Advanced Peak Detection Algorithm

Real-Time Heart

Rate Variability Processing 

Real-Time Cardiac Signal Processing 

Real-Time Respiration Signal Processing 

Olea HeartSignature

OleaSense™ Machine Learning Diagnostics

OleaSense™ Machine Learning Diagnostics Demo

Machine learning, a subdiscipline in the field of artificial intelligence (AI), focuses on algorithms capable of learning and/or adapting their structure (e.g., parameters) based on a set of observed data, with adaptation done by optimizing over an objective or cost function. OleaSense™ utilizes advanced machine learning and statistical pattern recognition technologies which have been the subject of tremendous interest in the biomedical community because they offer promise for improving the sensitivity and/or specificity of detection and diagnosis of disease, while at the same time increasing the objectivity of the decision-making process.

 

The OleaSense™ demo displays our advanced software development platform which processes real-time data from the OS-3010 detailing the use of real-time cardiac signal processing, advanced peak detection algorithms, real-time respiration signal processing and extracts vital sign statistics such as real-time heart-rate variability. Below is a mobile-friendly video of the OleaSense™ Demo. 

Olea's Advanced Dashboard GUI

Below is Olea's advanced dash board GUI that can be embedded in all platform such as tablets, smartphones and PCs. The GUI captures all the real-time data processed by the OleaSense™ software platform. Inspired by the science fiction movie Star Trek, the Olea GUI captures all of the vital sign statistics that is IoT compatible for remote health monitoring.

Olea HeartSignature™️ is like no other authentication technology in its ability to continuously identify an individual in real time using contact-less, wireless detection of vital signs to create a unique digital "signature" for limitless security applications.

 

Click through to learn more about our development platforms: Development Platforms.