Abstract
Remotely detecting the physiological state of humans is becoming increasingly important for rehabilitative robotics (RR) and socially assistive robotics (SAR) because it makes robots better-suited to work more closely and more cooperatively with humans. This research delivers a new non-contact technique for detecting heart rate in real time using a high precision, single-point infrared sensor. The proposed approach is an important potential improvement over existing methods because it collects heart rate information unencumbered by biofeedback sensors, complex computational processing or high cost equipment. We use a thermal infrared sensor to capture subtle changes in the sub-nasal skin surface temperature to monitor cardiac pulse. This study extends our previous research in which breathing rate is automatically extracted using the same hardware. Experiments conducted to test the proposed system accuracy show that in 72.7% of typical cases heart rate was successfully detected within 0-9 beats per minute as measured by root-mean-square error.
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
Preview
Unable to display preview. Download preview PDF.
References
Krebs, H.I., Hogan, N.: Therapeutic robotics a technology push. Proceedings of the IEEE 94(9), 1727–1738 (2006)
Montagu, J.D., Coles, E.M.: Mechanism and measurement of the galvanic skin response. Psychological Bulletin 65(5), 261–279 (1966)
Tyson, P.D.: Task-related stress and EEG alpha biofeedback. Biofeedback and Self-Regulation 12(2), 105–119 (1987)
Boccanfuso, L., O’Kane, J.M.: Remote measurement of breathing rate in real time using a high precision, single-point infrared temperature sensor. In: Proceedings IEEE International Conference on Biomedical Robotics and Biomechatronics (2012)
Matsukawa, T., Yokoyama, K.: Visualizing physiological information based on 3dcg. FORMA 25, 11–14 (2010)
Barreto, A., Zhai, J., Adjouadi, M.: Non-intrusive Physiological Monitoring for Automated Stress Detection in Human-Computer Interaction. In: Lew, M., Sebe, N., Huang, T.S., Bakker, E.M. (eds.) HCI 2007. LNCS, vol. 4796, pp. 29–38. Springer, Heidelberg (2007)
Kakadiaris, I.A., Passalis, G., Theoharis, T., Toderici, G., Konstantinidis, I., Murtuza, N.: Multimodal face recognition: Combination of geometry with physiological information. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1022–1029 (2005)
Poh, M.Z., McDuff, D.J., Picard, R.W.: Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Transactions on Biomedical Engineering 58(1), 7–11 (2011)
Suzuki, S., Matsui, T., Gotoh, S., Mori, Y., Takase, B., Ishihara, M.: Development of non-contact monitoring system of heart rate variability (hrv) - an approach of remote sensing for ubiquitous technology. In: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International, pp. 195–203 (2009)
Kulic, D., Croft, E.: Estimating robot induced affective state using hidden markov models. In: The IEEE International Symposium on Robot and Human Interactive Communication (ROMAN), pp. 257–262 (September 2006)
Kulic, D., Croft, E.: Physiological and subjective responses to articulated robot motion. Robotica 25(1), 13–27 (2007)
Rani, P., Sims, J., Brackin, R., Sarkar, N.: Online stress detection using psychophysiological signals for implicit human-robot cooperation. Robotica 20(6), 673–685 (2002)
McLaughlin, L.: Engineering meets emotion: New robots sense human distress. IEEE Intelligent Systems 18, 4–7 (2003)
Liu, C., Rani, P., Sarkar, N.: Affective state recognition and adaptation in human-robot interaction: A design approach. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3099–3106 (2006)
Rohrbaugh, J.W., Sirevaag, E.J., Singla, N., O’Sullivan, J., Chen, M.: Laser doppler vibrometry measures of physiological function: evaluation of biometric capabilities. IEEE Transactions on Information Forensics and Security 5, 449–460 (2010)
A mini-robot with a long standoff capability to detect motion and breathing inside a compound (September 2011), http://www.ereleases.com/pr/author/tialinx-inc (accessed January 2012)
Sekine, M., Maeno, K.: Non-contact heart rate detection using periodic variation in doppler frequency. In: Proceedings of the IEEE, Sensors Applications Symposium (SAS), pp. 318–322 (February 2011)
Lohman, B., Boric-Lubecke, O., Lubecke, V.M., Ong, P.W., Sondhi, M.M.: A digital signal processor for doppler radar sensing of vital signs. IEEE Engineering in Medicine and Biology Magazine 21(5), 161–164 (2002)
Singh, A., Lubecke, V.M.: Respiratory monitoring and clutter rejection using a cw doppler radar with passive rf tags. IEEE Sensors Journal 12(3), 558–565 (2012)
McSharry, P.E., Clifford, G.D., Tarassenko, L., Smith, L.A.: A dynamical model for generating synthetic electrocardiogram signals. IEEE Transactions on Biomedical Engineering 50(3), 289–294 (2003)
Burrus, C.S., Gopinath, R.A., Guo, H.: Introduction to Wavelets and Wavelet Transforms: A Primer. Prentice-Hall (1997)
Daubechies, I.: Ten lectures on wavelets. Society for Industrial and Applied Mathematics, Philadelphia (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Boccanfuso, L., Perez, E.J., Robinson, M., O’Kane, J.M. (2012). Collecting Heart Rate Using a High Precision, Non-contact, Single-Point Infrared Temperature Sensor. In: Ge, S.S., Khatib, O., Cabibihan, JJ., Simmons, R., Williams, MA. (eds) Social Robotics. ICSR 2012. Lecture Notes in Computer Science(), vol 7621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34103-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-34103-8_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34102-1
Online ISBN: 978-3-642-34103-8
eBook Packages: Computer ScienceComputer Science (R0)