Aalto University project develops data-driven methods for the prediction of sudden cardiac deaths

RemoteA  participates in an Aalto University project for the development of new computational methods for diagnosing heart diseases with ECG. The aim of the project is to provide robust data-driven methods for the prediction of sudden cardiac deaths from long-term cardiac recordings. Besides RemoteA, also GE Healthcare and Spektikor participatein the project. The project, co-funded by Tekes, started in spring 2017 and will be finished by the end of 2018.

The project is related to the digitalization of health technology, personalized health care planning, and the use of data science technologies to improve outpatient care, including reducing the average length of stay of in-patients in hospitals.

The primary sensory modality is ECG, but the aim is to use also movement sensors as well as other sensors for enhanced reliability. The main focus areas are advanced data analysis, software aspects and signal processing, such as EKF (Extended Kalman Filters).

The project applies the latest classification methods in machine learning as well as advanced signal processing methods, that have previously been used in for example space technology and navigation applications.

RemoteA brings to the project its service operator and data-driven automatic diagnostics expertise. RemoteA, in turn,  has the opportunity to implement the outcomes of the Aalto University state-of-the-art methodology research in its own development.

For more information:

RemoteA Ltd, Jarno Mäkelä, CTO, jarno.makela@remotea.com

Aalto-yliopisto, Lauri Palva, lauri.palva@aalto.fi, +358 50 316 1033 sekä Simo Särkkä, simo.sarkka@aalto.fi

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