Recognizing the human attention state using cardiac pulse from the noncontact and automatic-based measurements
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User attention state recognition when interacting with a monitor or undertaking a specific task represents a crucial issue in many domains and applications, such as e-learning, driving and network video conferences. However, for the consideration of convenience and practicality in these situations, it is inescapable and necessary to develop a noncontact and automatic monitoring system to analyze, recognize and predict what kind of attention state in individuals during a task execution without delay. The elaborated technique presented here has achieved efficient cardiac pulse estimation based on the face image captured by the noncontact, automatic and webcam-based measurement method. After collecting cardiac pulse signals, various features extraction methods are presented to obtain key features from the raw data which is related to the attention state or not. The experiment result shows that it is possible to estimate humans attention state based on the technique presented here. The proposed technique may be useful for monitoring person for the purpose of health care, psychological testing, online learning or security, etc.
KeywordsHuman attention state Cardiac pulse Noncontact
The authors would like to thank anonymous reviewers for their very detailed and helpful review. This study was funded by National Natural Science Foundation of China (61502291, 61573157 and 61561024), the Cultivation Project for Outstanding Young Teachers in Higher Education Institutions of Guangdong Province (YQ2015070), the Characteristic Innovation Project in Higher Education Institutions of Guangdong Province (2015KTSCX039, 2015GXJK037), the Shantou University National Foundation Cultivation Project (NFC15005) and the Science Foundation of Jiangxi University of Science and Technology (NSFJ2015-K13).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants performed by any of the authors.
- Asteriadis S, Karpouzis K, Kollias S (2008) A neuro-fuzzy approach to user attention recognition. In: Artificial Neural Networks-ICANN 2008, pp 927–936. SpringerGoogle Scholar
- Banzhaf W, Nordin P, Keller RE, Francone FD (1998) Genetic programming: an introduction, vol 270. Morgan Kaufmann San FranciscoGoogle Scholar
- Belle A, Hargraves RH, Najarian K (2012) An automated optimal engagement and attention detection system using electrocardiogram. Comput Math Methods Med 2012. doi: 10.1155/2012/528781
- Beymer D, Flickner M (2003) Eye gaze tracking using an active stereo head. In: Computer vision and pattern recognition, 2003. Proceedings. 2003 IEEE computer society conference on, vol 2, pp II–451. IEEEGoogle Scholar
- Bousefsaf F, Maaoui C, Pruski A (2014) Remote assessment of physiological parameters by non-contact technologies to quantify and detect mental stress states. In: Control, decision and information technologies (CoDIT), 2014 International conference on, pp 719–723. IEEEGoogle Scholar
- Ferreira C (2002) Gene expression programming in problem solving. In: Soft Computing and Industry, pp 635–653. Springer, LondonGoogle Scholar
- Ferreira C, Gepsoft U (2008) What is gene expression programmingGoogle Scholar
- Gu B, Sheng VS (2016) A robust regularization path algorithm for v-support vector classificationGoogle Scholar
- Hennessey C, Noureddin B, Lawrence P (2006) A single camera eye-gaze tracking system with free head motion. In: Proceedings of the 2006 symposium on Eye tracking research & applications, pages 87–94. ACMGoogle Scholar
- Huelsbusch M, Blazek V (2002) Contactless mapping of rhythmical phenomena in tissue perfusion using PPGI. In: Medical Imaging 2002, pp 110–117. International Society for Optics and PhotonicsGoogle Scholar
- Hyvärinen A, Karhunen J, Oja E (2004) Independent component analysis, vol 46. Wiley, HobokenGoogle Scholar
- Jiang D, Zhijian W, Kang L, Cao B, Li K (2006) A new method used in gene expression programming: GRCM. J Syst Simul 18(6):1466–1468Google Scholar
- Jiang D, Wang Z, Sun H, Du Y (2010) A unified fitness calculation method for automatic modeling algorithms. In: Intelligent control and automation (WCICA), 2010 8th World congress on, pp 1569–1573. IEEEGoogle Scholar
- Lewandowska M, Rumiński J, Kocejko T, et al. (2011) Measuring pulse rate with a webcama non-contact method for evaluating cardiac activity. In: Computer science and information systems (FedCSIS), 2011 Federated conference on, pp 405–410. IEEEGoogle Scholar
- Li X, Hu B, Dong Q, Campbell W, Moore P, Peng H (2011) Eeg-based attention recognition. In: Pervasive computing and applications (ICPCA), 2011 6th International conference on, pp 196–201. IEEEGoogle Scholar
- Lindsley DB (1950) Emotions and the electroencephalogramGoogle Scholar
- Lowd D, Domingos P (2005) Naive bayes models for probability estimation. In: Proceedings of the 22nd international conference on machine learning, pp 529–536. ACMGoogle Scholar
- Monkaresi H, Hussain MS, Calvo RA (2014) Using remote heart rate measurement for affect detection. In: FLAIRS ConferenceGoogle Scholar
- Shen J, Tan H, Wang J, Wang J, Lee S (2015) A novel routing protocol providing good transmission reliability in underwater sensor networks. J Internet Technol 16(1):171–178Google Scholar
- Van Loan C (1992) Computational frameworks for the fast Fourier transform, vol 10. SIAMGoogle Scholar
- Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Computer vision and pattern recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE computer society conference on, vol 1, pp I–511. IEEEGoogle Scholar
- Wei L, Tian Y, Wang Y, Ebrahimi T, Huang T (2012) Automatic webcam-based human heart rate measurements using laplacian eigenmap. In: Computer vision–ACCV 2012, pp 281–292. SpringerGoogle Scholar
- Xia Z, Wang X, Sun X, Liu Q, Xiong N (2014a) Steganalysis of LSB matching using differences between nonadjacent pixels. Multimed Tools Appl 75(4):1974–1962Google Scholar
- Xia Z, Wang X, Sun X, Wang Q (2016) A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data. IEEE Trans Parallel Distrib Syst 27(2):340–352Google Scholar