A4 Artikkeli konferenssijulkaisussa
Emotions and Activity Recognition System Using Wearable Device Sensors (2021)

Rumiantcev, M. (2021). Emotions and Activity Recognition System Using Wearable Device Sensors. In S. Balandin, V. Deart, & T. Tyutina (Eds.), FRUCT '28 : Proceedings of the 28th Conference of Open Innovations Association FRUCT (pp. 381-389). FRUCT Oy. Proceedings of Conference of Open Innovations Association FRUCT. https://doi.org/10.23919/FRUCT50888.2021.9347652

JYU-tekijät tai -toimittajat

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Rumiantcev, Mikhail

Emojulkaisu: FRUCT '28 : Proceedings of the 28th Conference of Open Innovations Association FRUCT

Emojulkaisun toimittajat: Balandin, Sergey; Deart, Vladimir; Tyutina, Tatiana

Konferenssin paikka ja aika: Moscow, Russia, 25.-29.1.2021

eISBN: 978-952-69244-4-1

Lehti tai sarja: Proceedings of Conference of Open Innovations Association FRUCT

ISSN: 2305-7254

eISSN: 2343-0737

Julkaisuvuosi: 2021

Artikkelin sivunumerot: 381-389

Kustantaja: FRUCT Oy

Julkaisumaa: Suomi

Julkaisun kieli: englanti

DOI: https://doi.org/10.23919/FRUCT50888.2021.9347652

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Kokonaan avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/74291

Tiivistelmä

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.

YSO-asiasanat: älytekniikka; älytuotteet; tekoäly; koneoppiminen; paikkatiedot; liikkeentunnistus; kasvontunnistus (tietotekniikka); anturit; fyysinen aktiivisuus; toiminta; mieliala; tunteet

Vapaat asiasanat: deep learning; image segmentation; zero-shot semantic segmentation

Liittyvät organisaatiot

OKM-raportointi: Kyllä

Raportointivuosi: 2021

JUFO-taso: 1