e96–e105 (2020).PubMed

Li，P.等人，《阿尔茨海默病进展中的昼夜节律紊乱：基于社区的老年人的前瞻性观察性队列研究》。柳叶刀健康Longev。1，e96–e105（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Targa, A. D. S. et al. The circadian rest-activity pattern predicts cognitive decline among mild-moderate Alzheimer’s disease patients. Alzheimer’s Res. Therapy 13, https://doi.org/10.1186/s13195-021-00903-7 (2021).Tranah, G. J. et al. Circadian activity rhythms and risk of incident dementia and mild cognitive impairment in older women.

Targa，A.D.S.等人。昼夜节律休息活动模式预测轻中度阿尔茨海默病患者的认知能力下降。阿尔茨海默病治疗13，https://doi.org/10.1186/s13195-021-00903-7（2021年）。Tranah，G.J.等人。老年女性的昼夜节律活动节律和痴呆和轻度认知障碍的风险。

Ann. Neurol. 70, 722–732 (2011).PubMed .

安。神经病学。70722-732（2011）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Rogers-Soeder, T. S. et al. Rest-Activity Rhythms and Cognitive Decline in Older Men: The Osteoporotic Fractures in Men Sleep Study. J. Am. Geriatrics Soc. 66, 2136–2143 (2018).

罗杰斯·索德（Rogers Soeder，T.S.）等人，《老年男性休息活动节律和认知能力下降：男性骨质疏松性骨折睡眠研究》。J、 美国老年医学学会662136-2143（2018）。

Google Scholar

谷歌学者

Dodge, H. H., Mattek, N. C., Austin, D., Hayes, T. L. & Kaye, J. A. In-home walking speeds and variability trajectories associated with mild cognitive impairment. Neurology 78, 1946–1952 (2012).CAS

Dodge，H.H.，Mattek，N.C.，Austin，D.，Hayes，T.L。＆Kaye，J.A。与轻度认知障碍相关的家庭步行速度和变异轨迹。神经病学781946-1952（2012）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Leng, Y., Redline, S., Stone, K. L., Ancoli-Israel, S. & Yaffe, K. Objective napping, cognitive decline, and risk of cognitive impairment in older men. Alzheimers Dement. 15, 1039–1047 (2019).PubMed

Leng，Y.，Redline，S.，Stone，K.L.，Ancoli Israel，S。＆Yaffe，K。客观午睡，认知能力下降和老年男性认知障碍的风险。阿尔茨海默病。151039-1047（2019）。PubMed出版社

Google Scholar

谷歌学者

Khan, T. & Jacobs, P. G. Prediction of Mild Cognitive Impairment Using Movement Complexity. IEEE J. Biomed. Health Inform. 25, 227–236 (2021).PubMed

Khan，T。＆Jacobs，P.G。使用运动复杂性预测轻度认知障碍。IEEE J.生物医学。健康信息。25227-236（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Gunn, D. G., Naismith, S. L., Bolitho, S. J. & Lewis, S. J. Actigraphically-defined sleep disturbance in Parkinson’s disease is associated with differential aspects of cognitive functioning. J. Clin. Neurosci. 21, 1112–1115 (2014).PubMed

Gunn，D.G.，Naismith，S.L.，Bolitho，S.J。＆Lewis，S.J。帕金森病中活动定义的睡眠障碍与认知功能的不同方面有关。J、 临床。。211112-1115（2014）。PubMed出版社

Google Scholar

谷歌学者

Akl, A. et al. Clustering Home Activity Distributions for Automatic Detection of Mild Cognitive Impairment in Older Adults. J. Ambient Intell. Smart Environ. 8, 437–451 (2016).PubMed

Akl，A。等人。聚类家庭活动分布，用于自动检测老年人的轻度认知障碍。J、 。智能环境。8437-451（2016）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Dawadi, P. N., Cook, D. J. & Schmitter-Edgecombe, M. Automated Cognitive Health Assessment From Smart Home-Based Behavior Data. IEEE J. Biomed. Health Inf. 20, 1188–1194 (2016).

Dawadi，P.N.，Cook，D.J。和Schmitter Edgecombe，M。基于智能家居的行为数据的自动认知健康评估。IEEE J.生物医学。健康信息201188-1194（2016）。

Google Scholar

谷歌学者

Alberdi, A. et al. Smart Home-Based Prediction of Multidomain Symptoms Related to Alzheimer’s Disease. IEEE J. Biomed. Health Inf. 22, 1720–1731 (2018).

Alberdi，A.等人。基于智能家居的阿尔茨海默病多领域症状预测。IEEE J.生物医学。健康信息221720-1731（2018）。

Google Scholar

谷歌学者

Akl, A., Taati, B. & Mihailidis, A. Autonomous unobtrusive detection of mild cognitive impairment in older adults. IEEE Trans. Biomed. Eng. 62, 1383–1394 (2015).PubMed

Akl，A.，Taati，B。＆Mihailidis，A。自主不引人注目地检测老年人的轻度认知障碍。IEEE Trans。生物医学。工程621383-1394（2015）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Sacco, G. et al. Detection of activities of daily living impairment in Alzheimer’s disease and mild cognitive impairment using information and communication technology. Clin. Interventions Aging 7, 539–549, (2012).

Sacco，G.等人。使用信息和通信技术检测阿尔茨海默病和轻度认知障碍的日常生活障碍活动。临床。干预年龄7539-549（2012）。

Google Scholar

谷歌学者

Lussier, M. et al. Smart Home Technology: A New Approach for Performance Measurements of Activities of Daily Living and Prediction of Mild Cognitive Impairment in Older Adults. J. Alzheimers Dis. 68, 85–96 (2019).PubMed

Lussier，M.等人，《智能家居技术：老年人日常生活活动性能测量和轻度认知障碍预测的新方法》。J、 阿尔茨海默病。68,85-96（2019）。PubMed出版社

Google Scholar

谷歌学者

Jeon, S. Y. et al. Circadian rest-activity rhythm and longitudinal brain changes underlying late-life cognitive decline. Psychiatry Clin. Neurosci. 77, 205–212 (2023).PubMed

Jeon，S.Y.等人。昼夜休息活动节律和大脑纵向变化是晚年认知能力下降的基础。精神病学临床。。77205-212（2023）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Antonsdottir, I. M. et al. 24 h Rest/Activity Rhythms in Older Adults with Memory Impairment: Associations with Cognitive Performance and Depressive Symptomatology. Adv. Biol., e2300138, https://doi.org/10.1002/adbi.202300138 (2023).Hooghiemstra, A. M., Eggermont, L. H., Scheltens, P., van der Flier, W.

