$GTCH company plans to use a non-invasive, photopl
Post# of 12925
(Total Views: 140)
Posted On: 08/24/2021 8:15:06 AM
$GTCH company plans to use a non-invasive, photoplethysmographic (PPG) optical sensors. This optical sensor technology can track small variations in blood biological substances through the skin and with the use of AI algorithms determine blood sugar levels. GBT is now running feasibility simulations to assess accuracy and options. GBT is already using optical sensors in its qTerm device to measure heart rate, and blood oxygen levels and plans to use this light sensing technology to monitor glucose levels.
A major key component for accurately measuring blood sugar levels is a machine learning algorithm that will continuously be monitoring blood changes and run analytics to produce these results. The results will be shown on a mobile and synchronized web application. The system will record the data and keep history as part of its health monitoring feature and in case of a concern the system will alert the user, and the data could be sent to a clinic or a physician through the internet for further evaluation. GBT believes that such a feature could be a significant addition to qTerm device making it a comprehensive, personal health watching system. qTerm can be used independently or as a telemedicine device enabling high quality medicine around the world.
"We are quite ambitions when it comes to our qTerm health watching device and constantly looking how to make it more comprehensive and efficient. Using the device optical sensors along with advanced artificial intelligence analytics, we are aiming to provide noninvasive blood glucose data simply with the touch of a finger. The hardware will sample blood elements data, providing it to a set of AI algorithms to conclude glucose levels. We believe this type of check, assuming fully developed, will be very appealing for diabetic patients due to its simplicity and noninvasive fashion. We strongly believe that this additional feature, if successfully developed, can be a major asset to qTerm, making it a comprehensive health watching device to assist with a healthy lifestyle,” said Danny Rittman, the Company CTO.
A major key component for accurately measuring blood sugar levels is a machine learning algorithm that will continuously be monitoring blood changes and run analytics to produce these results. The results will be shown on a mobile and synchronized web application. The system will record the data and keep history as part of its health monitoring feature and in case of a concern the system will alert the user, and the data could be sent to a clinic or a physician through the internet for further evaluation. GBT believes that such a feature could be a significant addition to qTerm device making it a comprehensive, personal health watching system. qTerm can be used independently or as a telemedicine device enabling high quality medicine around the world.
"We are quite ambitions when it comes to our qTerm health watching device and constantly looking how to make it more comprehensive and efficient. Using the device optical sensors along with advanced artificial intelligence analytics, we are aiming to provide noninvasive blood glucose data simply with the touch of a finger. The hardware will sample blood elements data, providing it to a set of AI algorithms to conclude glucose levels. We believe this type of check, assuming fully developed, will be very appealing for diabetic patients due to its simplicity and noninvasive fashion. We strongly believe that this additional feature, if successfully developed, can be a major asset to qTerm, making it a comprehensive health watching device to assist with a healthy lifestyle,” said Danny Rittman, the Company CTO.
(0)
(0)Scroll down for more posts ▼