Biofeedback as a stress management tool: a systematic review

  • Lauren KennedyEmail author
  • Sarah Henrickson Parker
Original Article


Inappropriate management of acute stress can negatively affect cognition and task performance. Frequently occurring acute stress encounters can lead to cardiovascular and immunity deficiencies, and psychological disorders such as depression, fatigue, and burnout. Biofeedback can be used as a non-invasive, passive, continuous method of managing stress in real time. A systematic review of biofeedback as a real-time stress management intervention for non-patients was conducted to identify literature between 2000 and 2017, yielding 17 studies evaluating physiological, psychological, and/or performance metrics. Participants represent convenience samples (N = 9 studies) and deliberately selected samples, whose optimal performance under stress is critical for occupational success (N = 8 studies). Various methods to collect data, display biofeedback, induce stress, and measure performance were reported. Overall, biofeedback is an effective intervention that can be used to reduce physiological and subjective stress, and enhance performance. This is especially true among professionals, whose job performance requires appropriate stress management.


Acute stress Chronic stress Stress management Biofeedback Performance 



This work was supported by an Agency for Healthcare Research and Quality grant (R18HS023465-02) awarded to Sarah Henrickson Parker, PhD.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving animal and human participants

This article does not contain any studies with human participants or animals performed by any of the authors.


