VivaLNK, Campbell, CA, has launched its IoT-enabled medical wearable Sensor Platform, complete with a range of sensors, edge computing technologies, and an Internet of Health Things (IoHT) data cloud. This unique platform captures human vitals and biometrics, and delivers data from the patient to edge computing devices as well as the cloud for application integration and analysis.

Available through the VivaLNK Developer Program, the Sensor Platform enables IoHT partners to easily capture streams of patient data such as heart and respiratory rates, temperature, ECG rhythms, activity, and more. Partners such as Australia-based Vitalic Medical, a digital health innovator in the early detection of patient health deterioration and potential falls, is developing a bedside monitoring solution using the platform.

“Our growing aging patient population, a rise in complex health conditions, and increasing staff workloads makes it challenging for medical professionals to detect early signs of patient deterioration and prevent falls," says Sue Dafnias, CEO of Vitalic Medical. "By leveraging VivaLNK wearable sensor within the Vitalic platform, Vitalic Medical can offer an early trigger system that helps nurses identify early signs of patient deterioration and fall-risk patients."

IoHT has the potential to significantly change healthcare for the better, and the key starts with data. Much of the machine learning and intelligence will come from user generated data that currently doesn’t exist or is not easily accessible. This is where wearable devices collecting medical-grade data that can easily connect to networked applications becomes crucial.

"The launch of our Sensor Platform is instrumental in helping solution partners accelerate medical and healthcare innovation to market, especially within crucial therapeutic areas such as cardiology, cancer, chronic disease and more," says Jiang Li, CEO at VivaLNK. “To have a more complete picture of patient health, applications and algorithms not only need access to data, but a variety of relevant data that can be used to correlate and accurately assess and predict health situations.”