Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics
This paper presents a study related to human psychophysiological activity estimation based on a smartphone camera and sensors. In recent years, awareness of the human body, as well as human mental states, has become more and more popular. Yoga and meditation practices have moved from the east to Eur...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-07-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/12/7/111 |
| _version_ | 1797563511732174848 |
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| author | Alexey Kashevnik Mikhail Kruglov Igor Lashkov Nikolay Teslya Polina Mikhailova Evgeny Ripachev Vladislav Malutin Nikita Saveliev Igor Ryabchikov |
| author_facet | Alexey Kashevnik Mikhail Kruglov Igor Lashkov Nikolay Teslya Polina Mikhailova Evgeny Ripachev Vladislav Malutin Nikita Saveliev Igor Ryabchikov |
| author_sort | Alexey Kashevnik |
| collection | DOAJ |
| description | This paper presents a study related to human psychophysiological activity estimation based on a smartphone camera and sensors. In recent years, awareness of the human body, as well as human mental states, has become more and more popular. Yoga and meditation practices have moved from the east to Europe, the USA, Russia, and other countries, and there are a lot of people who are interested in them. However, recently, people have tried the practice but would prefer an objective assessment. We propose to apply the modern methods of computer vision, pattern recognition, competence management, and dynamic motivation to estimate the quality of the meditation process and provide the users with objective information about their practice. We propose an approach that covers the possibility of recognizing pictures of humans from a smartphone and utilizes wearable electronics to measure the user’s heart rate and motions. We propose a model that allows building meditation estimation scores based on these parameters. Moreover, we propose a meditation expert network through which users can find the coach that is most appropriate for him/her. Finally, we propose the dynamic motivation model, which encourages people to perform the practice every day. |
| first_indexed | 2024-03-10T18:44:41Z |
| format | Article |
| id | doaj.art-986d71c24a744b6ca1cb2c18f8468c40 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-10T18:44:41Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-986d71c24a744b6ca1cb2c18f8468c402023-11-20T05:36:45ZengMDPI AGFuture Internet1999-59032020-07-0112711110.3390/fi12070111Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable ElectronicsAlexey Kashevnik0Mikhail Kruglov1Igor Lashkov2Nikolay Teslya3Polina Mikhailova4Evgeny Ripachev5Vladislav Malutin6Nikita Saveliev7Igor Ryabchikov8Computer Aided Integrated Systems Laboratory, SPIIRAS, St. Petersburg 199178, RussiaInformation Technology and Programming Faculty, ITMO University, St. Petersburg 197101, RussiaComputer Aided Integrated Systems Laboratory, SPIIRAS, St. Petersburg 199178, RussiaComputer Aided Integrated Systems Laboratory, SPIIRAS, St. Petersburg 199178, RussiaInformation Technology and Programming Faculty, ITMO University, St. Petersburg 197101, RussiaInformation Technology and Programming Faculty, ITMO University, St. Petersburg 197101, RussiaInformation Technology and Programming Faculty, ITMO University, St. Petersburg 197101, RussiaInformation Technology and Programming Faculty, ITMO University, St. Petersburg 197101, RussiaInformation Technology and Programming Faculty, ITMO University, St. Petersburg 197101, RussiaThis paper presents a study related to human psychophysiological activity estimation based on a smartphone camera and sensors. In recent years, awareness of the human body, as well as human mental states, has become more and more popular. Yoga and meditation practices have moved from the east to Europe, the USA, Russia, and other countries, and there are a lot of people who are interested in them. However, recently, people have tried the practice but would prefer an objective assessment. We propose to apply the modern methods of computer vision, pattern recognition, competence management, and dynamic motivation to estimate the quality of the meditation process and provide the users with objective information about their practice. We propose an approach that covers the possibility of recognizing pictures of humans from a smartphone and utilizes wearable electronics to measure the user’s heart rate and motions. We propose a model that allows building meditation estimation scores based on these parameters. Moreover, we propose a meditation expert network through which users can find the coach that is most appropriate for him/her. Finally, we propose the dynamic motivation model, which encourages people to perform the practice every day.https://www.mdpi.com/1999-5903/12/7/111meditation estimationneural networkshuman behavior patterns |
| spellingShingle | Alexey Kashevnik Mikhail Kruglov Igor Lashkov Nikolay Teslya Polina Mikhailova Evgeny Ripachev Vladislav Malutin Nikita Saveliev Igor Ryabchikov Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics Future Internet meditation estimation neural networks human behavior patterns |
| title | Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics |
| title_full | Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics |
| title_fullStr | Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics |
| title_full_unstemmed | Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics |
| title_short | Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics |
| title_sort | human psychophysiological activity estimation based on smartphone camera and wearable electronics |
| topic | meditation estimation neural networks human behavior patterns |
| url | https://www.mdpi.com/1999-5903/12/7/111 |
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