Royal Philips Electronics, the parent company of Philips Healthcare of Andover, MA, will lead a European Union-funded research project to improve the care of heart patients with telemonitoring technology, the company reported.
The EU's HeartCycle project will begin March 1, and will develop systems for monitoring the condition of coronary heart disease and heart failure patients. The systems will include sensors built into a patient's clothing or bed linens, as well as home appliances such as weight scales and blood pressure monitors.
Philips of Amsterdam, Netherlands, is leading a consortium of 18 research, academic, industrial, and medical organizations from nine different European countries and China. The group will develop software to analyze acquired data and provide feedback on a patient's health and compliance to prescribed therapies. The software will also report data to clinicians automatically.
The project will run for four years, and has a budget of 21 million euros ($31 million), Philips said.
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![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
