Search results for "Feature fusion"

showing 2 items of 2 documents

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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Cross-Subject Emotion Recognition Using Fused Entropy Features of EEG.

2022

Emotion recognition based on electroencephalography (EEG) has attracted high interest in fields such as health care, user experience evaluation, and human–computer interaction (HCI), as it plays an important role in human daily life. Although various approaches have been proposed to detect emotion states in previous studies, there is still a need to further study the dynamic changes of EEG in different emotions to detect emotion states accurately. Entropy-based features have been proved to be effective in mining the complexity information in EEG in many areas. However, different entropy features vary in revealing the implicit information of EEG. To improve system reliability, in this paper,…

ihmisen ja tietokoneen vuorovaikutusGeneral Physics and AstronomyneuroverkotentropiamittausmenetelmätMSEBiLSTMtunteetemotion recognitionfeature fusionemotion recognition; EEG; feature fusion; MSE; BiLSTMEEGaivotfysiologiset vaikutuksetEntropy (Basel, Switzerland)
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