。高级生物学。，e2300138，https://doi.org/10.1002/adbi.202300138（2023年）。胡吉姆斯特拉（Hooghiemstra），洛杉矶埃格蒙特（Eggermont），P。谢尔滕斯（Scheltens），W。范德弗利尔（VanderFlier）。

M. & Scherder, E. J. The rest-activity rhythm and physical activity in early-onset dementia. Alzheimer Dis. Assoc. Disord. 29, 45–49 (2015).PubMed .

M、 ＆Scherder，E.J。早发性痴呆的休息活动节律和体力活动。阿尔茨海默病。协会Disord。29,45-49（2015）。PubMed。

Google Scholar

谷歌学者

Sevil, M. et al. Discrimination of simultaneous psychological and physical stressors using wristband biosignals. Comput. Methods Programs Biomed. 199, https://doi.org/10.1016/j.cmpb.2020.105898 (2021).Jacobson, N. C., Lekkas, D., Huang, R. & Thomas, N. Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17–18 years.

Sevil，M.等人。使用腕带生物信号区分同时的心理和身体压力源。计算机。方法程序Biomed。，https://doi.org/10.1016/j.cmpb.2020.105898（2021年）。Jacobson，N.C.，Lekkas，D.，Huang，R。＆Thomas，N。深度学习与可穿戴被动感知数据相结合，可预测17-18年焦虑症症状的恶化。

J. Affect. Disord. 282, 104–111 (2021).PubMed .

J、 影响。混乱。282104-111（2021）。PubMed。

Google Scholar

谷歌学者

Di Matteo, D. et al. Smartphone-Detected Ambient Speech and Self-Reported Measures of Anxiety and Depression: Exploratory Observational Study. JMIR Form. Res 5, e22723 (2021).PubMed

Di Matteo，D.等人，《智能手机检测环境语言和自我报告的焦虑和抑郁测量：探索性观察性研究》。JMIR表5，e22723（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Opoku Asare, K. et al. Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study. JMIR mHealth uHealth 9, e26540 (2021).PubMed

Opoku Asare，K。等人。使用机器学习方法，超参数优化和特征重要性分析从智能手机行为标记预测抑郁症：探索性研究。JMIR mHealth uHealth 9，e26540（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Rykov, Y., Thach, T. Q., Bojic, I., Christopoulos, G. & Car, J. Digital Biomarkers for Depression Screening With Wearable Devices: Cross-sectional Study With Machine Learning Modeling. JMIR Mhealth Uhealth 9, e24872 (2021).PubMed

Rykov，Y.，Thach，T.Q.，Bojic，I.，Christopoulos，G。＆Car，J。可穿戴设备抑郁症筛查的数字生物标志物：机器学习建模的横断面研究。JMIR Mhealth Uhealth 9，e24872（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Narziev, N. et al. STDD: Short-Term Depression Detection with Passive Sensing. Sensors 20, https://doi.org/10.3390/s20051396 (2020).Saeb, S., Lattie, E. G., Kording, K. P. & Mohr, D. C. Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety. JMIR Mhealth Uhealth 5, e112 (2017).PubMed .

Narziev，N。等人。STDD：被动感知的短期抑郁症检测。传感器20，https://doi.org/10.3390/s20051396（2020年）。Saeb，S.，Lattie，E.G.，Kording，K.P。＆Mohr，D.C。手机检测语义位置及其与抑郁和焦虑的关系。JMIR Mhealth Uhealth 5，e112（2017）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Choi, J., Lee, S., Kim, S., Kim, D. & Kim, H. Depressed Mood Prediction of Elderly People with a Wearable Band. Sensors 22, https://doi.org/10.3390/s22114174 (2022).Saeb, S., Lattie, E. G., Schueller, S. M., Kording, K. P. & Mohr, D. C. The relationship between mobile phone location sensor data and depressive symptom severity.

Choi，J.，Lee，S.，Kim，S.，Kim，D。和Kim，H。佩戴可穿戴乐队的老年人的抑郁情绪预测。传感器22，https://doi.org/10.3390/s22114174（2022年）。Saeb，S.，Lattie，E.G.，Schueller，S.M.，Kording，K.P。＆Mohr，D.C。手机位置传感器数据与抑郁症状严重程度之间的关系。

PeerJ 4, e2537 (2016).Schutz, N. et al. A Sensor-Driven Visit Detection System in Older Adults Homes: Towards Digital Late-Life Depression Marker Extraction. IEEE J. Biomed. Health Informatics., https://doi.org/10.1109/JBHI.2021.3114595 (2021).Huang, M. et al. Association of Depressive Symptoms with Sleep Disturbance: A Co-twin Control Study.

PeerJ 4，e2537（2016）。Schutz，N.等人，《老年人家庭中传感器驱动的访问检测系统：走向数字晚年抑郁症标记提取》。IEEE J.生物医学。。，https://doi.org/10.1109/JBHI.2021.3114595（2021年）。Huang，M.等人。抑郁症状与睡眠障碍的关联：一项双胞胎对照研究。

Ann. Behav. Med. 15, https://doi.org/10.1093/abm/kaab040 (2021).Zhang, Y. et al. Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study. JMIR mHealth uHealth 9, e24604 (2021).PubMed .

安。行为。医学15，https://doi.org/10.1093/abm/kaab040（2021年）。Zhang，Y.等人。使用腕带可穿戴设备收集的重度抑郁症症状严重程度与睡眠之间的关系：多中心纵向观察研究。JMIR mHealth uHealth 9，e24604（2021）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Mulryan, P., Affonso, S. & Sullivan, A. Sleep and depression in Parkinson’s disease: Investigating the relationship between sleep and depression using a combination of subjective and objective sleep assessment methods. Ann. Neurol. 88, S196 (2020).