  1. Allen RJ (1983) Human stress: its nature and control. Burgess, MinneapolisGoogle Scholar
  2. Alvarez GA (2011) Representing multiple objects as an ensemble enhances visual cognition. Trends in Cogn Sci 15(3):122–131. CrossRefGoogle Scholar
  3. Andersen JP, Gustafsberg H (2016) A training method to improve police use of force decision making: a randomized controlled trial. SAGE Open 6(2):1–13. CrossRefGoogle Scholar
  4. Arora S, Sevdalis N, Aggarwal R, Sirimanna P, Darzi A, Kneebone R (2010a) Stress impairs psychomotor performance in novice laparoscopic surgeons. Surg Endosc Other Interv Tech 24(10):2588–2593. CrossRefGoogle Scholar
  5. Arora S, Sevdalis N, Nestel D, Woloshynowych M, Darzi A, Kneebone R (2010b) The impact of stress on surgical performance: a systematic review of the literature. Surgery 147(3):318–330.e6. CrossRefGoogle Scholar
  6. Astor PJ, Adam MTP, Jerčić P, Schaaff K, Weinhardt C (2013) Integrating biosignals into information systems: A NeuroIS tool for improving emotion regulation. J Manag Inf Syst 30(3):247–278. CrossRefGoogle Scholar
  7. Atkins PW, Wood RE, Rutgers PJ (2002) The effects of feedback format on dynamic decision making. Organ Behav Hum Decis Process 88(2):587–604. CrossRefGoogle Scholar
  8. Balch CM, Freischlag JA, Shanafelt TD (2009) Stress and burnout among surgeons. Arch Surg 144(4):371–376. CrossRefGoogle Scholar
  9. Bormann JE, Becker S, Gershwin M, Kelly A, Pada L, Smith TL, Gifford AL (2006) Relationship of frequent mantram repetition to emotional and spiritual well-being in healthcare workers. J Contin Educ Nurs 37(5):218–224. CrossRefGoogle Scholar
  10. Bouchard S, Bernier F, Boivin É, Morin B, Robillard G (2012) Using biofeedback while immersed in a stressful videogame increases the effectiveness of stress management skills in soldiers. PLoS One 7(4):1–11. CrossRefGoogle Scholar
  11. Bradley RT, McCraty R, Atkinson M, Tomasino D, Daugherty A, Arguelles L (2010) Emotion self-regulation, psychophysiological coherence, and test anxiety: Results from an experiment using electrophysiological measures. Appl Psychophysiol Biofeedback 35(4):261–283. CrossRefGoogle Scholar
  12. Childre D, McCraty R (2010) Coherence: bridging personal, social, and global health. Altern Ther Health Med 16(4):10–24Google Scholar
  13. Cohen I, Brinkman W-P, Neerincx MA (2015) Modelling environmental and cognitive factors to predict performance in a stressful training scenario on a naval ship simulator. Cogn Technol Work 17(4):503–519. CrossRefGoogle Scholar
  14. Cohen I, Brinkman W-P, Neerincx MA (2016) Effects of different real-time feedback types on human performance in high-demanding work conditions. Int J Hum Comput Stud 91:1–12. CrossRefGoogle Scholar
  15. Dadashi N, Golightly D, Sharples S (2017) Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance. Cogn Technol Work 19(4):561–570. CrossRefGoogle Scholar
  16. Delahaij R, Van Dam K (2017) Coping with acute stress in the military: The influence of coping style, coping self-efficacy and appraisal emotions. Personal Individ Differ 119:13–18. CrossRefGoogle Scholar
  17. Delahaij R, van Dam K, Gaillard AWK, Soeters J (2011) Predicting performance under acute stress: The role of individual characteristics. Int J Stress Manag 18(1):49–66. CrossRefGoogle Scholar
  18. Derogatis LR, Melisaratos N (2012). The brief symptom inventory: an introductory report the brief symptom inventory: an introductory report. Psychol Med (July 2009), 595–605.
  19. Dziembowska I, Izdebski P, Rasmus A, Brudny J, Grzelczak M, Cysewski P (2016) Effects of heart rate variability biofeedback on EEG alpha asymmetry and anxiety symptoms in male athletes: a pilot study. Appl Psychophysiol Biofeedback 41(2):141–150. CrossRefGoogle Scholar
  20. Eddie D, Vaschillo E, Vaschillo B, Lehrer P (2015) Heart rate variability biofeedback: theoretical basis, delivery, and its potential for the treatment of substance use disorders. Addict Res Theory 23(4):266–272. CrossRefGoogle Scholar
  21. Escolano C, Navarro-Gil M, Garcia-Campayo J, Minguez J (2014) The effects of a single session of upper alpha neurofeedback for cognitive enhancement: a sham-controlled study. Appl Psychophysiol Biofeedback 39(3–4):227–236. CrossRefGoogle Scholar
