Abstract
It is well known that feeling pain is very common. If anyone does not feel the pain for any causes, then it is considered as a disease or disorder; s(he) requires immediate medical attention. Since pain is an advance informer about the disease, it is considered as a fifth vital sign of the human body. Pain is felt by an excellent mechanism of the human body, and this mechanism transmits the information from the location of tissue damage to the cortex of the brain for further response. In pain management, the priority always goes to control the pain than to cure the disease. Pain measurement is a tool which helps the physicians to control the pain by prescribing the right dosage of pain killers. The dosage of pain killers which are prescribed to alleviate the pain is decided based on the patient’s subjective responses. It is hard to hide the fact that the pain killers leave their side effects on the patient while controlling the pain. So, the pain is still one of the most challenging problems in clinical practices. It is essential to adopt a method to measure the pain to control it. There are two methods to measure pain: subjective method and objective method. In the present scenario, almost all physicians use any of the subjective methods. This method is totally dependent on patients’ external responses which are not reliable; the prescribed dosage of pain killer could also not be an accurate one. Hence, it is necessary to propose an alternate method which could overcome the challenges posed by pain killers in the name of side effects. This chapter presents a few experimental attempts made to propose an objective method which is reliable and hence could be used to prescribe the correct dosage of pain killer to the patient.
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
Morone, N. E., & Weiner, D. K. (2013, November). Pain as the 5th vital sign: Exposing the vital need for pain education. Clinical Therapeutics, 35(11), 1728–1732. https://doi.org/10.1016/j.clinthera.2013.10.001.
Cohen, L. L., Lemanek, K., Blount, R. L., Dahlquist, L. M., Lim, C. S., Palermo, T. M., et al. (2008) Evidence-based assessment of pediatric pain. Journal of Pediatric Psychology, 33(9), 939–955. https://doi.org/10.1093/jpepsy/jsm103.
Merskey, H., & Bogduk, N. (2002). Classification of chronic pain descriptions of chronic pain syndromes and definitions of pain terms (2nd ed.). IASP PRESS SEATTLE.
Ikeda, K. (1995). Quantitative evaluation of pain by analyzing non-invasively obtained physiological data with particular reference to joint healing with continuous passive motion. In Proceeding RC IEEE-EMBS. https://doi.org/10.1109/RCEMBS.1995.532959.
Granovsky, Y., Granot, M., Nir, R.-R., & Yarnitsky, D. (2008). Objective correlate of subjective pain perception by contact heat-evoked potentials. The Journal of Pain, 9(1), 53–63.
Rissacher, D., Dowman, R., & Schuckers, S. A. C. (2007). Identifying frequency—domain features for an EEG-based pain measurement system. In Bioengineering Conference, NEBC, IEEE 33rd Annual Northeast. https://doi.org/10.1109/NEBC.2007.4413305.
Li, D., Puntillo, K., & Miaskowski, C. (2008, January). A review of objective pain measures for use with critical care adult patients unable to self-report. Journal of Pain, 9(1), 2–10. Epub 2007 Nov 5.
Mobascher, A., Brinkmeyer, J., Warbrick, T., Musso, F., Schlemper, V., & Wittsack, H. (2010). Brain activation patterns underlying fast habituation to painful laser stimuli. International Journal of Psychophysiology, 75, 16–24. https://doi.org/10.1016/j.ijpsycho.2009.10.008.
Schasfoort, F. C., Formanoy, M. A., Bussmann, J. B., Peters, J. W., Tibboel, D., & Stam, H. J. (2008, July). Objective and continuous measurement of peripheral motor indicators of pain in hospitalized infants: A feasibility study. Pain, 15, 137(2), 323–331.
First objective measure of pain discovered in brain scan patterns by CU-Boulder study. Available from: https://www.colorado.edu/today/2013/04/10/first-objective-measure-pain-discovered-brain-scan-patterns-cu-boulder-study. January 28, 2015.
Brauer, F., Dick, B. D., Stroink, G., Connolly, J. F, McGrath, P. J., & Finley, G. A. (2000). KLT analysis of brain potential maps during pain. In Proceedings of the 22nd Annual International Conference of the IEEE. Engineering in Medicine and Biology Society.
PainImaging. Available from: https://www.liverpool.ac.uk/pain-research-institute/our-research/pain-imaging/. September 23, 2016.
Pande, A. C., Pyke, R. E., Greiner, M., Cooper, S. A., Benjamin, R., & Pierce, M.W. (1996, February). Analgesic efficacy of the kappa-receptor agonist, enadoline, in dental surgery pain. Clinical Neuropharmacology, 19(1), 92–97.
Shankar, K., Manivannan, M., & Frenandez, P. (2006, January). GSR analysis of hypnotic analgesia. International Journal of Systemics, Cybernetics and Infomatics, ISBN 0973-4864.
Turk, D. C., & Melzack, R. (2011). The hand book of pain assessment. New York: The Guilford Press.
Rudolph, H., Packer, J. S., Cade, J. F., Lee, B., & Morley, P. (1999, March). Pain relief using smart technology: An overview of a new patient—Controlled analgesia device. IEEE Transaction on Information Technology in Biomedicine, 3(1), 20–27.
Brown, J. E., Chatterjee, N., Younger, J., & Mackey, S. (2011). Towards a physiology-based measure of pain: Patterns of human brain activity distinguish painful from non-painful thermal stimulation. PLoS ONE, 6(9), e24124. https://doi.org/10.1371/journal.pone.0024124.
Definition of Objective Measurement. Available from: https://www.rasch.org/define.htm. May 21, 2016.
Strigo, I. A., Carli, F., & Catherine Bushnell, M. (2000). Effect of ambient temperature on human pain and temperature perception. Anesthesiology, 92, 699–707.
Ayurvedic Treatment of Arthritis (Painful Joints). Available from. https://www.boloji.com/index.cfm?md=Content&sd=Articles&ArticleID=1185. May 21, 2016.
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 chapter
Cite this chapter
Shankar, K., Abudhahir, A. (2021). Realization of Objectivity in Pain: An Empirical Approach. In: Patgiri, R., Biswas, A., Roy, P. (eds) Health Informatics: A Computational Perspective in Healthcare. Studies in Computational Intelligence, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-15-9735-0_11
Download citation
DOI: https://doi.org/10.1007/978-981-15-9735-0_11
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9734-3
Online ISBN: 978-981-15-9735-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)