Johns Hopkins University School of Medicine, Baltimore, Maryland.
Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, California.
Ann Clin Transl Neurol. 2020 Mar;7(3):288-295. doi: 10.1002/acn3.50988. Epub 2020 Feb 26.
To create a novel neurological vital sign and reliably capture MS-related limb disability in less than 5 min.
Consecutive patients meeting the 2010 MS diagnostic criteria and healthy controls were offered enrollment. Participants completed finger and foot taps wearing the MYO-band© (accelerometer, gyroscope, and surface electromyogram sensors). Signal processing was performed to extract spatiotemporal features from raw sensor data. Intraclass correlation coefficients (ICC) assessed intertest reproducibility. Spearman correlation and multivariable regression methods compared extracted features to physician- and patient-reported disability outcomes. Partial least squares regression identified the most informative extracted textural features.
Baseline data for 117 participants with MS (EDSS 1.0-7.0) and 30 healthy controls were analyzed. ICCs for final selected features ranged from 0.80 to 0.87. Time-based features distinguished cases from controls (P = 0.002). The most informative combination of extracted features from all three sensors strongly correlated with physician EDSS (finger taps r = 0.77, P < 0.0001; foot taps r = 0.82, P < 0.0001) and had equally strong associations with patient-reported outcomes (WHODAS, finger taps r = 0.82, P < 0.0001; foot taps r = 0.82, P < 0.0001). Associations remained with multivariable modeling adjusted for age and sex.
Extracted features from the multi-sensor demonstrate striking correlations with gold standard outcomes. Ideal for future generalizability, the assessments take only a few minutes, can be performed by nonclinical personnel, and wearing the band is nondisruptive to routine practice. This novel paradigm holds promise as a new neurological vital sign.
创建一种新颖的神经生命体征,并在不到 5 分钟的时间内可靠地捕捉到与多发性硬化症相关的肢体残疾。
连续符合 2010 年多发性硬化症诊断标准的患者和健康对照者被邀请参加。参与者在佩戴 MYO 带(加速度计、陀螺仪和表面肌电图传感器)时完成手指和脚部敲击。信号处理用于从原始传感器数据中提取时空特征。组内相关系数(ICC)评估了测试间的可重复性。Spearman 相关和多变量回归方法将提取的特征与医生和患者报告的残疾结果进行比较。偏最小二乘回归确定了最具信息量的提取纹理特征。
对 117 名多发性硬化症患者(EDSS 1.0-7.0)和 30 名健康对照者的基线数据进行了分析。最终选择的特征的 ICC 范围为 0.80-0.87。基于时间的特征可区分病例和对照者(P=0.002)。来自所有三个传感器的提取特征的最具信息量的组合与医生 EDSS 高度相关(手指敲击 r=0.77,P<0.0001;脚部敲击 r=0.82,P<0.0001),与患者报告的结果也有很强的关联(WHODAS,手指敲击 r=0.82,P<0.0001;脚部敲击 r=0.82,P<0.0001)。在调整年龄和性别后,多变量模型仍具有相关性。
从多传感器提取的特征与黄金标准结果具有显著相关性。这种评估方法非常适合未来的推广,仅需几分钟即可完成,可以由非临床人员进行,并且佩戴带不会干扰日常实践。这种新的范式有望成为一种新的神经生命体征。