Abstract
Technology is advancing at an unprecedented rate with developments in almost every gadget, particularly smartphones. This project aims at using smartphones to measure some of the most important vitals of the human body—heart rate, breathing rate, blood pressure, oxygen level in blood and heart rate variability. In this approach, a person places his or her right and left finger tips on the smartphone camera lens to record 10-s video signals, which are then analyzed to measure the parameters. Thus, no external equipment like sensors and electrodes are required. The performance has been evaluated on 50 subjects with different age groups. Experimental results show that the heart rate and blood pressure can be estimated effectively using this approach with an average error rate of 2.5% and 2.3% respectively.
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
Similar content being viewed by others
References
Fusco, A., Locatelli, D., Onorati, F., Durelli, G.C., Santambrogio, M.D.: On how to extract breathing rate from PPG signal using wearable devices. In: IEEE Biomedical Circuits and Systems Conference (2015)
Yang, D., Zhu, J., Zhu, P.: SpO2 and heart rate measurement with wearable watch based on PPG. In: IET International Conference on Biomedical Image and Signal Processing (2015)
Czerwinski, D., Wojcicki, P., Zientarski, T.: On time blood pressure prediction with the use of PPG signals. In: International Conference on Electromagnetic Devices and Processes in Environment Protection with Seminar Applications of Superconductors (2017)
Daimiwal, N., Sundhararajan, M., Shriram, R.: Respiratory rate, heart rate and continuous measurement of BP using PPG. In: International Conference on Communication and Signal Processing (2014)
Benlamri, R., Docksteader, L.: MORF: A mobile health-monitoring platform. IT Professional 12(3), 18–25 (2010)
Maia, P., Batista, T., Cavalcante, E., Baffa, A., Delicato, F.C., Pires, P.F., Zomaya, A.: A web platform for interconnecting body sensors and improving health care. Procedia Comput. Sci 40, 135–142 (2014)
Agarwal, S., Lau, C.T.: Remote health monitoring using mobile phones and web services: Telemed E Health 16(5), 603–607 (2010)
Paliwal, S., Lakshmi, C.V., Patvardhan, C.: Real time heart rate detection and heart rate variability calculation. In: IEEE Region 10 Humanitarian Technology Conference (2016)
Chandrasekaran, V.: Measuring vital signs using smart phones. Denton, Texas (2013)
Lagido, R.B., Lobo, J., Leite, S., Sousa, C., Ferreira, L., Cardoso, J.S.: Using the smartphone camera to monitor heart rate and rhythm in heart failure patients. In: IEEE-EMBS International Conference on Biomedical and Health Informatics (2014)
Devaki, V., Jayanthi, T.: Pulse rate measurement using android smartphone. In: International Conference on Wireless Communications Signal Processing and Networking (2019)
Rajani, L.V., Padma Sai, Y., Balaji, N.: Arduino based abnormal heart rate detection and wireless communication. Int. J. Cybern. Inf. 5(4), 47–53 (2016)
Koç, K.O., Polat, K.: MATLAB GUI design for heart rate monitoring using smart phone Camera. In: Medical Technologies National Congress (2017)
Peng, R.C., Zhou, X., Lin, W.H., Zhang, Y.T.: Extraction of heart rate variability from smartphone photoplethysmograms. Comput. Math. Meth. Med. 1–11 (2015)
Shah, S.A.: Vital Sign Monitoring and Data Fusion for Paediatric Triage. PhD Thesis, University of Oxford (2012)
Ding, X., Nassehi, D., Larson, E.C.: Measuring oxygen saturation with smartphone cameras using convolutional neural networks. IEEE J. Biomed. Health Inf. 23(6) (2019)
Kanva, A.K., Sharma, C.J., Deb, S.: Determination of SpO2 and heart-rate using smartphone camera. In: International Conference on Control, Instrumentation, Energy and Communication (2014)
Lazazzera, R., Belhaj, Y., Carrault, G.: A new wearable device for blood pressure estimation using photoplethysmogram. Sensors 19(11), 2557 (2019)
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
Sree Dhruti, P.S.S., Rajani Kumari, L.V., Padma Sai, Y. (2021). An Inference Engine Integrated with Health Parameters for Medical Web Platform. In: Udgata, S.K., Sethi, S., Srirama, S.N. (eds) Intelligent Systems. Lecture Notes in Networks and Systems, vol 185. Springer, Singapore. https://doi.org/10.1007/978-981-33-6081-5_33
Download citation
DOI: https://doi.org/10.1007/978-981-33-6081-5_33
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-33-6080-8
Online ISBN: 978-981-33-6081-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)