A novel interactive eHealth platform for personalised and accessible Cardiac Rehabilitation (CaRe)

Ateleris is one of four collaborators on a European R&D project to build a novel interactive eHealth platform. Currently, Ateleris is developing a deep-learning-based training coach application to guide patients through rehabilitation exercises.

New pose detection demo available online.

EUREKA/Eurostars is a European intergovernmental organization for fostering pan-European research, development, and innovation collaborations among SMEs. EUREKA is providing support and funding for industry-led R&D collaborations.

The CaRe project 12527 with the title “A novel interactive mHealth platform for personalised and accessible Cardiac Rehabilitation” was accepted and funded in October 2018 through October 2021.

The CaRe consortium consists of the two Danish companies Wellfaster and Tutee, the Dutch university medical center Radboud UMC, and the Swiss company Ateleris.

The CaRe project aims at building a platform for providing personalized experiences and better guidance for cardiac rehabilitation patients. The platform helps patients to stay motivated and actively engaged in their rehabilitation programs. Studies have shown that only 30-40% of all cardiac patients fully complete their rehabilitation programs.

Ateleris is providing machine learning and analytics know-how and is developing smart decision-making algorithms.

Ateleris engineered a heart rate measurement and analytics Android app (based on the Ionic framework and Cordova). By solely using the mobile phone’s flashlight and camera, the app was able to read a patient’s pulse.

Currently, Ateleris is building a rehabilitation training coach application in C#. The training coach uses Deep Learning models and advanced algorithms to recognize patients doing their rehabilitation exercises. It can measure the training exercise accuracy, count the repetitions, and give live feedback to the patient (see video at the top of this article).

Furthermore, Ateleris is actively supporting Radboud UMC in their data analysis tasks to help them gain additional insights from previously executed patient studies. With Ateleris’ support, they can improve future studies in the CaRe project frame, which will help further enhance the CaRe platform performance.

Key Technologies/Terms
  • Exploratory data analytics
  • Machine learning (Clustering algorithm, Deep Learning)
  • Skeleton detection, keypoint detection
  • Python, R, C#
  • Ionic framework, Cordova, Android development
  • eHealth/mHealth
  • EUREKA/Eurostars European collaboration
Wellfaster Logo

Wallfaster is an eHealth and platform provider for virtual training technologies.

Tutee Logo

Tutee is a Danish tech company that develops cloud-based learning and education platforms.

Radboud University Medical Center

The Radboud University Medical Center is the teaching hospital affiliated with the Radboud University Nijmegen in Nijmegen in the eastern-central part of the Netherlands.

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Silvan Laube

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