Publication | Open Access
Feature Set Optimization for Physical Activity Recognition Using Genetic Algorithms
20
Citations
41
References
2015
Year
Unknown Venue
Physical ActivityEngineeringMachine LearningRemote Patient MonitoringPhysical ActivitiesBiometricsWearable TechnologyFeature ExtractionFeature SelectionFeature Set OptimizationKey FactorsKinesiologyData SciencePattern RecognitionPhysical ExerciseHealth SciencesAssistive TechnologyPhysical FitnessRehabilitationComputer ScienceFeature ConstructionHealth MonitoringHuman MovementActivity RecognitionPattern Recognition Application
Physical activity is recognized as one of the key factors for a healthy life due to its beneficial effects. The range of physical activities is very broad, and not all of them require the same effort to be performed nor have the same effects on health. For this reason, automatically recognizing the physical activity performed by a user (or patient) turns out to be an interesting research field, mainly because of two reasons: (1) it increases personal awareness about the activity being performed and its consequences on health, allowing to receive proper credit (e.g. social recognition) for the effort; and (2) it allows doctors to perform continuous remote patient monitoring.
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