Mulryan，P.，Affonso，S。＆Sullivan，A。帕金森病的睡眠和抑郁：使用主观和客观睡眠评估方法相结合的方法研究睡眠和抑郁之间的关系。安。神经病学。88，S196（2020）。

Google Scholar

谷歌学者

Coutts, L. V., Plans, D., Brown, A. W. & Collomosse, J. Deep learning with wearable based heart rate variability for prediction of mental and general health. J. Biomed Inf 112, https://doi.org/10.1016/j.jbi.2020.103610 (2020).Dogrucu, A. et al. Moodable: On feasibility of instantaneous depression assessment using machine learning on voice samples with retrospectively harvested smartphone and social media data.

Coutts，L.V.，Plans，D.，Brown，A.W。＆Collomosse，J。深度学习与可穿戴式心率变异性预测心理和一般健康。J、 生物医学Inf 112，https://doi.org/10.1016/j.jbi.2020.103610（2020年）。Dogrucu，A。等人。可讨论：使用机器学习对语音样本进行即时抑郁评估的可行性，并回顾性收集智能手机和社交媒体数据。

Smart Health 17, https://doi.org/10.1016/j.smhl.2020.100118 (2020).Palmius, N. et al. Detecting bipolar depression from geographic location data. IEEE Trans. Biomed. Eng. 64, 1761–1771 (2017).CAS .

智能健康17，https://doi.org/10.1016/j.smhl.2020.100118（2020年）。Palmius，N.等人。从地理位置数据检测双相抑郁症。IEEE Trans。生物医学。。CAS。

PubMed

PubMed

Google Scholar

谷歌学者

Braund, T. A. et al. Smartphone Sensor Data for Identifying and Monitoring Symptoms of Mood Disorders: A Longitudinal Observational Study. JMIR Ment. Health 9, e35549 (2022).PubMed

Braund，T.A.等人，《用于识别和监测情绪障碍症状的智能手机传感器数据：一项纵向观察性研究》。JMIR公司。健康9，e35549（2022）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Lee, D. et al. Changes in the Circadian Rhythm of High-Frequency Heart Rate Variability Associated With Depression. J. Korean Med Sci. 38, e142 (2023).PubMed

Lee，D.等人。与抑郁症相关的高频心率变异性昼夜节律的变化。J、 韩国医学科学。38，e142（2023）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Siddi, S. et al. The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity. Psychol. Med 53, 3249–3260 (2023).CAS

Siddi，S.等人。白天和夜间心率动力学作为抑郁症严重程度数字生物标志物的可用性。心理学。医学533249-3260（2023）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

Hayashi, M., Takeshima, M., Hosoya, T. & Kume, Y. 24-Hour Rest-Activity Rhythm in Middle-Aged and Older Persons with Depression. Int. J. Environ. Res. Public Health 20, https://doi.org/10.3390/ijerph20075275 (2023).de Feijter, M., Kocevska, D., Ikram, M. A. & Luik, A. I. The bidirectional association of 24-h activity rhythms and sleep with depressive symptoms in middle-aged and elderly persons.

Hayashi，M.，Takeshima，M.，Hosoya，T。＆Kume，Y。中老年抑郁症患者的24小时休息活动节律。内景J.环境。第20号决议，https://doi.org/10.3390/ijerph20075275（2023）。de Feijter，M.，Kocevska，D.，Ikram，M.A。和Luik，A.I。24小时活动节律和睡眠与中老年人抑郁症状的双向关联。

Psychol. Med. 53, 1418–1425 (2023).PubMed .

心理。Med.534118-1425（2023）。PubMed。

Google Scholar

谷歌学者

Whitehead, D. L., Davies, A. D., Playfer, J. R. & Turnbull, C. J. Circadian rest-activity rhythm is altered in Parkinson’s disease patients with hallucinations. Mov. Disord. 23, 1137–1145 (2008).PubMed

怀特海，D.L.，戴维斯，A.D.，普莱弗，J.R。和特恩布尔，C.J。帕金森病幻觉患者的昼夜休息活动节律发生了改变。莫夫。混乱。231137-1145（2008）。PubMed出版社

Google Scholar

谷歌学者

Godkin, F. E. et al. Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease. J. Neurol., 1–14, https://doi.org/10.1007/s00415-021-10831-z (2021).Keogh, A., Dorn, J. F., Walsh, L., Calvo, F. & Caulfield, B. Comparing the Usability and Acceptability of Wearable Sensors Among Older Irish Adults in a Real-World Context: Observational Study.

Godkin，F.E.等人。在患有神经退行性疾病的人群中，连续多传感器远程健康监测方法的可行性。J、 神经病学。，1–14，https://doi.org/10.1007/s00415-021-10831-z（2021年）。Keogh，A.，Dorn，J.F.，Walsh，L.，Calvo，F。＆Caulfield，B。在现实世界中比较爱尔兰老年人可穿戴传感器的可用性和可接受性：观察性研究。

JMIR mHealth uHealth 8, e15704 (2020).PubMed .

