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首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >A Clinical Applicable Smartwatch Application for Measuring Hyperkinetic Movement Disorder Severity
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A Clinical Applicable Smartwatch Application for Measuring Hyperkinetic Movement Disorder Severity

机译：用于测量运动过度运动严重程度的临床适用Smartwatch应用程序

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Measuring the severity of hyperkinetic movement disorders like tremor and myoclonus is challenging. Although many accelerometers are available to quantify movements, the vast majority lacks real-time analysis and an interface that makes it possible to real-time adjust therapy like deep brain stimulation (DBS). Here, we developed a smartwatch / smartphone application that is capable of real-time analysing movement disorder severity. Movement analysis was realised by integrating acceleration values, to velocity and subsequently to distance. Measured distances were compared with a validated accelerometer already applied for quantifying movement disorders. Further validation was done by quantitative assessment of simulated movement disorders in 10 healthy volunteers. Finally, the approach was tested in two patients treated with DBS to quantify the effect of different DBS settings on myoclonus and tremor severity, respectively. The distance measured with the application had a 96% accuracy. This was non-inferior (p = 0.76) compared to accelerometers already clinically applied. Furthermore, (simulated) movement disorder severity could be classified correctly in 93% of the cases. Finally, the method was capable of distinguishing effective from non-effective DBS parameters in two patients. In summary, with our approach we realised an instantaneous and reliable estimation of the severity of movement disorders which can assist in real time titrating therapy like DBS.
机译：测量诸如震颤和肌阵挛之类的运动过度运动障碍的严重程度具有挑战性。尽管有许多加速度计可用于量化运动，但绝大多数加速度计缺乏实时分析和接口，无法像深部脑刺激（DBS）那样实时调整治疗方法。在这里，我们开发了一种智能手表/智能手机应用程序，能够实时分析运动障碍的严重程度。通过对加速度值，速度和距离进行积分来实现运动分析。将测得的距离与已经用于量化运动障碍的经过验证的加速度计进行比较。通过对10名健康志愿者的模拟运动障碍进行定量评估，进行了进一步的验证。最后，该方法在两名接受DBS治疗的患者中进行了测试，以分别量化不同DBS设置对肌阵挛和震颤严重程度的影响。使用该应用程序测量的距离的准确性为96％。与临床上已经应用的加速度计相比，这是不逊色的（p = 0.76）。此外，在93％的病例中，（模拟的）运动障碍严重程度可以正确分类。最后，该方法能够区分两名患者的有效DBS参数和无效DBS参数。总而言之，通过我们的方法，我们实现了对运动障碍严重程度的即时且可靠的估计，可以帮助实时滴定治疗（例如DBS）。

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