Wearable tremor suppression devices (WTSD) have been considered as a viable solution to manage parkinsonian tremor. WTSDs showed their ability to improve the quality of life of individuals suffering from parkinsonian tremor, by helping them to perform activities of daily living (ADL). Since parkinsonian tremor has been shown to be nonstationary, nonlinear, and stochastic in nature, the performance of the tremor models used by WTSDs is affected by their inability to adapt to the nonlinear behaviour of tremor. Another drawback that the models have is their limitation to estimate or predict one step ahead, which introduces delay when used in real time with WTSDs, which compromises performance. To address these issues, this work proposes a deep neural network model that learns the correlations and nonlinearities of tremor and voluntary motion, and is capable of multi-step prediction with minimal delay. A generalized model that is task and user-independent is presented. The model achieved an average estimation percentage accuracy of 99.2%. The average future voluntary motion prediction percentage accuracy with 10, 20, 50, and 100 steps ahead was 97.0%, 94.0%, 91.6%, and 89.9%, respectively, with prediction time as low as 1.5 ms for 100 steps ahead. The proposed model also achieved an average of 93.8% ± 1.5% in tremor reduction when it was tested in an experimental setup in real time. The tremor reduction showed an improvement of 25% over the Weighted Fourier Linear Combiner (WFLC), an estimator commonly used with WTSDs.

中文翻译：

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使用深度神经网络进行实时自主运动预测和帕金森氏震颤减轻


可穿戴式震颤抑制设备（WTSD）已被认为是治疗帕金森氏震颤的可行解决方案。 WTSD 展示了通过帮助帕金森震颤患者进行日常生活活动 (ADL) 来改善他们的生活质量的能力。由于帕金森震颤本质上是非平稳、非线性和随机的，因此 WTSD 使用的震颤模型的性能因其无法适应震颤的非线性行为而受到影响。该模型的另一个缺点是它们在估计或预测前一步方面存在局限性，这会在与 WTSD 实时使用时引入延迟，从而影响性能。为了解决这些问题，这项工作提出了一种深度神经网络模型，该模型可以学习震颤和随意运动的相关性和非线性，并且能够以最小的延迟进行多步预测。提出了一个独立于任务和用户的通用模型。该模型的平均估计百分比准确度为 99.2%。提前 10、20、50 和 100 步的未来自主运动预测平均准确率分别为 97.0%、94.0%、91.6% 和 89.9%，提前 100 步的预测时间低至 1.5 毫秒。当在实验装置中进行实时测试时，所提出的模型还实现了平均 93.8% ± 1.5% 的震颤减少。与加权傅立叶线性组合器 (WFLC)（WTSD 常用的估计器）相比，震颤减少效果提高了 25%。