ACE-WP - Automatic Classification Extraction of Waveform Photoplethysmyography

ACE-WP是一个工业研究项目，旨在使用多阶段机器学习算法的新方法从组合的ECG和光电体积描记传感器中推断生物标志物信息。这项研究的主要目的是建立从手上测量血压的方法，其次是能够使用相同的技术产生生物识别安全性。通过这种方式，我们的目标是创建一个系统，为我们提供可用于多个行业的上市IP。我们已经拥有这些作品的背景专利，因此我们正在寻求通过这些作品将血压自动计算的水平提升到一个新的水平。通过从安装在手动操作设备（如智能手机）上的两个传感器组计算血压，我们实际上使消费者医疗保健能够在一个新的水平上自主操作。心血管系统可能是身体最重要的性能指标，到目前为止，系统只存在于方程的心血管方面。ACE-WP通过波形分析将心脏和血管方面结合在一起，使智能手机和医疗设备都能受益。

ACE-WP is an industrial research project aiming to use a new approach of multi-stage Machine Learning Algorithms to extrapolate biomarker information from combined ECG and Photoplethysmographic sensor. The primary aim of this research is to build on approach to the estimation of Blood Pressure when measured from the hands with the secondary aim of being able to produce Biometric security using the same technology. In such a manner we are aiming to create a system that gives us go-to-market IP that can be used in multiple industries. We already hold the background Patent for these works and so we are seeking to take the level of automatic calculation of Blood Pressure to the next level with these works. By calculating the Blood Pressure from the two sensor sets mounted on hand operated devices, such as Smartphones we are in effect enabling consumer healthcare to operate autonomously at a new level. The Cardiovascular system is perhaps the body's most significant indicator of performance and up until now, systems have only existed that look at the Cardio side of the equation. ACE-WP brings together both the Cardio and Vascular aspects through waveform analysis enabling Smartphones and Medical Devices alike to benefit.