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Automatic Assessment System of Pulse Diagnosis for Treatment Effect Evaluation

机译:脉冲诊断自动评估系统治疗效果评价

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Pulse Diagnosis (PD) is a well-established diagnostic technique used in Traditional Chinese Medicine (TCM). The positions for PD are the radial arteries in the left and right wrists, and the pulse assessment is done by placing index, middle, and ring fingers on each wrist. The pulse of patients is then measured in the superficial, middle, and deep levels by TCM doctors to obtain more information regarding energy or Qi imbalance of the patients. For modern medical researches, PD is also used for indicating some status of patients. However, it is a challenging issue for all medical staff to properly assess the pulse of various patients. Therefore, this work proposes a systematic scheme to measure patient pulse by Photoplethysmography (PPG) sensors. An evaluation framework of some treatments, e.g., acupuncture therapy, is then built on top of the PPG sensing system with machine learning solutions. In our implementation, sensor data will be collected and transferred from Arduino platforms to our server for the PD assessment. The effect of the evaluated treatments will be estimated by the analysis of the PD results with machine learning supports. The major performance index is on the accuracy of the assessment for the treatments.
机译:脉冲诊断(PD)是一种熟悉的中医(TCM)中使用的良好诊断技术。 PD的位置是左手腕和右手腕的径向动脉,脉冲评估是通过放置每个手腕上的指数,中间和环形手指来完成的。然后,TCM医生在浅表,中间和深度水平中测量患者的脉冲,以获得有关患者的能量或QI失衡的更多信息。对于现代医学研究,PD也用于表明患者的某些地位。然而,所有医务人员都是一个具有挑战性的问题,以适当地评估各种患者的脉搏。因此,这项工作提出了一种系统方案来通过光增差测学(PPG)传感器来测量患者脉冲。然后,在具有机器学习解决方案的PPG传感系统之上,建立了一些处理的评估框架,例如针灸治疗。在我们的实施中,传感器数据将从Arduino平台收集并转移到我们的服务器以进行PD评估。通过对机器学习支持的PD结果分析,将估算评估治疗的效果。主要性能指数是对治疗评估的准确性。

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