Search results for "Computació centrada en humans"

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A Trajectory-Driven 3D Channel Model for Human Activity Recognition

2021

This paper concerns the design, analysis, and simulation of a 3D non-stationary channel model fed with inertial measurement unit (IMU) data. The work in this paper provides a framework for simulating the micro-Doppler signatures of indoor channels for human activity recognition by using radiofrequency-based sensing technologies. The major human body segments, such as wrists, ankles, torso, and head, are modelled as a cluster of moving point scatterers. We provide expressions for the time variant (TV) speed and TV angles of motion based on 3D trajectories of the moving person. Moreover, we present mathematical expressions for the TV Doppler shifts and TV path gains associated with each movin…

Channel transfer functionGeneral Computer ScienceComputer scienceInternet of ThingsComputació centrada en humansDoppler EfecteActivity recognitionsymbols.namesakespectrogramInertial measurement unitVDP::Teknologi: 500::Medisinsk teknologi: 620Channel measurementsnon-stationary fading channelsmedicineGeneral Materials ScienceComputer visionNon-stationary fading channelsReconeixement de formes (Informàtica)channel state informationSpectrogrambusiness.industryWireless sensingGeneral Engineering:Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes [Àrees temàtiques de la UPC]TorsoInertial measurement unitsExpression (mathematics)TK1-9971Time-variant Doppler power characteristicsmedicine.anatomical_structureChannel state informationHuman-centered computingchannel transfer functiontime-variant Doppler power characteristicsTrajectorysymbolsChannel state informationSpectrogramMicro-Doppler signature:Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC]Electrical engineering. Electronics. Nuclear engineeringArtificial intelligenceHuman activity recognitionbusinessDoppler effect
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WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities

2020

Robust and accurate human activity recognition (HAR) systems are essential to many human-centric services within active assisted living and healthcare facilities. Traditional HAR systems mostly leverage a single sensing modality (e.g., either wearable, vision, or radio frequency sensing) combined with machine learning techniques to recognize human activities. Such unimodal HAR systems do not cope well with real-time changes in the environment. To overcome this limitation, new HAR systems that incorporate multiple sensing modalities are needed. Multiple diverse sensors can provide more accurate and complete information resulting in better recognition of the performed activities. This article…

General Computer ScienceComputer scienceFeature extractionPrincipal component analysisComputació centrada en humansWearable computer02 engineering and technologyDoppler EfecteAccelerometerRadio frequency sensinglaw.inventionActivity recognitionlawInertial measurement unitMachine learning0202 electrical engineering electronic engineering information engineeringfeature fusionGeneral Materials ScienceComputer visionReconeixement de formes (Informàtica)VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Feature fusionModality (human–computer interaction)business.industryfeature extractionSupervised learningGeneral Engineering:Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes [Àrees temàtiques de la UPC]020206 networking & telecommunicationsGyroscopemicro-Doppler signatureDoppler effectWearable sensingmachine learningHuman-centered computingActivity recognitionFeature extractionMicro-Doppler signature020201 artificial intelligence & image processing:Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC]Artificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineeringHuman activity recognitionbusinesslcsh:TK1-9971
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