A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors
In recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to proce...
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doaj-04e5680afc95426cb52448aaee58751e2020-11-25T04:07:30ZengMDPI AGSensors1424-82202020-11-01206367636710.3390/s20216367A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone SensorsAgata Kołakowska0Wioleta Szwoch1Mariusz Szwoch2Telecommunications and Informatics, Faculty of Electronics, Gdańsk University of Technology, 80-233 Gdansk, PolandTelecommunications and Informatics, Faculty of Electronics, Gdańsk University of Technology, 80-233 Gdansk, PolandTelecommunications and Informatics, Faculty of Electronics, Gdańsk University of Technology, 80-233 Gdansk, PolandIn recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones, the variety of their built-in sensors, as well as the availability of cloud computing services have made them an environment in which the task of recognising emotions can be performed at least as effectively. This is possible and particularly important due to the fact that smartphones and other mobile devices have become the main computer devices used by most people. This article provides a systematic overview of publications from the last 10 years related to emotion recognition methods using smartphone sensors. The characteristics of the most important sensors in this respect are presented, and the methods applied to extract informative features on the basis of data read from these input channels. Then, various machine learning approaches implemented to recognise emotional states are described.https://www.mdpi.com/1424-8220/20/21/6367affective computingemotion recognitionsmartphonessensory datasensorshuman–computer interaction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Agata Kołakowska Wioleta Szwoch Mariusz Szwoch |
spellingShingle |
Agata Kołakowska Wioleta Szwoch Mariusz Szwoch A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors Sensors affective computing emotion recognition smartphones sensory data sensors human–computer interaction |
author_facet |
Agata Kołakowska Wioleta Szwoch Mariusz Szwoch |
author_sort |
Agata Kołakowska |
title |
A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors |
title_short |
A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors |
title_full |
A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors |
title_fullStr |
A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors |
title_full_unstemmed |
A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors |
title_sort |
review of emotion recognition methods based on data acquired via smartphone sensors |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-11-01 |
description |
In recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones, the variety of their built-in sensors, as well as the availability of cloud computing services have made them an environment in which the task of recognising emotions can be performed at least as effectively. This is possible and particularly important due to the fact that smartphones and other mobile devices have become the main computer devices used by most people. This article provides a systematic overview of publications from the last 10 years related to emotion recognition methods using smartphone sensors. The characteristics of the most important sensors in this respect are presented, and the methods applied to extract informative features on the basis of data read from these input channels. Then, various machine learning approaches implemented to recognise emotional states are described. |
topic |
affective computing emotion recognition smartphones sensory data sensors human–computer interaction |
url |
https://www.mdpi.com/1424-8220/20/21/6367 |
work_keys_str_mv |
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