Emotions and Activity Recognition System Using Wearable Device Sensors
| Autor: | Mikhail Rumiantcev |
|---|---|
| Přispěvatelé: | Balandin, Sergey, Deart, Vladimir, Tyutina, Tatiana |
| Rok vydání: | 2021 |
| Předmět: |
paikkatiedot
Computer science media_common.quotation_subject Wearable computer tekoäly Recommender system wearable device sensors lcsh:Telecommunication Activity recognition toiminta tunteet Human–computer interaction lcsh:TK5101-6720 emotions recognition zero-shot semantic segmentation activity recognition anturit Situational ethics image segmentation Wearable technology media_common Human intelligence business.industry mieliala deep learning liikkeentunnistus machine learning koneoppiminen älytuotteet Feeling älytekniikka Consciousness business kasvontunnistus (tietotekniikka) fyysinen aktiivisuus |
| Zdroj: | FRUCT Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 28, Iss 1, Pp 381-389 (2021) |
| DOI: | 10.23919/fruct50888.2021.9347652 |
| Popis: | 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 wearable devices involve wide-ranging sensors. In this paper, I am going to present emotion and activity recognition approaches. The experimental recognition system elaborated during this research, enriched with sensor data collection and machine learning algorithms. It is targeted to guess how users are doing and what they are feeling. Such recognition systems can find applications in different areas such as music recommendations, personal safety or healthcare domains. peerReviewed |
| Databáze: | OpenAIRE |
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