Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study
To equip computers with human communication skills and to enable natural interaction between the computer and a human, intelligent solutions are required based on artificial intelligence (AI) methods, algorithms, and sensor technology. This study aimed at identifying and analyzing the state-of-the-a...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/1/20 |
| _version_ | 1827667702444982272 |
|---|---|
| author | Boštjan Šumak Saša Brdnik Maja Pušnik |
| author_facet | Boštjan Šumak Saša Brdnik Maja Pušnik |
| author_sort | Boštjan Šumak |
| collection | DOAJ |
| description | To equip computers with human communication skills and to enable natural interaction between the computer and a human, intelligent solutions are required based on artificial intelligence (AI) methods, algorithms, and sensor technology. This study aimed at identifying and analyzing the state-of-the-art AI methods and algorithms and sensors technology in existing human–computer intelligent interaction (HCII) research to explore trends in HCII research, categorize existing evidence, and identify potential directions for future research. We conduct a systematic mapping study of the HCII body of research. Four hundred fifty-four studies published in various journals and conferences between 2010 and 2021 were identified and analyzed. Studies in the HCII and IUI fields have primarily been focused on intelligent recognition of emotion, gestures, and facial expressions using sensors technology, such as the camera, EEG, Kinect, wearable sensors, eye tracker, gyroscope, and others. Researchers most often apply deep-learning and instance-based AI methods and algorithms. The support sector machine (SVM) is the most widely used algorithm for various kinds of recognition, primarily an emotion, facial expression, and gesture. The convolutional neural network (CNN) is the often-used deep-learning algorithm for emotion recognition, facial recognition, and gesture recognition solutions. |
| first_indexed | 2024-03-10T03:22:57Z |
| format | Article |
| id | doaj.art-42891d9213c84f28ab9cb63975b07a17 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:22:57Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-42891d9213c84f28ab9cb63975b07a172023-11-23T12:15:38ZengMDPI AGSensors1424-82202021-12-012212010.3390/s22010020Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping StudyBoštjan Šumak0Saša Brdnik1Maja Pušnik2Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, SloveniaFaculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, SloveniaFaculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, SloveniaTo equip computers with human communication skills and to enable natural interaction between the computer and a human, intelligent solutions are required based on artificial intelligence (AI) methods, algorithms, and sensor technology. This study aimed at identifying and analyzing the state-of-the-art AI methods and algorithms and sensors technology in existing human–computer intelligent interaction (HCII) research to explore trends in HCII research, categorize existing evidence, and identify potential directions for future research. We conduct a systematic mapping study of the HCII body of research. Four hundred fifty-four studies published in various journals and conferences between 2010 and 2021 were identified and analyzed. Studies in the HCII and IUI fields have primarily been focused on intelligent recognition of emotion, gestures, and facial expressions using sensors technology, such as the camera, EEG, Kinect, wearable sensors, eye tracker, gyroscope, and others. Researchers most often apply deep-learning and instance-based AI methods and algorithms. The support sector machine (SVM) is the most widely used algorithm for various kinds of recognition, primarily an emotion, facial expression, and gesture. The convolutional neural network (CNN) is the often-used deep-learning algorithm for emotion recognition, facial recognition, and gesture recognition solutions.https://www.mdpi.com/1424-8220/22/1/20human–computer intelligent interactionintelligent user interfacesIUIsensorsartificial intelligence |
| spellingShingle | Boštjan Šumak Saša Brdnik Maja Pušnik Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study Sensors human–computer intelligent interaction intelligent user interfaces IUI sensors artificial intelligence |
| title | Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study |
| title_full | Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study |
| title_fullStr | Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study |
| title_full_unstemmed | Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study |
| title_short | Sensors and Artificial Intelligence Methods and Algorithms for Human–Computer Intelligent Interaction: A Systematic Mapping Study |
| title_sort | sensors and artificial intelligence methods and algorithms for human computer intelligent interaction a systematic mapping study |
| topic | human–computer intelligent interaction intelligent user interfaces IUI sensors artificial intelligence |
| url | https://www.mdpi.com/1424-8220/22/1/20 |
| work_keys_str_mv | AT bostjansumak sensorsandartificialintelligencemethodsandalgorithmsforhumancomputerintelligentinteractionasystematicmappingstudy AT sasabrdnik sensorsandartificialintelligencemethodsandalgorithmsforhumancomputerintelligentinteractionasystematicmappingstudy AT majapusnik sensorsandartificialintelligencemethodsandalgorithmsforhumancomputerintelligentinteractionasystematicmappingstudy |