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通过智能手机识别和量化神经功能障碍

Identifying and Quantifying Neurological Disability via Smartphone.

作者信息

Boukhvalova Alexandra K, Kowalczyk Emily, Harris Thomas, Kosa Peter, Wichman Alison, Sandford Mary A, Memon Atif, Bielekova Bibiana

机构信息

Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United States.

Department of Computer Science, University of Maryland, College Park, MD, United States.

出版信息

Front Neurol. 2018 Sep 4;9:740. doi: 10.3389/fneur.2018.00740. eCollection 2018.

Abstract

Embedded sensors of the smartphones offer opportunities for granular, patient-autonomous measurements of neurological dysfunctions for disease identification, management, and for drug development. We hypothesized that aggregating data from two simple smartphone tests of fine finger movements with differing contribution of specific neurological domains (i.e., strength & cerebellar functions, vision, and reaction time) will allow establishment of secondary outcomes that reflect domain-specific deficit. This hypothesis was tested by assessing correlations of smartphone-derived outcomes with relevant parts of neurological examination in multiple sclerosis (MS) patients. We developed MS test suite on Android platform, consisting of several simple functional tests. This paper compares cross-sectional and longitudinal performance of Finger tapping and Balloon popping tests by 76 MS patients and 19 healthy volunteers (HV). The primary outcomes of smartphone tests, the average number of taps (per two 10-s intervals) and the average number of pops (per two 26-s intervals) differentiated MS from HV with similar power to traditional, investigator-administered test of fine finger movements, 9-hole peg test (9HPT). Additionally, the secondary outcomes identified patients with predominant cerebellar dysfunction, motor fatigue and poor eye-hand coordination and/or reaction time, as evidenced by significant correlations between these derived outcomes and relevant parts of neurological examination. The intra-individual variance in longitudinal sampling was low. In the time necessary for performing 9HPT, smartphone tests provide much richer and reliable measurements of several distinct neurological functions. These data suggest that combing more creatively-construed smartphone apps may one day recreate the entire neurological examination.

摘要

智能手机的嵌入式传感器为精确、患者自主测量神经功能障碍提供了机会,可用于疾病识别、管理以及药物研发。我们假设,汇总来自两项简单的智能手机精细手指运动测试的数据(这两项测试对特定神经领域的贡献不同,即力量与小脑功能、视觉和反应时间)将有助于建立反映特定领域缺陷的次要结果。通过评估智能手机衍生结果与多发性硬化症(MS)患者神经检查相关部分的相关性,对这一假设进行了检验。我们在安卓平台上开发了MS测试套件,其中包括多项简单的功能测试。本文比较了76名MS患者和19名健康志愿者(HV)进行手指敲击和气球爆破测试的横断面和纵向表现。智能手机测试的主要结果,即平均敲击次数(每两个10秒间隔)和平均爆破次数(每两个26秒间隔),区分MS患者和HV的能力与传统的、由研究人员进行的精细手指运动测试——9孔插钉测试(9HPT)相当。此外,次要结果识别出了主要存在小脑功能障碍、运动疲劳以及眼手协调和/或反应时间较差的患者,这些衍生结果与神经检查相关部分之间的显著相关性证明了这一点。纵向采样中的个体内方差较低。在进行9HPT所需的时间内,智能手机测试能够对几种不同的神经功能进行更丰富、可靠的测量。这些数据表明,更具创造性构建的智能手机应用程序结合起来,也许有一天能够重现整个神经检查。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e59/6131483/9438dbd8f0ba/fneur-09-00740-g0001.jpg

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