Wearable Sensors for Estimation of Parkinsonian Tremor Severity during Free Body Movements
Wearable Sensors for Estimation of Parkinsonian Tremor Severity during Free Body Movements
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DOI：
10.3390/s19194215
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发表时间：
2019-10-01
期刊：
影响因子：
3.9
通讯作者：
Ghoraani, Behnaz
中科院分区：
文献类型：
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作者：
Hssayeni, Murtadha D.;Jimenez-Shahed, Joohi;Ghoraani, Behnaz
震颤是帕金森病（PD）的主要症状之一，降低了生活质量。震颤作为统一帕金森病评定量表（UPDRS）第三部分的一部分进行测量。然而，评估是基于现场的身体检查，并不能完全代表患者在日常生活中的震颤经历。我们在论文中的目标是开发一种算法，结合可穿戴传感器，可以在患者进行各种自由身体运动时估计帕金森病的总震颤。我们开发了两种方法：基于梯度树增强的集成模型和基于长短期记忆（LSTM）网络的深度学习模型。利用24例PD患者的陀螺仪传感器数据对所开发的方法进行了评估。我们的分析表明，与基于lstm的方法相比，基于梯度树增强的方法在估计和临床评估的震颤亚评分之间提供了高相关性（使用持空测试r = 0.96，使用基于受试者的留一交叉验证r = 0.93），具有中等相关性（使用持空测试r = 0.84，使用基于受试者的留一交叉验证r = 0.77）。这些结果表明，我们的方法在通过连续监测受试者在自然环境中的运动来提供患者震颤的全谱方面具有很大的前景。
Tremor is one of the main symptoms of Parkinson's Disease (PD) that reduces the quality of life. Tremor is measured as part of the Unified Parkinson Disease Rating Scale (UPDRS) part III. However, the assessment is based on onsite physical examinations and does not fully represent the patients' tremor experience in their day-to-day life. Our objective in this paper was to develop algorithms that, combined with wearable sensors, can estimate total Parkinsonian tremor as the patients performed a variety of free body movements. We developed two methods: an ensemble model based on gradient tree boosting and a deep learning model based on long short-term memory (LSTM) networks. The developed methods were assessed on gyroscope sensor data from 24 PD subjects. Our analysis demonstrated that the method based on gradient tree boosting provided a high correlation (r = 0.96 using held-out testing and r = 0.93 using subject-based, leave-one-out cross-validation) between the estimated and clinically assessed tremor subscores in comparison to the LSTM-based method with a moderate correlation (r = 0.84 using held-out testing and r = 0.77 using subject-based, leave-one-out cross-validation). These results indicate that our approach holds great promise in providing a full spectrum of the patients' tremor from continuous monitoring of the subjects' movement in their natural environment.