ACE-WP - Automatic Classification Extraction of Waveform Photoplethysmyography

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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.