JMIR mHealth uHealth 8，e15704（2020）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Areia, C. et al. Wearability Testing of Ambulatory Vital Sign Monitoring Devices: Prospective Observational Cohort Study. JMIR mHealth uHealth 8, e20214 (2020).PubMed

Areia，C.等人。动态生命体征监测设备的可穿戴性测试：前瞻性观察性队列研究。JMIR mHealth uHealth 8，e20214（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Saif, N. et al. Feasibility of Using a Wearable Biosensor Device in Patients at Risk for Alzheimer’s Disease Dementia. J. Prev. Alzheimers Dis. 7, 104–111 (2020).CAS

Saif，N.等人。在阿尔茨海默病痴呆风险患者中使用可穿戴生物传感器装置的可行性。J、 上一页。阿尔茨海默病。7104-111（2020）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Silva de Lima, A. L. et al. Feasibility of large-scale deployment of multiple wearable sensors in Parkinson’s disease. PLoS One 12, e0189161 (2017).PubMed

席尔瓦·德利马（Silva de Lima），A.L。等人。帕金森病中大规模部署多个可穿戴传感器的可行性。PLoS One 12，e0189161（2017）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Meinders, M. J., Donnelly, A. C., Sheehan, M. & Bloem, B. R. Including People with Parkinson’s Disease in Clinical Study Design and Execution: A Call to Action. J. Parkinsons Dis. 12, 1359–1363 (2022).PubMed

Meinders，M.J.，Donnelly，A.C.，Sheehan，M。＆Bloem，B.R。在临床研究设计和执行中包括帕金森病患者：行动呼吁。J、 。121359-1363（2022）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Schneider, R. et al. Feasibility of using a smartphone application for the objective evaluation of Parkinson’s disease. Mov. Disord. 32, 973 (2017).

Schneider，R.等人。使用智能手机应用程序客观评估帕金森病的可行性。莫夫。混乱。32973（2017）。

Google Scholar

谷歌学者

Seelye, A. et al. Feasibility of In-Home Sensor Monitoring to Detect Mild Cognitive Impairment in Aging Military Veterans: Prospective Observational Study. JMIR Form. Res. 4, e16371 (2020).PubMed

Seelye，A.等人。家庭传感器监测检测老年退伍军人轻度认知障碍的可行性：前瞻性观察性研究。JMIR表格4，e16371（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Betthauser, L. M. et al. Mobile app for mental health monitoring and clinical outreach in veterans: Mixed methods feasibility and acceptability study. J. Med. Internet Res. 22, https://doi.org/10.2196/15506 (2020).Heinzel, S. et al. Update of the MDS research criteria for prodromal Parkinson’s disease.

Betthauser，L.M.等人，《退伍军人心理健康监测和临床推广的移动应用程序：混合方法可行性和可接受性研究》。J、 医学互联网第22号决议，https://doi.org/10.2196/15506（2020年）。Heinzel，S.等人。前驱帕金森病MDS研究标准的更新。

Mov. Disord. 34, 1464–1470 (2019).PubMed .

莫夫。混乱。341464-1470（2019）。PubMed。

Google Scholar

谷歌学者

Otaiku, A. I. Association of sleep abnormalities in older adults with risk of developing Parkinson’s disease. Sleep 45, https://doi.org/10.1093/sleep/zsac206 (2022).Bugalho, P. et al. Polysomnographic predictors of sleep, motor and cognitive dysfunction progression in Parkinson’s disease: a longitudinal study.

Otaiku，A.I。老年人睡眠异常与帕金森病发病风险的关系。睡眠45，https://doi.org/10.1093/sleep/zsac206（2022年）。Bugalho，P。等人。帕金森病睡眠、运动和认知功能障碍进展的多导睡眠图预测因子：一项纵向研究。

Sleep. Med. 77, 205–208 (2021).PubMed .

睡觉与77205-208（2021）。Pub Med。

Google Scholar

谷歌学者

Dijkstra, F., de Volder, I., Viaene, M., Cras, P. & Crosiers, D. Polysomnographic Predictors of Sleep, Motor, and Cognitive Dysfunction Progression in Parkinson’s Disease. Curr. Neurol. Neurosci. Rep. 22, 657–674 (2022).PubMed

Dijkstra，F.，de Volder，I.，Viaene，M.，Cras，P。＆Crosiers，D。帕金森病睡眠，运动和认知功能障碍进展的多导睡眠图预测因子。货币。神经病学。。代表22657–674（2022）。PubMed出版社

Google Scholar

谷歌学者

Bugalho, P. et al. Heart rate variability in Parkinson disease and idiopathic REM sleep behavior disorder. Clin. Auton. Res 28, 557–564 (2018).PubMed

Bugalho，P。等人。帕金森病和特发性REM睡眠行为障碍的心率变异性。临床。自动。第28557-564号决议（2018）。PubMed出版社

Google Scholar

谷歌学者

Yang, J. H. et al. Association of heart rate variability with REM sleep without atonia in idiopathic REM sleep behavior disorder. J. Clin. Sleep. Med. 17, 461–469 (2021).PubMed

Yang，J.H.等人。特发性REM睡眠行为障碍中心率变异性与无失调症的REM睡眠的关联。J、 临床。睡觉。医学17461-469（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Suzuki, M. et al. Wearable sensor device-based detection of decreased heart rate variability in Parkinson’s disease. J. Neural Transm. 129, 1299–1306 (2022).PubMed

Suzuki，M.等人。基于可穿戴传感器设备的帕金森病心率变异性降低检测。J、 神经传输。1291299-1306（2022）。PubMed出版社

Google Scholar

谷歌学者

Haapaniemi, T. H. et al. Ambulatory ECG and analysis of heart rate variability in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 70, 305–310 (2001).CAS

Haapaniemi，T.H.等人。帕金森病的动态心电图和心率变异性分析。J、 神经病学。神经外科。精神病学70305-310（2001）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Speelberg, D. H. B. et al. Prodromal Cognitive Deficits and the Risk of Subsequent Parkinson’s Disease. Brain Sci. 12, https://doi.org/10.3390/brainsci12020199 (2022).Roheger, M., Kalbe, E. & Liepelt-Scarfone, I. Progression of Cognitive Decline in Parkinson’s Disease. J. Parkinsons Dis.

Speelberg，D.H.B.等人，《前驱认知缺陷和随后帕金森病的风险》。脑科学。12年，https://doi.org/10.3390/brainsci12020199（2022年）。Roheger，M.，Kalbe，E。和Liepelt-Scarfone，I。帕金森病认知能力下降的进展。J、 帕金森病。

8, 183–193 (2018).PubMed .