  22. Evetovich TK, Conley DS, Todd JB, Rogers DC, Stone TL (2007) Effect of mechanomyography as a biofeedback method to enhance muscle relaxation and performance. J Strength Cond Res 21(1):96–99. CrossRefGoogle Scholar
  23. Frazier SE, Parker SH (2018) Measurement of physiological responses to acute stress in multiple occupations: a systematic review and implications for front line healthcare providers. Transl Behav Med. Google Scholar
  24. Gevirtz R (2013) The promise of heart rate variability biofeedback: evidence based applications. Biofeedback 41(3):110–120. CrossRefGoogle Scholar
  25. Greenberg SF, Valletutti PJ (1980) Stress and the helping professions. P.H. Brookes, BaltimoreGoogle Scholar
  26. Henriques G, Keffer S, Abrahamson C, Horst SJ (2011) Exploring the effectiveness of a computer-based heart rate variability biofeedback program in reducing anxiety in college students. Appl Psychophysiol Biofeedback 36(2):101–112. CrossRefGoogle Scholar
  27. Hupbach A, Fieman R (2012) Moderate stress enhances immediate and delayed retrieval of educationally relevant material in healthy young men. Behav Neurosci 126(6):819–825. CrossRefGoogle Scholar
  28. Joseph B, Parvaneh S, Swartz T, Haider A, Hassan A, Kulavatunyou N, Rhee P (2016) Stress among surgical attendings and trainees: a quantitative assessment during trauma activation and emergency surgeries. J Trauma Acute Care Surg 81(4):1. Google Scholar
  29. Khazan IZ (2013) The clinical handbook of biofeedback, 1st edn. Wiley, New York. CrossRefGoogle Scholar
  30. Kim PW, Kim SA, Jung KH (2012) Electrocardiographic anxiety profiles improve speech anxiety. Appl Psychophysiol Biofeedback 37(4):261–267. CrossRefGoogle Scholar
  31. Klampfer B, Flin R, Helmreich R, Häusler R, Sexton B, Fletcher G, Amacher A (2001) Enhancing performance in high risk environments: recommendations for the use of behavioural markers. In: Group interaction in high risk environments, pp 6–33. Retrieved from
  32. Kontogiannis T, Kossiavelou Z (1999) Stress and team performance: Principles and challenges for intelligent decision aids. Saf Sci 33(3):103–128. CrossRefGoogle Scholar
  33. Kudo N, Shinohara H, Kodama H (2014) Heart rate variability biofeedback intervention for reduction of psychological stress during the early postpartum period. Appl Psychophysiol Biofeedback 39(3–4):203–211. CrossRefGoogle Scholar
  34. Laborde S, Mosley E, Thayer JF (2017) Heart rate variability and cardiac vagal tone in psychophysiological research—recommendations for experiment planning, data analysis, and data reporting. Front Psychol 8:1–18. CrossRefGoogle Scholar
  35. LeBlanc VR (2009) The effects of acute stress on performance: Implications for health professions education. Acad Med 84(10):S25–S33. CrossRefGoogle Scholar
  36. Lehrer P (2007) Principles and practice of stress management: advances in the field. Biofeedback 35(3):82–84Google Scholar
  37. Lehrer P (2013a) History of heart rate variability biofeedback research: a personal and scientific voyage. Biofeedback 41(3):88–97. CrossRefGoogle Scholar
  38. Lehrer P (2013b) How does heart rate variability biofeedback work? Resonance, the baroreflex, and other mechanisms. Biofeedback 41(1):26–31. CrossRefGoogle Scholar
  39. Lehrer P, Eddie D (2013) Dynamic processes in regulation and some implications for biofeedback and biobehavioral interventions. Appl Psychophysiol Biofeedback 38(2):143–155. CrossRefGoogle Scholar
  40. Lehrer P, Gevirtz R (2014) Heart rate variability biofeedback: How and why does it work? Front Psychol 5:1–9. CrossRefGoogle Scholar
  41. Lehrer P, Vaschillo E (2008) The future of heart rate variability biofeedback. Biofeedback 36(1):11–14Google Scholar
  42. Lehrer P, Vaschillo E, Vaschillo B (2000) Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training. Appl Psychophysiol Biofeedback 25(3):177–191. CrossRefGoogle Scholar
  43. Lehrer P, Vaschillo B, Zucker T, Graves J, Katsamanis M, Aviles M, Wamboldt F (2013) Protocol for heart rate variability biofeedback training. Biofeedback 41(3):98–109. CrossRefGoogle Scholar
  44. Ley R (1999) The modification of breathing behavior: pavlovian and operant control in emotion and cognition. Behav Modif 23(3):441–479CrossRefGoogle Scholar
  45. Marteau TM, Bekker H (1992) The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Br J Clin Psychol 31(3):301–306. CrossRefGoogle Scholar
