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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Gils, Mark Van
in Cooperation with on an Cooperation-Score of 37%
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Publications (4/4 displayed)
- 2020Data-driven precision medicine
- 2018Data-driven precision medicine ecosystem - stakeholder needs and opportunities
- 2013Biosignal processing methods to guide cardiac patients to perform safe and beneficial exercise for rehabilitation
- 2012Biosignal processing methods to guide cardiac patients to perform safe and beneficial exercise for rehabilitation
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document
Biosignal processing methods to guide cardiac patients to perform safe and beneficial exercise for rehabilitation
Abstract
This paper describes biosignal interpretation methods inan application to support a CAD (Coronary Artery Disease)patient during rehabilitation. The methods usephysiological signals from a wearable device (embedded ina shirt) to guide the patient through safe and beneficialexercise. The paper describes the different designconsiderations of the processing chain: signal qualityverification; on-line analysis and feedback; recoveryanalysis and exercise summary analysis. The systemcomponents have been validated: differences in heart ratebetween the device and the reference were small, ECGsignal quality estimation algorithm had high sensitivityand specificity, and the on-line feedback algorithmsperform well enough for use during exercise in practice.A study regarding the clinical usefulness of the overallsystem is carried in 2012 in the context of the EUproject Heartcycle