8, 183–193 (2018).Pub Med。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Frazzitta, G., Ferrazzoli, D., Folini, A., Palamara, G. & Maestri, R. Severe Constipation in Parkinson’s Disease and in Parkinsonisms: Prevalence and Affecting Factors. Front Neurol. 10, 621 (2019).PubMed

Frazzitta，G.，Ferrazzoli，D.，Folini，A.，Palamara，G。＆Maestri，R。帕金森病和帕金森病的严重便秘：患病率和影响因素。前神经。10621（2019）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Yoo, S. W. et al. Delayed orthostatic hypotension in Parkinson’s disease. NPJ Parkinsons Dis. 7, 37 (2021).CAS

Yoo，S.W.等人。帕金森病中的迟发性体位性低血压。NPJ帕金森病。7，37（2021）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Fedor, S. et al. Wearable Technology in Clinical Practice for Depressive Disorder. N. Engl. J. Med. 389, 2457–2466 (2023).PubMed

Fedor，S.等人。抑郁症临床实践中的可穿戴技术。N、 英语。J、 医学3892457-2466（2023）。PubMed出版社

Google Scholar

谷歌学者

Cheng, P. G. et al. Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening. JMIR Mhealth Uhealth 4, e88 (2016).PubMed

。JMIR Mhealth Uhealth 4，e88（2016）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Ozkanca, Y. et al. Depression Screening from Voice Samples of Patients Affected by Parkinson’s Disease. Digital Biomark. 3, 72–82 (2019).

Ozkanca，Y.等人。从帕金森病患者的声音样本中筛查抑郁症。数字生物标志3,72-82（2019）。

Google Scholar

谷歌学者

Robin, J., Xu, M., Kaufman, L. D. & Simpson, W. Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment. Front. Digit Health 3, 749758 (2021).PubMed

Robin，J.，Xu，M.，Kaufman，L.D。和Simpson，W。使用数字语音评估来检测认知障碍的早期迹象。正面。数字健康3749758（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Konig, A. et al. Objective measurement of gait parameters in healthy and cognitively impaired elderly using the dual-task paradigm. Aging Clin. Exp. Res. 29, 1181–1189 (2017).PubMed

Konig，A.等人。使用双任务范式对健康和认知障碍老年人的步态参数进行客观测量。老年临床。Exp.Res.291181–1189（2017）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Pagano, G. et al. Trial of Prasinezumab in Early-Stage Parkinson’s Disease. N. Engl. J. Med. 387, 421–432 (2022).CAS

Pagano，G.等人，Prasinezumab在早期帕金森病中的试验。N、 英语。J、 医学387421-432（2022）。中科院

PubMed

PubMed

Google Scholar

谷歌学者

Torrado, J. C. et al. Digital phenotyping by wearable-driven artificial intelligence in older adults and people with Parkinson’s disease: Protocol of the mixed method, cyclic ActiveAgeing study. PLoS One 17, e0275747 (2022).CAS

Torrado，J.C.等人，《老年人和帕金森病患者可穿戴驱动人工智能的数字表型：混合方法的方案，循环活跃老化研究》。《公共科学图书馆·综合》17，e0275747（2022）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Dorsey, E. R. et al. Deep Phenotyping of Parkinson’s Disease. J. Parkinsons Dis. 10, 855–873 (2020).PubMed

Dorsey，E.R.等人，《帕金森病的深层表型》。J、 。10855-873（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Sung, H. Y. et al. The prevalence and patterns of pharyngoesophageal dysmotility in patients with early stage Parkinson’s disease. Mov. Disord. 25, 2361–2368 (2010).PubMed

Sung，H.Y.等人。早期帕金森病患者咽食管运动障碍的患病率和模式。莫夫。混乱。252361-2368（2010）。PubMed出版社

Google Scholar

谷歌学者

Barnes, J. & David, A. S. Visual hallucinations in Parkinson’s disease: a review and phenomenological survey. J. Neurol. Neurosurg. Psychiatry 70, 727–733 (2001).CAS

Barnes，J.＆David，A.S。帕金森病的视觉幻觉：综述和现象学调查。J、 神经病学。神经外科精神病学70727-733（2001）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Winge, K., Skau, A. M., Stimpel, H., Nielsen, K. K. & Werdelin, L. Prevalence of bladder dysfunction in Parkinsons disease. Neurourol. Urodyn. 25, 116–122 (2006).PubMed

Winge，K.，Skau，A.M.，Stimpel，H.，Nielsen，K.K。＆Werdelin，L。帕金森病膀胱功能障碍的患病率。神经甾醇。乌洛丁。25116-122（2006）。PubMed出版社

Google Scholar

谷歌学者

Mueller, C. A. et al. A self-administered odor identification test procedure using the “Sniffin’ Sticks. Chem. Senses 31, 595–598 (2006).PubMed

Mueller，C.A.等人，《使用“嗅探”棒的自我管理气味识别测试程序》。化学感官31595-598（2006）。PubMed

Google Scholar

谷歌学者

Elhanbly, S. M., Abdel-Gawad, M. M., Elkholy, A. A. & State, A. F. Nocturnal penile erections: A retrospective study of the role of RigiScan in predicting the response to sildenafil in erectile dysfunction patients. J. Adv. Res. 14, 93–96 (2018).CAS

Elhanbly，S.M.，Abdel Gawad，M.M.，Elkholy，A.A。和State，A.F。夜间阴茎勃起：一项回顾性研究，旨在预测RigiScan在预测勃起功能障碍患者对西地那非的反应中的作用。J、 Adv.Res.14，93–96（2018）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Taore, A., Lobo, G., Turnbull, P. R. & Dakin, S. C. Diagnosis of colour vision deficits using eye movements. Sci. Rep. 12, 7734 (2022).CAS

Taore，A.，Lobo，G.，Turnbull，P.R。和Dakin，S.C。使用眼球运动诊断色觉缺陷。科学。代表127734（2022年）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Ozgur, O. K., Emborgo, T. S., Vieyra, M. B., Huselid, R. F. & Banik, R. Validity and Acceptance of Color Vision Testing on Smartphones. J. Neuroophthalmol. 38, 13–16 (2018).PubMed

Ozgur，O.K.，Emborgo，T.S.，Vieyra，M.B.，Huselid，R.F。＆Banik，R。智能手机色觉测试的有效性和接受性。J、 神经眼科。38,13-16（2018）。PubMed出版社

