INSIDE: Predictive monitoring and causality for cardiac rehabilitation
The INSIDE project aims to address adherence issues in Cardiac Rehabilitation, focusing on three complementary perspectives. Firstly, the project seeks to enhance predictive models for dropout rates and cardiovascular risk to improve the personalization and optimization of the patients' treatment. Secondly, INSIDE aims to develop methods for accurately discerning patient mood from physiological variables recorded via wearable devices during program participation. Finally, the project will synthesize information from the first two phases to identify potential causal relationships impacting dropout rates and cardiovascular risk.
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<p><span style="color: rgb(0, 0, 0);">The INSIDE project aims to address adherence issues in Cardiac Rehabilitation, focusing on three complementary perspectives. Firstly, the project seeks to enhance predictive models for dropout rates and cardiovascular risk to improve the personalization and optimization of the patients' treatment. Secondly, INSIDE aims to develop methods for accurately discerning patient mood from physiological variables recorded via wearable devices during program participation. Finally, the project will synthesize information from the first two phases to identify potential causal relationships impacting dropout rates and cardiovascular risk.</span></p> - TED2021-130374B-C21 - Manuel Lama Penín, Juan Carlos Vidal Aguiar - Paulo Félix Lamas, Senén Barro Ameneiro, Alberto José Bugarín Diz
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