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本文引用的文献

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Monitoring motor fluctuations in patients with Parkinson's disease using wearable sensors.使用可穿戴传感器监测帕金森病患者的运动波动情况。
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Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results.运动障碍协会赞助的统一帕金森病评定量表修订版(MDS-UPDRS):量表介绍及临床测量测试结果
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Parkinson's disease: clinical features and diagnosis.帕金森病:临床特征与诊断
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Ambulatory monitoring of freezing of gait in Parkinson's disease.帕金森病步态冻结的动态监测。
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Quantitative gait analysis in Parkinson's disease: comparison with a healthy control group.帕金森病的定量步态分析:与健康对照组的比较。
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Gait assessment in Parkinson's disease: toward an ambulatory system for long-term monitoring.帕金森病的步态评估:迈向用于长期监测的动态系统
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Sleep disorder related to Parkinson's disease.与帕金森病相关的睡眠障碍。
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Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases.特发性帕金森病临床诊断的准确性:100例临床病理研究
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借助可穿戴技术和大数据分析实现帕金森病研究的突破。

Enabling breakthroughs in Parkinson's disease with wearable technologies and big data analytics.

作者信息

Cohen Shahar, Bataille Lauren R, Martig Adria K

机构信息

Intel Corporation, Azorim Park, Petach Tikva, Israel.

The Michael J. Fox Foundation for Parkinson's Research, New York, NY, USA.

出版信息

Mhealth. 2016 May 12;2:20. doi: 10.21037/mhealth.2016.04.02. eCollection 2016.

DOI:10.21037/mhealth.2016.04.02
PMID:28293596
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5344108/
Abstract

Parkinson's disease (PD) is a progressive, degenerative disorder of the central nervous system that is diagnosed and measured clinically by the Unified Parkinson's Disease Rating Scale (UPDRS). Tools for continuous and objective monitoring of PD motor symptoms are needed to complement clinical assessments of symptom severity to further inform PD therapeutic development across several arenas, from developing more robust clinical trial outcome measures to establishing biomarkers of disease progression. The Michael J. Fox Foundation for Parkinson's Disease Research and Intel Corporation have joined forces to develop a mobile application and an Internet of Things (IoT) platform to support large-scale studies of objective, continuously sampled sensory data from people with PD. This platform provides both population and per-patient analyses, measuring gait, activity level, nighttime activity, tremor, as well as other structured assessments and tasks. All data collected will be available to researchers on an open-source platform. Development of the IoT platform raised a number of engineering considerations, including wearable sensor choice, data management and curation, and algorithm validation. This project has successfully demonstrated proof of concept that IoT platforms, wearable technologies and the data they generate offer exciting possibilities for more robust, reliable, and low-cost research methodologies and patient care strategies.

摘要

帕金森病(PD)是一种中枢神经系统的进行性退行性疾病,临床上通过统一帕金森病评定量表(UPDRS)进行诊断和评估。需要用于持续、客观监测帕金森病运动症状的工具,以补充对症状严重程度的临床评估,从而在多个领域为帕金森病治疗的发展提供更多信息,从制定更可靠的临床试验结果测量方法到确定疾病进展的生物标志物。迈克尔·J·福克斯帕金森病研究基金会与英特尔公司联手开发了一款移动应用程序和一个物联网(IoT)平台,以支持对帕金森病患者的客观、连续采样的感官数据进行大规模研究。该平台提供总体分析和个体患者分析,可测量步态、活动水平、夜间活动、震颤以及其他结构化评估和任务。收集到的所有数据将在一个开源平台上提供给研究人员。物联网平台的开发引发了一些工程方面的考虑,包括可穿戴传感器的选择、数据管理与整理以及算法验证。该项目已成功证明了概念验证,即物联网平台、可穿戴技术及其生成的数据为更强大、可靠且低成本的研究方法和患者护理策略提供了令人兴奋的可能性。