Google Scholar

谷歌学者

He, R. et al. Olfactory Dysfunction Predicts Disease Progression in Parkinson’s Disease: A Longitudinal Study. Front Neurosci. 14, 569777 (2020).PubMed

嗅觉功能障碍预测帕金森病的疾病进展：一项纵向研究。前神经科学。14569777（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Iravani, B., Arshamian, A., Schaefer, M., Svenningsson, P. & Lundstrom, J. N. A non-invasive olfactory bulb measure dissociates Parkinson’s patients from healthy controls and discloses disease duration. NPJ Parkinsons Dis. 7, 75 (2021).CAS

Iravani，B.，Arshamian，A.，Schaefer，M.，Svenningsson，P。＆Lundstrom，J.N。一种非侵入性嗅球测量将帕金森氏病患者与健康对照分离并揭示疾病持续时间。NPJ帕金森病。7，75（2021）。中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Taylor, K. I., Staunton, H., Lipsmeier, F., Nobbs, D. & Lindemann, M. Outcome measures based on digital health technology sensor data: data- and patient-centric approaches. NPJ Digit Med. 3, 97 (2020).PubMed

Taylor，K.I.，Staunton，H.，Lipsmeier，F.，Nobbs，D。＆Lindemann，M。基于数字健康技术传感器数据的结果测量：以数据和患者为中心的方法。NPJ数字医学杂志3，97（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Manta, C., Patrick-Lake, B. & Goldsack, J. C. Digital Measures That Matter to Patients: A Framework to Guide the Selection and Development of Digital Measures of Health. Digit Biomark. 4, 69–77 (2020).PubMed

Manta，C.，Patrick Lake，B。＆Goldsack，J.C。对患者重要的数字测量：指导数字健康测量的选择和发展的框架。数字生物标志4,69-77（2020）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Espay, A. J. et al. A roadmap for implementation of patient-centered digital outcome measures in Parkinson’s disease obtained using mobile health technologies. Mov. Disord. 34, 657–663 (2019).PubMed

Espay，A.J.等人。使用移动健康技术获得的帕金森病患者中心数字结果测量实施路线图。莫夫。混乱。34657-663（2019）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Stephenson, D., Badawy, R., Mathur, S., Tome, M. & Rochester, L. Digital Progression Biomarkers as Novel Endpoints in Clinical Trials: A Multistakeholder Perspective. J. Parkinsons Dis. 11, S103–S109 (2021).PubMed

Stephenson，D.，Badawy，R.，Mathur，S.，Tome，M。＆Rochester，L。数字进展生物标志物作为临床试验的新终点：多利益相关者的观点。J、 。11，S103–S109（2021）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Evers, L. J. W., Peeters, J. M., Bloem, B. R. & Meinders, M. J. Need for personalized monitoring of Parkinson’s disease: the perspectives of patients and specialized healthcare providers. Front. Neurol. 14, 1150634 (2023).PubMed

Evers，L.J.W.，Peeters，J.M.，Bloem，B.R。＆Meinders，M.J。需要个性化监测帕金森病：患者和专业医疗保健提供者的观点。正面。神经病学。141150634（2023）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Martinez-Martin, N., Insel, T. R., Dagum, P., Greely, H. T. & Cho, M. K. Data mining for health: staking out the ethical territory of digital phenotyping. NPJ Digit Med. 1, https://doi.org/10.1038/s41746-018-0075-8 (2018).Berger, A. M. et al. Methodological Challenges When Using Actigraphy in Research.

Martinez-Martin，N.，Insel，T.R.，Dagum，P.，Greely，H.T。＆Cho，M.K。健康数据挖掘：划定数字表型的道德领域。，https://doi.org/10.1038/s41746-018-0075-8（2018年）。Berger，A.M.等人，《在研究中使用活动描记法的方法学挑战》。

J. Pain. Symptom Manag. 36, 191–199 (2008)..

J、 疼痛。症状管理。36191-199（2008年）。。

Google Scholar

谷歌学者

Maetzler, W., Klucken, J. & Horne, M. A clinical view on the development of technology-based tools in managing Parkinson’s disease. Mov. Disord. 31, 1263–1271 (2016).PubMed

Maetzler，W.，Klucken，J。＆Horne，M。关于开发基于技术的帕金森病管理工具的临床观点。莫夫。混乱。311263-1271（2016）。PubMed出版社

Google Scholar

谷歌学者

Roussos, G. et al. Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease. NPJ Digit Med. 5, 93 (2022).PubMed

Roussos，G.等人，《识别和表征帕金森氏病数字结果测量变异的来源》。NPJ数字医学5,93（2022）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Djeldjli, D., Reguig, F. B. & Maaoui, C. A robust photoplethysmographic imaging for contactless heart and respiratory rates measurement using a simple webcam. Int. J. Med. Eng. Inform. 13, 224–236 (2021).

Djeldjli，D.，Reguig，F.B。＆Maaoui，C。一种强大的光体积描记成像，用于使用简单的网络摄像头进行非接触式心率和呼吸频率测量。国际医学工程通报。13224-236（2021）。

Google Scholar

谷歌学者

Grossman, P., Spoerle, M. & Wilhelm, F. H. Reliability of respiratory tidal volume estimation by means of ambulatory inductive plethysmography. Biomed. Sci. Instrum. 42, 193–198 (2006).PubMed

Grossman，P.，Spoerle，M。和Wilhelm，F。H。通过动态感应体积描记法估计呼吸潮气量的可靠性。生物医学。科学。仪器。42193-198（2006）。PubMed出版社

Google Scholar

谷歌学者

Sano, E. et al. Developing a novel mobile wearable tool of measuring real-time respiratory pattern and thoracic motion non-invasively. Respirology 24, 104 (2019).

。呼吸学24104（2019）。

Google Scholar

谷歌学者

Sneddon, G. et al. Cardiorespiratory physiology remotely monitored via wearable wristband photoplethysmography: Feasibility and initial benchmarking. Thorax 73, A197 (2018).

