Hybrid Decoders for Marked Point Process Observations and External Influences
Hybrid Decoders for Marked Point Process Observations and External Influences
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用于标记点过程观察和外部影响的混合解码器
DOI：
10.1109/tbme.2022.3191243
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发表时间：
2023
影响因子：
4.6
通讯作者：
Faghih, Rose T.
中科院分区：
文献类型：
--
作者：
Wickramasuriya, Dilranjan S.;Crofford, Leslie J.;Widge, Alik S.;Faghih, Rose T.
内部生理过程控制着人体内的多个状态变量。从点过程型生物电和生物化学观测估计这些是一个挑战。在这里，我们寻求基于点过程和连续值数据来估计皮质醇相关的能量产生和交感神经觉醒，同时允许外部影响影响状态估计。方法传统的点过程状态空间方法，例如用于估计上述量的方法分别从皮质醇和皮肤电导测量，无法允许国家估计也适应外部影响在这里，我们修改了现有的递归神经网络（RNN）方法，通过加权成本进行状态空间估计，函数，使一个混合估计，具有这种capability.ResultsResults结果皮质醇数据的基础上假设的睡眠-觉醒的影响长期显示如何能源生产可以估计允许的估计，以适应外部的影响，尽可能多的期望。我们进一步展示了如何过拟合可能会减少使用基于昼夜节律的影响条款。皮肤电导数据的结果还表明，该方法如何用于在包含压力源和放松的实验中估计交感神经唤醒，结论基于RNN的混合方法能够从点过程和连续过程中恢复内部生理状态。有价值的观察，同时允许外部影响来指导估计。重要性混合估计器可以嵌入可穿戴设备中，可以根据领域专业知识或个人反馈量身定制的监视器。
ObjectiveInternal physiological processes govern multiple state variables within the human body. Estimating these from point process-type bioelectric and biochemical observations is a challenge. Here we seek to estimate cortisol-related energy production and sympathetic arousal based on point process and continuous-valued data while permitting an external influence to affect the state estimates.MethodsTraditional point process state-space methods, such as those used for estimating the aforementioned quantities from cortisol and skin conductance measurements respectively, suffer from the inability to permit the state estimates to also fit to an external influence (e.g. labels) or be guided by it. Here we modify an existing recurrent neural network (RNN) approach for state-space estimation through a weighted cost-function to enable a hybrid estimator that has this capability.ResultsResults on cortisol data based on a hypothetical sleep-wake influence term show how energy production can be estimated by permitting the estimates to fit to the external influence as much as desired. We further show how overfitting may be reduced by using circadian rhythm-based influence terms. Results on skin conductance data also indicate how the method can be used to estimate sympathetic arousal in an experiment containing stressors and relaxation, and permit an external influence as well.ConclusionThe RNN-based hybrid method is thus able to recover internal physiological states from point process and continuous-valued observations while permitting an external influence to guide the estimates.SignificanceThe hybrid estimator could be embedded within wearable monitors that can be tailored based on domain expertise or individual feedback.
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