  46. Mazur LM, Mosaly PR, Hoyle LM, Jones EL, Marks LB (2013) Subjective and objective quantification of physician’s workload and performance during radiation therapy planning tasks. Pract Radiat Oncol 3(4):e171–e177. CrossRefGoogle Scholar
  47. Mazur LM, Mosaly PR, Hoyle LM, Jones EL, Chera BS, Marks LB (2014) Relating physician’s workload with errors during radiation therapy planning. Pract Radiat Oncol 4(2):71–75. CrossRefGoogle Scholar
  48. McCraty R, Atkinson M, Tomasino D, Bradley RT (2009a). The coherent heart: heart-brain interactions, psychophysiological coherence, and the emergence of system-wide order. Integral Rev 5(2):10–115. (Publication No. 06–022)Google Scholar
  49. McCraty R, Atkinson M, Lipsenthal L, Arguelles L (2009b) New hope for correctional officers: An innovative program for reducing stress and health risks. Appl Psychophysiol Biofeedback 34(4):251–272. CrossRefGoogle Scholar
  50. McEwen BS (2006) Protective and damaging effects of stress mediators: central role of the brain. Dialogues in Clin Neurosci 8(4):367–381. Google Scholar
  51. Moorthy K, Munz Y, Dosis A, Bann S, Darzi A (2003) The effect of stress-inducing conditions on the performance of a laparoscopic task. Surg Endosc Other Interv Techniques 17(9):1481–1484. Google Scholar
  52. Nixon J, Charles R (2017) Understanding the human performance envelope using electrophysiological measures from wearable technology. Cogn Technol Work 19(4):655–666. CrossRefGoogle Scholar
  53. Pluyter JR, Buzink SN, Rutkowski AF, Jakimowicz JJ (2010) Do absorption and realistic distraction influence performance of component task surgical procedure? Surg Endosc Other Interv Techniques 24(4):902–907. CrossRefGoogle Scholar
  54. Prinsloo GE, Rauch HG, Lambert M, Muench F, Noakes T, Derman W (2011) The effect of short duration heart rate variability (HRV) biofeedback on cognitive stress. Appl Cogn Psychol 25(5):792–801CrossRefGoogle Scholar
  55. Prinsloo GE, Derman WE, Lambert MI, Rauch HGL (2013a) The effect of a single episode of short duration heart rate variability biofeedback on measures of anxiety and relaxation states. Int J Stress Manag 20(4):391–411. CrossRefGoogle Scholar
  56. Prinsloo GE, Rauch HGL, Karpul D, Derman WE (2013b) The effect of a single session of short duration heart rate variability biofeedback on EEG: a pilot study. Appl Psychophysiol Biofeedback 38(1):45–56. CrossRefGoogle Scholar
  57. Raaijmakers SF, Steel FW, de Goede M, van Wouwe NC, van Erp JBF, Brouwer A-M (2013) Heart rate variability and skin conductance biofeedback: a triple-blind randomized controlled study. 2013. In: Humaine Association Conference on Affective Computing and Intelligent Interaction, Sept, 289–293.
  58. Rosenstein BAH (2012) Physician stress and burnout: What can we do? Phys Executive J 11/12:22–30Google Scholar
  59. Rusciano A, Corradini G, Stoianov I (2017) Neuroplus biofeedback improves attention, resilience, and injury prevention in elite soccer players. Psychophysiology. Google Scholar
  60. Schoenberg PLA, David AS (2014) Biofeedback for psychiatric disorders: a systematic review. Appl Psychophysiol Biofeedback 39(2):109–135. CrossRefGoogle Scholar
  61. Schwartz MS (2010) A new improved universally accepted official definition of biofeedback: where did it come from? Why? Who did it? Who is it for? What’s next? Biofeedback, 38(3):88–90. CrossRefGoogle Scholar
  62. Shah P, Carpenter PA (1995) Conceptual limitations in comprehending line graphs. J Exp Psychol 124(1):43–61. CrossRefGoogle Scholar
  63. Sharma N, Gedeon T (2012) Objective measures, sensors and computational techniques for stress recognition and classification: a survey. Comput Methods Programs Biomed 108(3):1287–1301. CrossRefGoogle Scholar
  64. Sherlin L, Muench F, Wyckoff S (2010) Respiratory sinus arrhythmia feedback in a stressed population exposed to a brief stressor demonstrated by quantitative EEG and sLORETA. Appl Psychophysiol Biofeedback 35:219–228. CrossRefGoogle Scholar
  65. Sherlin LH, Larson NC, Sherlin RM (2013) Developing a performance brain training™ approach for baseball: A process analysis with descriptive data. Appl Psychophysiol Biofeedback 38(1):29–44. CrossRefGoogle Scholar
  66. Sime J-A (2007) Designing emergency response training: seven ways to reduce stress. In: IADIS International Conference on Cognition and Exploratory Learning in Digital Age, pp 41–48Google Scholar
  67. Spielberger CD, Gorsuch RL (1983) State-trait anxiety inventory for adults: manual, instrument, and scoring guide. Mind Garden, Inc, Menlo ParkGoogle Scholar
  68. Summerfield C, Egner T (2009) Expectation (and attention) in visual cognition. Trends Cogn Sci 13(9):403–409. CrossRefGoogle Scholar
  69. Talcott CP, Bennett KB, Martinez SG, Shattuck LG, Stansifer C (2007) Perception-action icons: an interface design strategy for intermediate domains. Hum Factors 49(1):120–135. CrossRefGoogle Scholar
  70. Tanev G, Saadi DB, Hoppe K, Sorensen HBD (2014). Classification of acute stress using linear and non-linear heart rate variability analysis derived from sternal ECG. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp 3386–3389.
  71. Thayer JF, Hansen AL, Saus-Rose E, Johnsen BH (2009) Heart rate variability, prefrontal neural function, and cognitive performance: the neurovisceral integration perspective on self-regulation, adaptation, and health. Ann Behav Med 37(2):141–153. CrossRefGoogle Scholar
  72. Thayer JF, Åhs F, Fredrikson M, Sollers JJ, Wager TD (2012) 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):747–756. CrossRefGoogle Scholar
  73. van Dijk ET, Westerink JHDM., Beute F, IJsselsteijn WA (2015). In sync: The effect of physiology feedback on the match between heart rate and self-reported stress. Biomed Res Int 2015:1–9. CrossRefGoogle Scholar
  74. Vaschillo EG, Vaschillo B, Lehrer PM (2006) Characteristics of resonance in heart rate variability stimulated by biofeedback. Appl Psychophysiol Biofeedback 31(2):129–142. CrossRefGoogle Scholar
  75. Venables L, Fairclough SH (2004) Establishing the psychophysiological variables that can identify and predict operator subjective state. Proc Hum Factors Ergon Soc Ann Meet 48:90–94. CrossRefGoogle Scholar
  76. Vine SJ, Freeman P, Moore LJ, Chandra-Ramanan R, Wilson MR (2013) Evaluating stress as a challenge is associated with superior attentional control and motor skill performance: Testing the predictions of the biopsychosocial model of challenge and threat. J Exp Psychol: Appl 19(3):185–194. Google Scholar
  77. Weigl M, Stefan P, Abhari K, Wucherer P, Fallavollita P, Lazarovici M, Catchpole K (2016) Intraoperative disruptions, surgeon’s mental workload, and technical performance in a full-scale simulated procedure. Surg Endos Other Interv Tech 30(2):559–566. CrossRefGoogle Scholar
  78. Wetzel CM, Kneebone RL, Woloshynowych M, Nestel D, Moorthy K, Kidd J, Darzi A (2006) The effects of stress on surgical performance. Am J Surg 191(1):5–10. CrossRefGoogle Scholar
  79. Whited A, Larkin KT, Whited M (2014) Effectiveness of emWave biofeedback in improving heart rate variability reactivity to and recovery from stress. Appl Psychophysiol Biofeedback 39(2):75–88. CrossRefGoogle Scholar
  80. Wickens CD, Andre AD (1990) Proximity compatibility and information display: effects of color, space, and object display on information integration. Hum Fact 32(1):61–77. CrossRefGoogle Scholar
  81. Wickens CD, Carswell CM (1995) The proximity compatibility principle: Its psychological foundation and relevance to display design. Hum Fact 37(3):473–494. CrossRefGoogle Scholar
  82. Yurko YY, Scerbo MW, Prabhu AS, Acker CE, Stefanidis D (2010) Higher mental workload is associated with poorer laparoscopic performance as measured by the NASA-TLX tool. Simul Healthc 5(5):267–271. CrossRefGoogle Scholar
  83. Zauszniewski JA, Au T, Musil CM (2013) Heart rate variability biofeedback in grandmothers raising grandchildren: effects on stress, emotions, and cognitions. Biofeedback 41(3):144–149. CrossRefGoogle Scholar
  84. Zhai J, Barreto A (2006) Stress recognition using non-invasive technology. In: Proceedings of the 19th International Florida Artificial Intelligence Research Society Conference (FLAIRS), pp 395–400.

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Authors and Affiliations

  1. 1.Virginia Tech Carilion Research InstituteRoanokeUSA
  2. 2.Graduate Program in Translational Biology, Medicine, and Health, Virginia TechBlacksburgUSA
  3. 3.Department of Basic Science EducationVirginia Tech Carilion School of MedicineRoanokeUSA
  4. 4.Carilion ClinicRoanokeUSA

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