Sneddon，G.等人。通过可穿戴腕带光体积描记术远程监测心肺生理：可行性和初步基准测试。胸部73，A197（2018）。

Google Scholar

谷歌学者

Yilmaz, G. et al. A Wearable Stethoscope for Long-Term Ambulatory Respiratory Health Monitoring. Sensors 20, https://doi.org/10.3390/s20185124 (2020).Sheikh, M., Qassem, M. & Kyriacou, P. A. Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring. Front.

Yilmaz，G.等人。用于长期动态呼吸健康监测的可穿戴听诊器。传感器20，https://doi.org/10.3390/s20185124（2020年）。。

Digit Health 3, 662811 (2021).PubMed .

数字健康3662811（2021）。PubMed。

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Gonzalez-Robles, C. et al. Outcome Measures for Disease-Modifying Trials in Parkinson’s Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative. J. Parkinsons Dis. 13, 1011–1033 (2023).PubMed

Gonzalez-Robles，C.等。帕金森病疾病缓解试验的结果测量：EJS ACT-PD多臂多阶段试验倡议的共识文件。J、 。131011-1033（2023）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Chaudhuri, K. R. et al. The metric properties of a novel non-motor symptoms scale for Parkinson’s disease: Results from an international pilot study. Mov. Disord. 22, 1901–1911 (2007).PubMed

Chaudhuri，K.R.等人。帕金森病新型非运动症状量表的度量特性：一项国际试点研究的结果。莫夫。混乱。221901-1911（2007）。PubMed出版社

Google Scholar

谷歌学者

EU. Horizon 2020 Work Programme 2014-2015 (EU, 2014)Elhanbly, S. & Elkholy, A. Nocturnal penile erections: the role of RigiScan in the diagnosis of vascular erectile dysfunction. J. Sex. Med. 9, 3219–3226 (2012).PubMed

欧盟。地平线2020工作计划2014-2015（欧盟，2014）Elhanbly，S。＆Elkholy，A。夜间阴茎勃起：RigiScan在血管性勃起功能障碍诊断中的作用。J、 性别。医学93219-3226（2012）。PubMed出版社

Google Scholar

谷歌学者

Ortiz-Tudela, E., Martinez-Nicolas, A., Campos, M., Rol, M. A. & Madrid, J. A. A new integrated variable based on thermometry, actimetry and body position (TAP) to evaluate circadian system status in humans. PLoS Comput. Biol. 6, e1000996 (2010).PubMed

Ortiz-Tudela，E.，Martinez-Nicolas，A.，Campos，M.，Rol，M.A。＆Madrid，J.A。一种基于体温测量，活动测量和身体位置（TAP）的新综合变量，用于评估人体昼夜节律系统状态。PLoS计算机。生物学杂志6，e1000996（2010）。PubMed出版社

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Mankins, J. C. Technology readiness levels. White Pap. 6, 1995 (1995).

Mankins，J.C。技术准备水平。白色Pap。1995年6月（1995年）。

Google Scholar

谷歌学者

Download referencesAcknowledgementsJ.M.J.D. is supported by a Therapeutic Pipeline Grant of the Michael J. Fox Foundation (Grant ID MJFF-019201). A.M. receives grants from the Department of Defense of the Israeli Ministry of Justice, the Michael J Fox Foundation, and the EU Joint Program—Neurodegenerative Disease Research.

。M、 J.D.得到了迈克尔·J·福克斯基金会（Grant ID MJFF-019201）的治疗管道资助。A、 M.获得以色列司法部国防部，迈克尔·福克斯基金会和欧盟联合计划神经退行性疾病研究的资助。

Sirwan Darweesh was supported in part by a Parkinson’s Foundation- Postdoctoral Fellowship (PF-FBS-2026) and a Veni award (09150162010183). Bastiaan Bloem has received research support from Biogen, Cure Parkinson’s, Davis Phinney Foundation, Edmond J. Safra Foundation, Gatsby Foundation, Hersenstichting Nederland, Horizon 2020, IRLAB Therapeutics, Maag Lever Darm Stichting, Michael J Fox Foundation, Ministry of Agriculture, Ministry of Economic Affairs & Climate Policy, Ministry of Health, Welfare and Sport, Netherlands Organization for Scientific Research (ZonMw), Not Impossible, Parkinson Vereniging, Parkinson’s Foundation, Parkinson’s UK, Stichting Alkemade-Keuls, Stichting Parkinson NL, Stichting Woelse Waard, Topsector Life Sciences and Health, UCB, Verily Life Sciences, Roche and Zambon.Author informationAuthors and AffiliationsRadboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The NetherlandsJules M.

Sirwan Darweesh得到了帕金森基金会博士后奖学金（PF-FBS-2026）和维尼奖（09150162010183）的部分支持。巴斯蒂安·布洛姆（Bastiaan Bloem）获得了Biogen、治愈帕金森氏症、戴维斯·菲尼基金会、埃德蒙·J·萨弗拉基金会、盖茨比基金会、荷兰赫森斯蒂奇汀、地平线2020、IRLAB Therapeutics、Maag Lever Darm Stichting、迈克尔·J·福克斯基金会、农业部、经济事务与气候政策部、卫生、福利与体育部、荷兰科学研究组织（ZonMw）、并非不可能、帕金森·维伦金（Parkinson Vereniging）、帕金森基金会、帕金森英国、Stichting Alkemade Keuls、Stichting Parkinson NL、Stichting Woelse Waard、Topsector Life Sciences and Health等的研究支持。UCB，Verily Life Sciences，Roche和Zambon。作者信息作者和附属机构荷兰奈梅亨帕金森和运动障碍专业中心神经病学系Donders大脑，认知和行为研究所拉德布德大学医学中心。

Janssen Daalen, Robin van den Bergh, Eva M. Prins, Mahshid Sadat Chenarani Moghadam, Sirwan K. L. Darweesh, Luc J. W. Evers & Bastiaan R. BloemHAN University of Applied Sciences, School of Engineering and Automotive, Health Concept Lab, Arnhem, The NetherlandsRudie van den Heuvel & Jeroen VeenUnshakeableMD, Oshawa, ON, CanadaSoania MathurParkinsonNL, Parkinson Patient Association, Bunnik, The NetherlandsHa.

