Search results for "wearable device"

showing 2 items of 12 documents

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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Validity of three smartwatches in estimating energy expenditure during outdoor walking and running.

2022

Commercially wrist-worn devices often present inaccurate estimations of energy expenditure (EE), with large between-device differences. We aimed to assess the validity of the Apple Watch Series 6 (AW), Garmin FENIX 6 (GF) and Huawei Watch GT 2e (HW) in estimating EE during outdoor walking and running. Twenty young normal-weight Chinese adults concurrently wore three index devices randomly positioned at both wrists during walking at 6 km/h and running at 10 km/h for 2 km on a 400- meter track. As a criterion, EE was assessed by indirect calorimetry (COSMED K5). For walking, EE from AW and GF was significantly higher than that obtained by the K5 (p < 0.001 and 0.002, respectively), but…

tarkkuusPhysiologyphysical activityälykellotmonitorointikävelyjuoksuvalidation accuracywearable deviceshealth monitoringvalidointiPhysiology (medical)mittarit (mittaus)puettava teknologiafyysinen aktiivisuusenergiankulutus (aineenvaihdunta)Frontiers in physiology
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