Igor Lashkov
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Igor Lashkov has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
Alexey Kashevnik
SPIIRAS, 39, 14 Line
4 shared publications- Alexey Kashevnik
ITMO University
2 shared publications - Andrey Ronzhin
St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia
1 shared publication - Evgeny Ripachev
Information Technology and Programming Faculty, ITMO University, St. Petersburg 197101, Russia
1 shared publication - Igor Ryabchikov
Information Technology and Programming Faculty, ITMO University, 197101 St. Petersburg, Russia
1 shared publication - Mikhail Kruglov
Information Technology and Programming Faculty, ITMO University, St. Petersburg 197101, Russia
1 shared publication
Latest Publications
- 30 October 2021
- Published by Springer Nature
- p. 787-797
Human–Computer Interaction Interface for Driver Suspicious Action Analysis in Vehicle Cabin
- 30 October 2021
- Published by Springer Nature
- p. 787-797
Human–Computer Interaction Interface for Driver Suspicious Action Analysis in Vehicle Cabin
- 3 August 2021
- Published by Springer Nature
- p. 574-585
A Multimodal Approach to Psycho-Emotional State Detection of a Vehicle Driver
- 3 August 2021
- Published by Springer Nature
- p. 574-585
A Multimodal Approach to Psycho-Emotional State Detection of a Vehicle Driver
- 25 August 2020
- Published by Springer Nature
- p. 789-799
Dangerous State Detection in Vehicle Cabin Based on Audiovisual Analysis with Smartphone Sensors
- 25 August 2020
- Published by Springer Nature
- p. 789-799
Dangerous State Detection in Vehicle Cabin Based on Audiovisual Analysis with Smartphone Sensors
- Open Access
- 1 July 2020
- Published by MDPI AG in Future Internet
- Vol. 12 (7) , 111
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 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.
- 1 July 2020
- Published by MDPI AG in Future Internet
- Vol. 12 (7) , 111
Open AccessHuman 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 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.
- 24 August 2019
- Published by Springer Nature in Advances in Intelligent Systems and Computing
- p. 152-165
Smartphone-Based Intelligent Driver Assistant: Context Model and Dangerous State Recognition Scheme
- 24 August 2019
- Published by Springer Nature in Advances in Intelligent Systems and Computing
- p. 152-165
Smartphone-Based Intelligent Driver Assistant: Context Model and Dangerous State Recognition Scheme
- 30 May 2019
- Published by Prof. Marin Drinov Publishing House of BAS (Bulgarian Academy of Sciences)
- Vol. 72 (5) , 650-657
Ontology-based Personalisation for Online Driver Monitoring by Smartphone
- 30 May 2019
- Published by Prof. Marin Drinov Publishing House of BAS (Bulgarian Academy of Sciences)
- Vol. 72 (5) , 650-657
Ontology-based Personalisation for Online Driver Monitoring by Smartphone