。

PubMed Google ScholarRobin van den BerghView author publicationsYou can also search for this author in

PubMed Google ScholarRobin van den BerghView作者出版物您也可以在

PubMed Google ScholarEva M. PrinsView author publicationsYou can also search for this author in

PubMed Google ScholarEva M.PrinsView作者出版物您也可以在

PubMed Google ScholarMahshid Sadat Chenarani MoghadamView author publicationsYou can also search for this author in

PubMed Google ScholarMahshid Sadat Chenarani MoghadamView作者出版物您也可以在

PubMed Google ScholarRudie van den HeuvelView author publicationsYou can also search for this author in

PubMed Google ScholarRudie van den HeuvelView作者出版物您也可以在

PubMed Google ScholarJeroen VeenView author publicationsYou can also search for this author in

PubMed谷歌学者Jeroen VeenView作者出版物您也可以在

PubMed Google ScholarSoania MathurView author publicationsYou can also search for this author in

PubMed Google ScholarSoania MathurView作者出版物您也可以在

PubMed Google ScholarHannie MeijerinkView author publicationsYou can also search for this author in

PubMed Google ScholarHannie MeijerinkView作者出版物您也可以在

PubMed Google ScholarAnat MirelmanView author publicationsYou can also search for this author in

PubMed Google ScholarAnat MirelmanView作者出版物您也可以在

PubMed Google ScholarSirwan K. L. DarweeshView author publicationsYou can also search for this author in

PubMed Google ScholarSirwan K.L.DarweeshView作者出版物您也可以在

PubMed Google ScholarLuc J. W. EversView author publicationsYou can also search for this author in

PubMed Google ScholarLuc J.W.EversView作者出版物您也可以在

PubMed Google ScholarBastiaan R. BloemView author publicationsYou can also search for this author in

PubMed Google ScholarBastiaan R.BloemView作者出版物您也可以在

PubMed Google ScholarContributionsJ.J.D., A.M., B.R.B.: conceptualization – J.J.D., R.B., E.P. M.S.C.M. R.H., J.V., S.M., H.M.: data curation, formal analysis, investigation, review & editing. – J.M.J.D., R.B., E.P., M.S.C.M.: original draft writing – J.M.J.D., R.B., A.M., S.K.L.D., L.E., B.R.B.: design, methodology, review & editing.Corresponding authorsCorrespondence to.

PubMed谷歌学术贡献。J、 D.，A.M.，B.R.B.：概念化-J.J.D.，R.B.，E.P.M.S.C.M.R.H.，J.V.，S.M.，H.M.：数据管理，正式分析，调查，审查和编辑J、 M.J.D.，R.B.，E.P.，M.S.C.M.：原稿写作-J.M.J.D.，R.B.，A.M.，S.K.L.D.，L.E.，B.R.B.：设计，方法，审查和编辑。通讯作者通讯。

Jules M. Janssen Daalen or Bastiaan R. Bloem.Ethics declarations

Jules M.Janssen Daalen或Bastiaan R.Bloem。道德宣言

Competing interests

相互竞争的利益

B.R.B. has received honoraria from serving on the scientific advisory board for Abbvie, Biogen, UCB, and Walk with Path (paid to the institute); has received fees for speaking at conferences from AbbVie, Zambon, Roche, GE Healthcare, and Bial (paid to the institute). A.M. receives consulting fees from Clexio; receives payment for lectures from Biogen; is on the advisory committee of the Michael J Fox Foundation; and is chair of the advisory board of the Michael J Fox Foundation.

B、 R.B.已从Abbvie，Biogen，UCB和Walk with Path的科学顾问委员会获得酬金（支付给研究所）；已收到AbbVie，Zambon，Roche，GE Healthcare和Bial（支付给研究所）的会议演讲费。A、 M.从Clexio收取咨询费；收到Biogen的讲座费用；是迈克尔·福克斯基金会咨询委员会的成员；他是迈克尔·福克斯基金会顾问委员会主席。

The other authors have nothing to disclose..

其他作者没有什么要披露的。。

Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSupplementary materialsRights and permissions

Additional informationPublisher的注释Springer Nature在已发布地图和机构隶属关系中的管辖权主张方面保持中立。补充信息补充材料权利和权限

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

开放获取本文是根据知识共享署名4.0国际许可证授权的，该许可证允许以任何媒体或格式使用，共享，改编，分发和复制，只要您对原始作者和来源给予适当的信任，提供知识共享许可证的链接，并指出是否进行了更改。

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

本文中的图像或其他第三方材料包含在文章的知识共享许可中，除非在材料的信用额度中另有说明。如果材料未包含在文章的知识共享许可证中，并且您的预期用途未被法律法规允许或超出允许的用途，则您需要直接获得版权所有者的许可。

To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/..

要查看此许可证的副本，请访问http://creativecommons.org/licenses/by/4.0/..

Reprints and permissionsAbout this articleCite this articleJanssen Daalen, J.M., van den Bergh, R., Prins, E.M. et al. Digital biomarkers for non-motor symptoms in Parkinson’s disease: the state of the art.

转载和许可本文引用本文Janssen Daalen，J.M.，van den Bergh，R.，Prins，E.M.等人。帕金森病非运动症状的数字生物标志物：最新技术。

npj Digit. Med. 7, 186 (2024). https://doi.org/10.1038/s41746-024-01144-2Download citationReceived: 05 January 2024Accepted: 22 May 2024Published: 11 July 2024DOI: https://doi.org/10.1038/s41746-024-01144-2Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

npj数字。医学杂志7186（2024）。https://doi.org/10.1038/s41746-024-01144-2Download引文收到日期：2024年1月5日接受日期：2024年5月22日发布日期：2024年7月11日OI：https://doi.org/10.1038/s41746-024-01144-2Share本文与您共享以下链接的任何人都可以阅读此内容：获取可共享链接对不起，本文目前没有可共享的链接。复制到剪贴板。

Provided by the Springer Nature SharedIt content-sharing initiative

由Springer Nature SharedIt内容共享计划提供