Search results for "Activity recognition"

showing 2 items of 42 documents

Identifying physical activity type in manual wheelchair users with spinal cord injury by means of accelerometers

2015

Objectives: The main objective of this study was to develop and test classification algorithms based on machine learning using accelerometers to identify the activity type performed by manual wheelchair users with spinal cord injury (SCI). Setting: The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia. Methods: A total of 20 volunteers were asked to perform 10 physical activities, lying down, body transfers, moving items, mopping, working on a computer, watching TV, arm-ergometer exercises, passive propulsion, slow propulsion and fast propulsion, while fitted with four accelerometers placed on both wrists, c…

medicine.medical_specialtySupport Vector MachinePARTICIPATIONPhysical activityComputerApplications_COMPUTERSINOTHERSYSTEMSACTIVITY RECOGNITIONMotor ActivityAccelerometerFunctional LateralityManual wheelchairTECNOLOGIA ELECTRONICAPhysical medicine and rehabilitationPEOPLEAccelerometryMedicineHumansVALIDITYSpinal cord injurySpinal Cord InjuriesAgedbusiness.industryVALUESENERGY-EXPENDITUREDiscriminant AnalysisReproducibility of ResultsPARAPLEGIAGeneral MedicineWristACTIVITY MONITORequipment and suppliesmedicine.diseasenervous system diseasesActivity monitorCross-Sectional StudiesNeurologyEnergy expenditureWheelchairsComputerSystemsOrganization_MISCELLANEOUSPhysical therapyComputingMilieux_COMPUTERSANDSOCIETYNeurology (clinical)InformationSystems_MISCELLANEOUSbusinessParaplegiahuman activities
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Emotions and Activity Recognition System Using Wearable Device Sensors

2021

Nowadays machines have become extremely smart, there are a lot of existing services that seemed to be unexpectable and futuristic decades or even a few years ago. However, artificial intelligence is still far from human intelligence, machines do not have feelings, consciousness, and intuition. How can we help machines to learn about human feelings and understand their needs better? People take their devices wherever they go, what can devices tell us about their owners? Personal preferences and needs are dependent on emotional and situational contexts. Therefore, emotional and activity aware gadgets would be more intuitive and provide more appropriate information to users. Contemporary weara…

paikkatiedotComputer sciencemedia_common.quotation_subjectWearable computertekoälyRecommender systemwearable device sensorslcsh:TelecommunicationActivity recognitiontoimintatunteetHuman–computer interactionlcsh:TK5101-6720emotions recognitionzero-shot semantic segmentationactivity recognitionanturitSituational ethicsimage segmentationWearable technologymedia_commonHuman intelligencebusiness.industrymielialadeep learningliikkeentunnistusmachine learningkoneoppiminenälytuotteetFeelingälytekniikkaConsciousnessbusinesskasvontunnistus (tietotekniikka)fyysinen aktiivisuus2021 28th Conference of Open Innovations Association (FRUCT)
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