Skip to main content

Sensor-Based Measurement of Nociceptive Pain: An Exploratory Study with Healthy Subjects

  • Conference paper
  • First Online:
Pervasive Computing Technologies for Healthcare (PH 2021)

Abstract

Valid assessment of pain is essential in daily clinical practice to enhance the quality of care for the patients and to avoid the risk of addiction to strong analgesics. The aim of this paper is to find a method for objective and quantitative evaluation of pain using multiple physiological markers. Data was obtained from healthy volunteers exposed to thermal and ischemic stimuli. Twelve subjects were recruited and their physiological data including skin conductance, heart rate, and skin temperature were collected via a wrist-worn sensor together with their self-reported pain on a visual analogue scale (VAS). Statistically significant differences (p < 0.01) were found between physiological scores obtained with the wearable sensor before and during the thermal test. Test-retest reliability of sensor-based measures was good during the thermal test with intraclass correlation coefficients ranging from 0.22 to 0.89. These results support the idea that a multi-sensor wearable device can objectively measure physiological reactions in the subjects due to experimentally induced pain, which could be used for daily clinical practice and as an endpoint in clinical studies. Nevertheless, the results indicate a need for further investigation of the method in real-life pain settings.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bhardwaj, P., Yadav, R.J.: Measuring pain in clinical trials: pain scales, endpoints, and challenges. Int. J. Clin. Exp. Physiol. 2, 151–156 (2015)

    Article  Google Scholar 

  2. Michaelides, A., Zis, P.: Depression, anxiety and acute pain: links and management challenges. Postgrad. Med. 131, 438–444 (2019)

    Article  Google Scholar 

  3. Rawal, N.: Current issues in postoperative pain management. Eur. J. Anaesthesiol. 33, 160–171 (2016)

    Article  Google Scholar 

  4. Triano, J.J., McGregor, M., Cramer, G.D., Emde, D.L.: A comparison of outcome measures for use with back pain patients: results of a feasibility study. J. Manipulative Physiol. Ther. 16, 67–73 (1993)

    Google Scholar 

  5. Lanzillotta, J.A., Clark, A., Starbuck, E., Kean, E.B., Kalarchian, M.: The impact of patient characteristics and postoperative opioid exposure on prolonged postoperative opioid use: an integrative review. Pain Manag. Nurs. 19, 535–548 (2018)

    Article  Google Scholar 

  6. Chou, R., et al.: Management of postoperative pain: a clinical practice guideline from the American pain society, the American society of regional anesthesia and pain medicine, and the American society of society of anesthesiologists’ committee on regional anesthesia, executive committee, and administrative council. J. Pain 17, 131–157 (2016)

    Article  Google Scholar 

  7. Hah, J.M., Bateman, B.T., Ratliff, J., Curtin, C., Sun, E.: Chronic opioid use after surgery: implications of perioperative management in the face of the opioid epidemic. Anesth. Analg. 125, 1733–1740 (2017)

    Article  Google Scholar 

  8. Angelini, E., Wijk, H., Brisby, H., Baranto, A.: Patients’ experiences of pain have an impact on their pain management attitudes and strategies. Pain Manag. Nurs. 19, 464–473 (2018)

    Article  Google Scholar 

  9. Taenzer, P., Melzack, R., Jeans, M.E.: Influence of psychological factors on postoperative pain, mood and analgesic requirements. Pain 24, 331–342 (1986)

    Article  Google Scholar 

  10. Empatica Homepage. https://www.empatica.com/en-eu/research/e4/. Accessed 2 Sept 2021

  11. Nabian, M., Yin, Y., Wormwood, J., Quigley, K.S., Barret, L.F., Ostadabbas, S.: An open-source feature extraction tool for the analysis of peripheral physiological data. IEEE J. Trans. Eng. Health Med. 6, 1–11 (2018)

    Article  Google Scholar 

  12. Wagemakers, S.H., van der Velden, J.M., Gerlich, A.S., Hindriks-Keegstra, A.W., van Dijk, J.F.M., Verhoeff, J.J.C.: A systematic review of devices and techniques that objectively measure patients’ pain. Pain Physician 22, 1–13 (2019)

    Article  Google Scholar 

  13. Chu, Y., Zhao, X., Han, J., Su, Y.: Physiological signal-based method for measurement of pain intensity. Front. Neurosci. 11, 279 (2017)

    Article  Google Scholar 

  14. Cowen, R., Stasiowska, M.K., Laycock, H., Bantel, C.: Assessing pain objectively: the use of physiological parameters. Anaesthesia 70, 828–847 (2015)

    Article  Google Scholar 

Download references

Acknowledgment

The study has been supported by the Swedish Agency for Innovation (VINNOVA) under the project “Controlled treatment of opiate-requiring pain using biosensors - SENSOP” in collaboration between the Multidisciplinary Pain Centre and Rehabilitation Medicine at Uppsala University Hospital, Sensidose AB, and Örebro University.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mevludin Memedi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Memedi, M. et al. (2022). Sensor-Based Measurement of Nociceptive Pain: An Exploratory Study with Healthy Subjects. In: Lewy, H., Barkan, R. (eds) Pervasive Computing Technologies for Healthcare. PH 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 431. Springer, Cham. https://doi.org/10.1007/978-3-030-99194-4_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-99194-4_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-99193-7

  • Online ISBN: 978-3-030-99194-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics