World Scientific
  • Search
  •   
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×
Our website is made possible by displaying certain online content using javascript.
In order to view the full content, please disable your ad blocker or whitelist our website www.worldscientific.com.

System Upgrade on Tue, Oct 25th, 2022 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.
Special Issue — Selected Papers from 2nd IEEE International Conference on Artificial Intelligence & Virtual Reality (AIVR 2019); Guest Editor: Jianquan LiuNo Access

A Biofeedback Enhanced Adaptive Virtual Reality Environment for Managing Surgical Pain and Anxiety

    https://doi.org/10.1142/S1793351X20400152Cited by:11 (Source: Crossref)

    Pain and anxiety are common accompaniments of surgery, and opioids have been the mainstay of pain management for decades, with about 80% of the surgical population leaving the hospital with an opioid prescription. Moreover, patients receiving an opioid prescription after short-stay surgeries have a 44% increased risk of long-term opioid use, and about one in 16 surgical patients becomes a long-term user. Current opioid abuse and addiction now place the US in an “opioid epidemic,” and calls for alternative pain management mechanisms. To mitigate the preoperative anxiety and postoperative pain, we developed a virtual reality (VR) experience based on Attention Restoration Theory (ART) and integrated the user’s heart rate variability (HRV) biofeedback to create an adaptive environment. A randomized control trial among 16 Total Knee Arthroplasty (TKA) patients undergoing surgery at Patewood Memorial Hospital, Greenville, SC demonstrated that patients experiencing the adaptive VR environment reported a significant decrease in preoperative anxiety (p<0.01) and postoperative pain (p<0.01) after the VR intervention. These results were also supported by the physiological measures where there was a significant increase in RR Interval (RRI) (p<0.01) and a significant decrease in the low frequency (LF)/high frequency (HF) ratio (p<0.01) and respiration rate (RR) (p=0.01).

    References

    • M. J. Hall, A. Schwartzman, J. Zhang and X. Liu, Ambulatory surgery data from hospitals and ambulatory surgery centers: United States, 2010, Natl. Health Stat. Report 2017(102) [2017] 1–15. Google Scholar
    • A. Perks, S. Chakravarti and M. Pirjo, Preoperative anxiety in neurosurgical patients, J. Neurosurg. Anesthesiol. 21(2) [2009] 127–130. Crossref, ISIGoogle Scholar
    • A. Buvanendran, J. Fiala, K. A. Patel, A. D. Golden, M. Moric and J. S. Kroin, The incidence and severity of postoperative pain following inpatient surgery, Pain Med. (United States) 16(12) [2015] 2277–2283. Crossref, ISIGoogle Scholar
    • H. Kehlet and K. Holte, Effect of postoperative analgesia on surgical outcome, Br. J. Anaesth. 87(1) [2001] 62–72. Crossref, ISIGoogle Scholar
    • J. L. Baratta, E. S. Schwenk and E. R. Viscusi, Clinical consequences of inadequate pain relief, Plast. Reconstr. Surg. 134(4S–2) [2014] 15S–21S. Crossref, ISIGoogle Scholar
    • CDC, Understanding the Epidemic, 2019. [Online]. Available: https://www.cdc.gov/drugoverdose/epidemic/index.html. Accessed: 10 October 2019. Google Scholar
    • H. Wunsch, D. N. Wijeysundera, M. A. Passarella and M. D. Neuman, Opioids prescribed after low-risk surgical procedures in the United States, 2004–2012, JAMA 315(15) [2016] 1654–1657. Crossref, ISIGoogle Scholar
    • X. Jiang et al., Chronic opioid usage in surgical patients in a large academic center, Ann. Surg. 265(4) [2017] 722–727. Crossref, ISIGoogle Scholar
    • E. C. Sun, B. D. Darnall, L. C. Baker and S. MacKey, Incidence of and risk factors for chronic opioid use among opioid-naive patients in the postoperative period, JAMA Intern. Med. 176(9) [2016] 1286–1293. Crossref, ISIGoogle Scholar
    • S. Kurtz, K. Ong, E. Lau, F. Mowat and M. Halpern, Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030, J. Bone Joint Surg. 89(4) [2007] 780. CrossrefGoogle Scholar
    • S. Boeke, H. J. Duivenvoorden, F. Verhage and A. Zwaveling, Prediction of postoperative pain and duration of hospitalization using two anxiety measures, Pain 45(3) [1991] 293–297. Crossref, ISIGoogle Scholar
    • Z. N. Kain, L. C. Mayes, A. A. Cladwell-Andrews, D. E. Karas and B. C. McClain, Preoperative anxiety, postoperative pain, and behavioral recovery in young children undergoing surgery, Pediatrics 118(2) [2006] 651–658. Crossref, ISIGoogle Scholar
    • A. Ali, D. Altun, B. H. Oguz, M. Ilhan, F. Demircan and K. Koltka, The effect of preoperative anxiety on postoperative analgesia and anesthesia recovery in patients undergoing laparascopic cholecystectomy, J. Anesth. 28(2) [2014] 222–227. Crossref, ISIGoogle Scholar
    • T. A. Dodds, D. P. Martin, W. C. Stolov and R. A. Deyo, A validation of the functional independence measurement and its performance among rehabilitation inpatients, Arch. Phys. Med. Rehabil. 74(5) [1993] 531–536. Crossref, ISIGoogle Scholar
    • M. R. Munafò and J. Stevenson, Anxiety and surgical recovery: Reinterpreting the literature, J. Psychosom. Res. 51(4) [2001] 589–596. Crossref, ISIGoogle Scholar
    • C. D. Jenkins, R. T. Jono and B. A. Stanton, Predicting completeness of symptom relief after major heart surgery, Behav. Med. 22(2) [1996] 45–57. Crossref, ISIGoogle Scholar
    • I. Maranets and Z. N. Kain, Preoperative anxiety and intraoperative anesthetic requirements, Anesth. Analg. 89(6) [1999] 1346–1351. Crossref, ISIGoogle Scholar
    • J. Gershon, E. Zimand and M. Pickering, A pilot and feasibility study of virtual reality as a distraction for children with cancer, J. Am. Acad. Child Adolesc. Psychiatry 43(10) [2004] 1243–1249. Crossref, ISIGoogle Scholar
    • A. Li, Z. Montano, J. V. Chen and J. I. Gold, Virtual reality and pain management: Current trends and future directions, Pain Manag. 1(2) [2012] 147–157. CrossrefGoogle Scholar
    • H. G. Hoffman et al., Virtual reality as an adjunctive non-pharmacologic analgesic for acute burn pain during medical procedures, Ann. Behav. Med. 41(2) [2011] 183–191. Crossref, ISIGoogle Scholar
    • P. Indovina, D. Barone, L. Gallo, A. Chirico, G. De Pietro and G. Antonio, Virtual reality as a distraction intervention to relieve pain and distress during medical procedures, Clin. J. Pain 34(9) [2018] 1. Crossref, ISIGoogle Scholar
    • L. Lagos, E. Vaschillo, B. Vaschillo, P. Lehrer, M. Bates and R. Pandina, Heart rate variability biofeedback as a strategy for dealing with competitive anxiety? A case study, Biofeedback 36(3) [2008] 109–115. Google Scholar
    • V. C. Goessl, J. E. Curtiss and S. G. Hofmann, The effect of heart rate variability biofeedback training on stress and anxiety: A meta-analysis, Psychol. Med. 47(15) [2017] 2578–2586. Crossref, ISIGoogle Scholar
    • I. Dziembowska, P. Izdebski, A. Rasmus, J. Brudny, M. Grzelczak and P. Cysewski, Effects of heart rate variability biofeedback on EEG alpha asymmetry and anxiety symptoms in male athletes: A pilot study, Appl. Psychophysiol. Biofeedback 41(2) [2016] 141–150. Crossref, ISIGoogle Scholar
    • J. Lee, J.-K. Kim and A. Wachholtz, The benefit of heart rate variability biofeedback and relaxation training in reducing trait anxiety, Korean J. Health Psychol. 20(2) [2015] 391–405. CrossrefGoogle Scholar
    • B. Rey, J. Montesa, M. Alcañiz, R. Baños and C. Botella, A preliminary study on the use of an adaptive display for the treatment of emotional disorders, PsychNology J. 3(1) [2005] 101–112. Google Scholar
    • E. Rahmani and S. A. Boren, Videogames and health improvement: A literature review of randomized controlled trials, Games Health J. 1(5) [2012] 331–341. Crossref, ISIGoogle Scholar
    • M. Good, G. C. Anderson, M. Stanton-Hicks, J. A. Grass and M. Makii, Relaxation and music reduce pain after gynecologic surgery, Pain Manag. Nurs. 3(2) [2002] 61–70. CrossrefGoogle Scholar
    • R. Melzack and P. D. Wall, Pain mechanisms? A new theory, Science 150(3699) [1965] 971–979. Crossref, ISIGoogle Scholar
    • C. Eccleston et al., Pain demands attention? A cognitive-affective model of the interruptive function of pain, Psychological Bulletin 125(3) [1999] 356–366. Crossref, ISIGoogle Scholar
    • C. D. Wickens, Processing resource in attention, in Varieties of Attention, eds. R. ParasuramanD. R. Davies (Academic Press, New York, 1984), pp. 63–101. Google Scholar
    • S. M. Lavalle, Virtual Reality, 1st edn. (Cambridge University Press, Cambridge, 2017). Google Scholar
    • C. B. Yucha and D. Montgomery, Evidence-based practice in biofeedback and neurofeedback. AAPB, Colorado, 2008. Google Scholar
    • J.-H. Kim, The effects of training using EMG biofeedback on stroke patients upper extremity functions, J. Phys. Ther. Sci. 29(6) [2017] 1085–1088. CrossrefGoogle Scholar
    • H. J. Woodford and C. I. Price, EMG biofeedback for the recovery of motor function after stroke, Cochrane Database Syst. Rev. 1(2) [2007] 1–26. Google Scholar
    • C. M. Li et al., Swallowing training combined with game-based biofeedback in poststroke dysphagia, PM&R, 8(8) [2016] 773–779. Crossref, ISIGoogle Scholar
    • T. M. Sokhadze, R. L. Cannon and D. L. Trudeau, EEG biofeedback as a treatment for substance use disorders: Review, rating of efficacy and recommendations for further research, J. Neurother. 12(1) [2008] 5–43. CrossrefGoogle Scholar
    • V. J. Monastra, S. Lynn, M. Linden, J. F. Lubar, J. Gruzelier and T. J. La Vaque, Electroencephalographic biofeedback in the treatment of attention-deficit/hyperactivity disorder, J. Neurother. 9(4) [2006] 5–34. CrossrefGoogle Scholar
    • G. Tan et al., Meta-analysis of EEG biofeedback in treating epilepsy, Clin. EEG Neurosci. 40(3) [2009] 173–179. Crossref, ISIGoogle Scholar
    • D. M. Hallman, E. M. G. Olsson, B. Von Scheéle, L. Melin and E. Lyskov, Effects of heart rate variability biofeedback in subjects with stress-related chronic neck pain: A pilot study, Appl. Psychophysiol. Biofeedback 36(2) [2011] 71–80. Crossref, ISIGoogle Scholar
    • G. Henriques, S. Keffer, C. Abrahamson and S. J. Horst, Exploring the effectiveness of a computer-based heart rate variability biofeedback program in reducing anxiety in college students, Appl. Psychophysiol. Biofeedback 36(2) [2011] 101–112. Crossref, ISIGoogle Scholar
    • C. A. Prato and C. B. Yucha, Biofeedback-assisted relaxation training to decrease test anxiety in nursing students, Nurs. Educ. Perspect. 34(2) [2013] 76–81. Google Scholar
    • R. Reiner, Integrating a portable biofeedback device into clinical practice for patients with anxiety disorders: Results of a pilot study, Appl. Psychophysiol. Biofeedback 33(1) [2008] 55–61. Crossref, ISIGoogle Scholar
    • P. M. Lehrer, R. L. Woolfolk and W. E. Sime, Principles and Practice of Stress Management (Guilford Press, 2007). Google Scholar
    • L. K. McCorry, Physiology of the autonomic nervous system, Am. J. Pharm. Educ. 71(4) [2007] 270–276. Crossref, ISIGoogle Scholar
    • R. Kaplan and S. Kaplan, The Experience of Nature: A Psychological Perspective, 1st edn. (Cambridge University Press, Cambridge, UK, 1989). Google Scholar
    • J. M. Walch, B. S. Rabin, R. Day, J. N. Williams, K. Choi and J. D. Kang, The effect of sunlight on postoperative analgesic medication use: A prospective study of patients undergoing spinal surgery, Psychosom. Med. 67(1) [2005] 156–163. Crossref, ISIGoogle Scholar
    • T. Hartig, R. Mitchell, S. de Vries and H. Frumkin, Nature and health, Annu. Rev. Public Health 35(1) [2014] 207–228. Crossref, ISIGoogle Scholar
    • E. A. McMahan and D. Estes, The effect of contact with natural environments on positive and negative affect: A meta-analysis, J. Posit. Psychol. 10(6) [2015] 507–519. Crossref, ISIGoogle Scholar
    • M. P. White, I. Alcock, B. W. Wheeler and M. H. Depledge, Coastal proximity, health and well-being: Results from a longitudinal panel survey, Health Place 23 [2013] 97–103. Crossref, ISIGoogle Scholar
    • A. Wright, Beginner’s Guide to Colour Psychology (Colour Affects Ltd, London, 1998). Google Scholar
    • N. Kaya and H. H. Epps, Relationship between color and emotion: A study of college students, Coll. Stud. J. 38(3) [2004] 396–405. Google Scholar
    • L. Eiseman, Color?: Messages and Meanings? A Pantone Color Resource (Hand Books Press: Cincinnati, 2006). Google Scholar
    • I. M. Lin, L. Y. Tai and S. Y. Fan, Breathing at a rate of 5.5 breaths per minute with equal inhalation-to-exhalation ratio increases heart rate variability, Int. J. Psychophysiol. 91(3) [2014] 206–211. Crossref, ISIGoogle Scholar
    • J. Brooke, SUS: A ‘quick and dirty’ usability scale, in Usability Evaluation in Industry, eds. P. W. JordanB. ThomasB. A. WeerdmeesterI. L. McClelland (Taylor & Francis, London, 1996), pp. 189–194. Google Scholar
    • C. Owsley, R. Sekuler and D. Siemsen, Contrast sensitivity throughout adulthood, Vision Res. 23(7) [1983] 689–699. Crossref, ISIGoogle Scholar
    • E. Facco et al., Validation of visual analogue scale for anxiety (VAS-A) in preanesthesia evaluation, Minerva Anestesiol. 79(12) [2013] 1389–1395. ISIGoogle Scholar
    • A. K. van der Bij, S. de Weerd, R. J. L. M. Cikot, E. A. P. Steegers and J. C. C. Braspenning, Validation of the Dutch short form of the state scale of the Spielberger state-trait anxiety inventory: Considerations for usage in screening outcomes, Public Health Genom. 6(2) [2003] 84–87. CrossrefGoogle Scholar
