Abstract
The paper has been designed for heartbeat rate classification while watching movies and sending movie ratings using Telegram Bot. The heartbeat of a movie viewer can increase abruptly at any point in the movie, which can harm the health of the person adversely with serious problems like cardiac arrest. To record heart activity in terms of heartbeat rate electrocardiogram is used. The Electrocardiogram is the technique to capture heart-signal provoked by the electric field and captured by a sensor. In this paper, the heartbeat rate is measured while watching a movie and is getting classified using Backpropagation Neural Network, that whether watching the movie will result in a slow, normal, or fast heartbeat rate. Observations are collected and analyzed and from next time when a person starts watching that movie, an alert message is sent using Telegram to notify the type of a movie. So from next time, before watching that movie, a person can get alert about the type of that particular movie based on the previous ratings and can watch or avoid watching the movie based on their discretion as it may affect their heart. The system is designed for weak-hearted, teenagers and be used as a parental guide.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
M. Nardelli, G. Valenza, A.Greco, A. Lanatá, E.P. Scilingo, R. Bailón, Quantifying the lagged Poincaré plot geometry of ultrashort heart rate variability series: automatic recognition of odor hedonic tone. Med. Biol. Eng. Comput. 1–14
M.S. Hassan, M.N. Osman, Z.S. Azarian, Effects of watching violence movies on the attitudes concerning aggression among middle schoolboys (13–17 years old) at international schools in Kuala Lumpur, Malaysia. Eur. J. Sci. Res. 38(1), 141–156 (2009)
M.H. Itoo, K. Nagar, Impact of negative portrayal of a destination in bollywood movies on viewers’ attitude towards the destination, intention to visit and destination image. Pac. Bus. Rev. Int. 10(5), 71–82 (2017)
M.I. Qadir, M. Asif, Does normal pulse rate correlate with watching horror movies. J. Cardiol. Curr. Res. 12(2), 67–68 (2019)
J.M. Arnold, D.H. Fitchett, J.G. Howlett, E.M. Lonn, J.C. Tardif, Resting heart rate: a modifiable prognostic indicator of cardiovascular risk and outcomes? Can. J. Cardiol. 24, 3A–15A (2008)
World Health Organization, Avoiding heart attacks and strokes: don’t be a victim, in Avoiding Heart Attacks and Strokes: Don’t be a Victim, 2005 (pp. 44–44)
N. Iyengar, C.K. Peng, R. Morin, A.L. Goldberger, L.A. Lipsitz, Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics. Am. J. Physiol. Regul. Integr. Comp. Physiol. 271(4), R1078–R1084 (1996)
A.L. Goldberger, L.A.N. Amaral, L. Glass, J.M. Hausdorff, P.C. Ivanov, R.G. Mark, J.E. Mietus, G.B. Moody, C.K. Peng, H.E. Stanley, PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23):e215-e220 (2003)
S. Nayak, S. Sahoo, B. Champaty, K. Pal, Effect of horror clips on the physiology of ANS & heart using ECG signal classification. in 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT) (IEEE, 2014), pp. 480–485
H.H. Tsai, C.W. Yi, Wearable ECG for tension assessment in movie watching and adventure riding, in 2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN) (IEEE, 2017), pp. 23–30
Y.L. Hsu, J.S. Wang, W.C. Chiang, C.H. Hung, Automatic ecg-based emotion recognition in music listening. IEEE Transactions on Affective Computing (2017)
S.K. Pandey, R.R. Janghel, Automatic detection of arrhythmia from imbalanced ECG database using CNN model with SMOTE. Australas. Phys. Eng. Sci. Med. 42(4), 1129–1139 (2019)
M. Al-Emran, S.I. Malik, M.N. Al-Kabi, A survey of internet of things (IoT) in education: opportunities and challenges, in Toward Social Internet of Things (SIoT): Enabling Technologies, Architectures and Applications (Springer, Cham, 2020), pp. 197–209
T. Srivastava, S. Singh, Impact of internet of things on societal applications, in Intelligent Communication, Control and Devices (Springer, Singapore, 2020), pp. 579–587
J.J. Kang, Systematic analysis of security implementation for internet of health things in mobile health networks, in Data Science in Cybersecurity and Cyberthreat Intelligence (Springer, Cham, 2020), pp. 87–113
F. Firouzi, B. Farahani, M. Weinberger, G. DePace, F.S. Aliee, IoT fundamentals: definitions, architectures, challenges, and promises, in Intelligent Internet of Things (Springer, Cham, 2020), pp. 3–50
C.S. Kolli, C.K. Reddy, M. Kavitha, A critical review on internet of things to empower the living style of physically challenged people, in Emerging Research in Data Engineering Systems and Computer Communications (Springer, Singapore, 2020), pp. 603–614
S. Alam, S.T. Siddiqui, A. Ahmad, R. Ahmad, M. Shuaib, Internet of things (IoT) enabling technologies, requirements, and security challenges, in Advances in Data and Information Sciences (Springer, Singapore, 2020), pp. 119–126
V. Saranya, M.C.M. Belinda, G.R. Kanagachidambaresan, An evolution of innovations protocols and recent technology in industrial IoT, in Internet of Things for Industry 4.0 (Springer, Cham, 2020), pp. 161–175
M.A. Al-Garadi, A. Mohamed, A. Al-Ali, X. Du, I. Ali, M. Guizani, M., A survey of machine and deep learning methods for internet of things (IoT) security. IEEE Commun. Surv. Tutorials (2020)
A. Jalilvand, M. Neshati, Channel retrieval: finding relevant broadcasters on telegram. Soc. Netw. Anal. Min. 10, 1–16 (2020)
Acknowledgements
We gratefully acknowledge the Maulana Abul Kalam Azad University of Technology, West Bengal, which has allowed us to do this wonderful project and also thanks to “physionet”, an open-source website for sharing ECG based movie’s dataset.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Das, S., Bhattacharya, A. (2021). ECG Assess Heartbeat rate, Classifying using BPNN while Watching Movie and send Movie Rating through Telegram. In: Tavares, J.M.R.S., Chakrabarti, S., Bhattacharya, A., Ghatak, S. (eds) Emerging Technologies in Data Mining and Information Security. Lecture Notes in Networks and Systems, vol 164. Springer, Singapore. https://doi.org/10.1007/978-981-15-9774-9_43
Download citation
DOI: https://doi.org/10.1007/978-981-15-9774-9_43
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9773-2
Online ISBN: 978-981-15-9774-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)