An intelligent self-care application providing personalized preventive care using Machine Learning and AI-based analytical platform and IoT based sensors for continuous monitoring, early detection and better management of lifestyle diseases and their associated risks
Globally, more than 14 million people above the age of 30, die prematurely each year from lifestyle disease like diabetes, hypertension, heart diseases, and others. Some of these diseases have emerged as more fatal than hereditary or infectious diseases. As per International Diabetes Federation, 1 in 2 people with diabetes across the world is not aware of their disease condition. Almost the same is the case with Hypertension. According to NIH estimates, over 7 million deaths each year are attributable to hypertension and its complications. One major challenge is individuals suffering from hypertension are not even aware of their disease (>58%) which poses a great threat to their health.
An important way of controlling these lifestyle diseases is by controlling the risk factors associated with it such as behavioral or lifestyle habits. Monitoring the trends of the diseases and their associated risks on a real-time basis is crucial for managing the diseases. Management includes proper diagnosis and screening followed by its treatment. A primary healthcare approach is required where early detection and proper treatment are prioritized. Overall, our solution will bring down the disease burden by early detection and management of lifestyle diseases.
We are building an ecosystem where IoT and medical sources of data are integrated into a single platform along with tools for continuous health monitoring and management. Our SaaS (Software as a Service) platform combines several parameters like IoT, medical data, physiological and lifestyle data to generate the risk scores for lifestyle diseases. Variable data extracted from IoT devices are correlated with medical biomarkers to yield meaningful insights into the health patterns.
Our solution addresses the mentioned health problems through
1. Early detection of lifestyle diseases especially diabetes, hypertension, and sleep apnea. Using our state of the art algorithm and predictive model, we aim to predict the onset of such lifestyle diseases and help individuals to monitor their health.
2. Real-time monitoring using the integrated platform of IoT devices will make users aware of their health issues based on which they can make positive changes in their lifestyle habits.
3. Personalized recommendation engine: The recommendation engine will generate personalized alerts based on the deviations from the baseline. This helps users to be aware of their health and take necessary corrective actions when needed.
4. An ecosystem for complete health monitoring – Along with a platform that generates comprehensive reports and timely alerts, consultancy and guidance by medical professionals, dieticians, physical trainers, and others will be incorporated in the platform to provide overall direction and control on one’s health.
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