    • T. Schubert, F. Friedmann and H. Regenbrecht, The experience of presence: Factor analytic insights, Presence Teleoperators Virtual Environ. 10(3) [2001] 266–281. Crossref, ISIGoogle Scholar
    • M. Malik et al., Heart rate variability: Standards of measurement, physiological interpretation, and clinical use, Eur. Heart J. 17(3) [1996] 354–381. Crossref, ISIGoogle Scholar
    • M. A. Peltola, Role of editing of R-R intervals in the analysis of heart rate variability, Front. Physiol. 3(148) [2012] 1–10. Google Scholar
    • J. F. Thayer, F. Åhs, M. Fredrikson, J. J. Sollers and T. D. Wager, A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health, Neurosci. Biobehav. Rev. 36(2) [2012] 747–756. Crossref, ISIGoogle Scholar
    • D. K. Brown, J. L. Barton and V. F. Gladwell, Viewing nature scenes positively affects recovery of autonomic function following acute-mental stress, Environ. Sci. Technol. 47(11) [2013] 5562–5569. Crossref, ISIGoogle Scholar
    • B. M. Appelhans and L. J. Luecken, Heart rate variability and pain: Associations of two interrelated homeostatic processes, Biol. Psychol. 77(2) [2008] 174–182. Crossref, ISIGoogle Scholar
    • J. A. Chalmers, D. S. Quintana, M. J. A. Abbott and A. H. Kemp, Anxiety disorders are associated with reduced heart rate variability: A meta-analysis, Front. Psychiatry 5 [2014] 1–11. Crossref, ISIGoogle Scholar
    • A. Malliani, M. Pagani, F. Lombardi and S. Cerutti, Cardiovascular neural regulation explored in the frequency domain, Circulation 84(2) [1991] 482–492. Crossref, ISIGoogle Scholar
    • M. P. Paulus, The breathing conundrum — Interoceptive sensitivity and anxiety, Depress. Anxiety 30(4) [2013] 315–320. Crossref, ISIGoogle Scholar
    • Y. Masaoka and I. Homma, Anxiety and respiratory patterns: Their relationship during mental stress and physical load, Int. J. Psychophysiol. 27(2) [1997] 153–159. Crossref, ISIGoogle Scholar
    • H. Jafari, I. Courtois, O. Van den Bergh, J. W. S. Vlaeyen and I. Van Diest, Pain and respiration, Pain 158(6) [2017] 995–1006. Crossref, ISIGoogle Scholar
    • D. C. Fowles, M. J. Christie, R. Edelberg, W. W. Grings, D. T. Lykken and P. H. Venables, Publication recommendations for electrodermal measurements, Psychophysiology 18(3) [1981] 232–239. Crossref, ISIGoogle Scholar
    • A. A. Dubé, M. Duquette, M. Roy, F. Lepore, G. Duncan and P. Rainville, Brain activity associated with the electrodermal reactivity to acute heat pain, Neuroimage 45(1) [2009] 169–180. Crossref, ISIGoogle Scholar
    • M. Sarchiapone et al., The association between electrodermal activity (EDA), depression and suicidal behaviour: A systematic review and narrative synthesis, BMC Psychiatry 18(1) [2018] 1–27. Crossref, ISIGoogle Scholar
    • F. Shaffer and J. P. Ginsberg, An overview of heart rate variability metrics and norms, Front. Public Health 5 [2017] 1–32. Crossref, ISIGoogle Scholar
    • J. J. Braithwaite, D. G. Watson, R. Jones and M. Rowe, A Guide for Analysing Electrodermal Activity (EDA) & Skin Conductance Responses (SCRs) for Psychological Experiments (Behavioural Brain Sciences Centre/University of Birmingham, Edgbaston, UK, 2015), pp. 1–43. Google Scholar
    Remember to check out the Most Cited Articles!

    Check out our titles in Semantic Computing!