Van Someren Eus J W, Pticek Myrthe D, Speelman Johannes D, Schuurman Peter R, Esselink Rianne, Swaab Dick F
Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.
Mov Disord. 2006 Aug;21(8):1136-43. doi: 10.1002/mds.20900.
A new method of movement analysis is validated, allowing an actigraph to discriminate tremor from other movements and store duration and intensity measures of both movement types. For algorithm optimization, wrist acceleration was recorded in nine controls and nine Parkinson's disease patients, while simultaneously rating their observed tremor minute by minute on item 20 of the Unified Parkinson's Disease Rating Scale. An optimization procedure to minimize false positives in controls while maximizing tremor detection in patients resulted in false positive tremor classification in 2.4% +/- 2.5% of the movement time of control subjects (range, 0%-7%), while providing tremor classification in 82.1% +/- 15.4% of the movement time in patients (range, 55%-100%), correlating r = 0.93 with their averaged observed tremor score. A second, generalizability study showed that application of the optimized algorithm resulted in accurate classification of 71% +/- 14% of the observed tremor time (range, 46%-90%) in another 9 patients and in a false positive classification in only 0.5% +/- 0.8% of the time in another 10 controls (range, 0%-2.4%). The commercial availability of this actigraph now for the first time makes it possible to investigate tremor fluctuations over several weeks. An example is given of how long-term monitoring can be of use in evaluation of symptom management.
一种新的运动分析方法得到了验证,使得活动记录仪能够区分震颤与其他运动,并存储两种运动类型的持续时间和强度测量值。为了优化算法,记录了9名对照者和9名帕金森病患者的手腕加速度,同时根据统一帕金森病评定量表的第20项逐分钟对他们观察到的震颤进行评分。一种优化程序,在尽量减少对照者假阳性的同时最大化患者震颤检测率,结果显示对照者运动时间的2.4%±2.5%(范围为0%-7%)出现震颤假阳性分类,而患者运动时间的82.1%±15.4%(范围为55%-100%)实现震颤分类,与他们的平均观察震颤评分的相关系数r = 0.93。第二项普遍性研究表明,应用优化算法在另外9名患者中对71%±14%(范围为46%-90%)的观察震颤时间进行了准确分类,在另外10名对照者中仅0.5%±0.8%(范围为0%-2.4%)的时间出现假阳性分类。这种活动记录仪的商业可用性首次使得研究数周内的震颤波动成为可能。文中给出了一个长期监测如何用于评估症状管理的例子。