Turn raw health data into actionable insights with algorithms optimized for your connected health device.
Connected health solutions such as an ingestible capture enormous amounts of data. How do you turn that into meaningful information and actionable insights? Count on imec to develop the algorithms that make your application truly smart.
Calculating body movements from the measurements of kinematic sensors, determining the heart rate from the readings of a vital sign monitoring device, ...
Imec develops a lot of algorithms that accurately characterize – often in real time – the collected mass of raw data. It’s a crucial step towards your development of clinical-grade connected health solutions.
These data analysis algorithms perform different data processing steps: from cleaning up noisy data to signal quality prediction. This last function is particularly important in neurotechnology applications, where users need to assess the reliability of the data before starting the procedure.
Once you have these filtered and reliable data sets, you can mine them for deeper meanings. For example:
It’s this layer of algorithms that opens the door towards advanced connected health applications that combine unobtrusive monitoring with reliable feedback – encouraging healthy behaviors and lifestyle choices.
If we want to integrate medical wearables seamlessly into our active lives, we need to make sure that they:
That’s why imec, driven by its vision of edge AI, devotes special attention to the co-optimization of device hardware and algorithms – resulting in exceptionally efficient solutions.
Want to join our research? Need an experienced partner to speed up your development?