便携式帕金森病震颤监测评估系统的可靠性检验

Linda Zhu, Nathaniel S. Miller, Charlotte Tang, Sriram Pendyala, Quinn Hanses, Lacie Gladding
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引用次数: 0

摘要

震颤,或身体部位的不自主振荡运动,是帕金森病(PD)的主要症状,可显著影响PD患者的日常生活活动。虽然抗pd药物可以减轻震颤,但PwPD的药物效果参差不齐。因此,日常监测和评估震颤是PwPD,临床医生和研究人员感兴趣的。虽然已经开发了几种传感器和可穿戴设备并将其引入消费者市场,但高昂的成本限制了它们的可及性。目前的研究是双重的。首先,我们开发了一个基于多种算法的评估系统,用于评估PD症状测量的可靠性:手部震颤和手指/手运动速度。其次,设计并开发了一个Android移动应用程序,以捕获手指敲击频率并测量手部震颤等几种PD症状。在这项研究中,一名健康的年轻成人参与者产生了一种自发的震颤。参与者手持便携设备,按照应用程序内的说明进行自我测量。静息性震颤是在参与者将上肢放在椅子扶手上时测量的,体位性震颤是在参与者保持对抗重力的姿势时测量的,动态震颤是在运动任务中测量的。数据收集大约需要15分钟。直线运动和旋转运动分别由嵌入移动设备的加速度计和陀螺仪收集。结果被捕获并传送到一个云数据库。一个具有多种算法的评估系统提供了参与者震颤的最终评估。这个过程包括三个部分。首先,计算所有线性方向和旋转方向的均方根(RMS)值,以提供震颤强度。其次,快速傅里叶变换(FFT)提取各方向的峰值频率;比较各峰的幂次,将最高的峰定义为主导频率和该频率对应的运动方向。第三,用手和运动相关分析来寻找震颤在三维运动中的相干性。为了测试运动测量的可靠性,将相同的运动输入同时应用于多个设备。在考虑市场上移动设备的各种因素和模型(即设备尺寸、重量、操作系统、采样频率和测量过程中的准确性)的同时,评估不同类型移动设备的输出。为了测试评估系统的可靠性和移动应用程序的性能,进行了多次试验。此外,移动应用程序支持手指敲击测试,测量手部运动速度,这在PwPD中很常见。震颤和运动速度测量可用于评估疾病随时间的进展,并可支持基于症状数据的重点药物调整。
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Reliability Check of an Assessment System for Parkinson’s Disease Tremor Monitoring With Portable Devices
Tremor, or an involuntary and oscillatory movement of a body part, is a cardinal symptom of Parkinson’s disease (PD) that can significantly impact activities of daily living in people with PD (PwPD). Although tremor can be mitigated with anti-PD medications, medication effectiveness is mixed for PwPD. Therefore, daily monitoring and assessment of tremor are of interest to PwPD, clinicians, and researchers. While several sensors and wearable devices have been developed and introduced to the consumer market, high costs limit their accessibility. The current research is two-fold. First, an assessment system based on multiple algorithms is developed for evaluating the reliability of measurements of PD symptoms: hand tremor and finger/hand movement speed. Second, an Android mobile application was designed and developed to capture finger-tapping frequencies and measurements of several PD symptoms like hand tremor. A healthy young adult participant produced a self-generated tremor for this study. The participant held the portable device and conducted self-measurements by following in-app instructions. Resting tremor was measured while the participant rested his upper extremity on the arm of a chair, postural tremor was measured while he maintained a position against gravity, and kinetic tremor was measured during a movement task. Data collection took approximately fifteen minutes. The linear and rotational motions, respectively, were collected by accelerometers and gyroscopes embedded within the mobile device. The results were captured and delivered to a cloud database. An assessment system with multiple algorithms provided a final evaluation of the participant’s tremor. The process included three parts. First, calculation of root-mean-square (RMS) values at all linear and rotational directions was conducted to provide tremor strength. Second, fast Fourier transform (FFT) extracted the peak frequency at each direction. The powers of peaks were compared and the highest peak was defined as the dominant frequency and that frequency’s corresponding direction of motion. Third, hand and motion correlation analysis was used to find any coherence of tremor on 3-D motions. To test the reliability of motion measurement, the same motion input was applied to multiple devices simultaneously. The outputs of different types of mobile devices were evaluated, while considering various factors and models of mobile devices in the market (i.e., device size, weight, operating system, sampling frequency, and accuracy during the measurement). Multiple trials were conducted to test the reliability of the assessment system and the performance of the mobile app. Additionally, the mobile application supports finger tapping tests that measure hand movement speed, which is commonly impaired in PwPD. Both tremor and movement speed measurements can be used to evaluate disease progression over time and could support focused medication adjustments based on symptom data.
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