Heart rate-based window segmentation improves accuracy of classifying posttraumatic stress disorder using heart rate variability measures

Physiological Measurement

Volumn 38, Issue 6, 2017, Pages 1061-1076

  Reinertsen, Erik ^a   Nemati, Shamim ^b   Vest, Adriana N ^b,c   Vaccarino, Viola ^b,c   Lampert, Rachel ^d   Shah, Amit J ^b,c   Clifford, Gari D ^a,b  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c EMORY UNIVERSITY   (United States)

^d YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

electrocardiogram; heart rate variability; machine learning; post traumatic stress disorder; segmentation

Indexed keywords

DISEASES; HEART; LEARNING SYSTEMS; PATIENT MONITORING; STATISTICAL TESTS;

AUTONOMIC NERVOUS; CLASSIFIER PERFORMANCE; HEART RATE VARIABILITY; HEART-RATE; POSTTRAUMATIC STRESS DISORDER; RR INTERVALS; SEGMENTATION; SINGLE CHANNEL ECG; SYSTEM FUNCTIONS; VARIABILITY MEASURES;

ELECTROCARDIOGRAPHY;

CASE CONTROL STUDY; ELECTROCARDIOGRAPHY; HEART RATE; HUMAN; MACHINE LEARNING; MALE; PATHOPHYSIOLOGY; POSTTRAUMATIC STRESS DISORDER; PSYCHOLOGY; SIGNAL PROCESSING; TIME FACTOR; VETERAN;

CASE-CONTROL STUDIES; ELECTROCARDIOGRAPHY; HEART RATE; HUMANS; MACHINE LEARNING; MALE; SIGNAL PROCESSING, COMPUTER-ASSISTED; STRESS DISORDERS, POST-TRAUMATIC; TIME FACTORS; VETERANS;

EID: 85019542038     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/1361-6579/aa6e9c     Document Type: Article

References (45)

1. Akselrod S et al 1981 Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control Science 213 220-22
2. Arlot S and Celisse A 2010 A survey of cross-validation procedures for model selection Stat. Surv. 4 40-79
3. Bauer A et al 2006a Deceleration capacity of heart rate as a predictor of mortality after myocardial infarction: cohort study Lancet 367 1674-81
4. Bauer A et al 2006b Phase-rectified signal averaging detects quasi-periodicities in non-stationary data Phys. A: Stat. Mech. Appl. 364 423-34
5. Behar J et al 2013 A review of current sleep screening applications for smartphones Physiol. Meas. 34 R29-46
6. Bigger J T et al 1992 Frequency domain measures of heart period variability and mortality after myocardial infarction Circulation 85 164-71
7. Bishop C M 1995 Neural Networks for Pattern Recognition (Oxford: Oxford University Press)
8. Breiman L 1996 Bagging predictors Mach. Learn. 24 123-40
9. Burns M N et al 2011 Harnessing context sensing to develop a mobile intervention for depression J. Med. Internet Res. 13 e55
10. Clifford G D 2002 Signal processing methods for heart rate variability PhD Thesis University of Oxford
11. Clifford G D and Tarassenko L 2004 Segmenting cardiac-related data using sleep stages increases separation between normal subjects and apnoeic patients Physiol. Meas. 25 N27-35
12. Dohrenwend B P et al 2006 The psychological risks of Vietnam for U.S. veterans: a revisit with new data and methods Science 313 979-82
13. Galatzer-Levy I R et al 2014 Quantitative forecasting of PTSD from early trauma responses: a machine learning application J. Psychiatric Res. 59 68-76
14. Germain A 2013 Sleep disturbances as the Hallmark of PTSD: where are we now? Am. J. Psychiatry 170 372-82
15. Germain A et al 2005 A brief sleep scale for posttraumatic stress disorder: pittsburgh sleep quality index addendum for PTSD J. Anxiety Disorders 19 233-44
16. Julien C 2006 The enigma of Mayer waves: facts and models Cardiovascular Res. 70 12-21
17. Karam E G et al 2014 Cumulative traumas and risk thresholds: 12-month Ptsd in the world mental health (WMH) surveys Depression Anxiety 31 130-42
18. Karstoft K I et al 2015 Bridging a translational gap: using machine learning to improve the prediction of PTSD BMC Psychiatry 15 30
19. Kessler R C et al 2014 How well can post-traumatic stress disorder be predicted from pre-trauma risk factors? an exploratory study in the WHO world mental health surveys World Psychiatry 13 265-74
20. Khoury N M et al 2012 The renin-angiotensin pathway in posttraumatic stress disorder: angiotensin-converting enzyme inhibitors and angiotensin receptor blockers are associated with fewer traumatic stress symptoms J. Clin. Psychiatry 73 849-55
21. Kobayashi I, Lavela J and Mellman T A 2014 Nocturnal autonomic balance and sleep in PTSD and resilience J. Traumatic Stress 27 712-6
22. Kok B C et al 2012 Posttraumatic stress disorder associated with combat service in Iraq or Afghanistan: reconciling prevalence differences between studies J. Nervous Mental Dis. 200 444-50
23. Liddell B J et al 2016 Heart rate variability and the relationship between trauma exposure age, and psychopathology in a post-conflict setting BMC Psychiatry 16 133
24. Lo A et al 2015 Why significant variables aren't automatically good predictors Proc. Natl Acad. Sci. 112 13892-7
25. Malik M 1996 Heart rate variability: standards of measurement, physiological interpretation, and clinical use Eur. Heart J. 17 354-81
26. Marmar C R et al 2015 Course of posttraumatic stress disorder 40 years after the vietnam war: findings from the National Vietnam Veterans Longitudinal Study JAMA Psychiatry 10016 875-81
27. Minassian A et al 2014 Heart rate variability characteristics in a large group of active-duty Marines and relationship to posttraumatic stress Psychosomatic Med. 76 292-301
28. Monasterio V, Burgess F and Clifford G D 2012 Robust classification of neonatal apno ea-related desaturations Physiol. Meas. 33 1503-16
29. Osipov M et al 2015 Objective identification and analysis of physiological and behavioral signs of schizophrenia J. Mental Health 24 276-82
30. Palmius N et al 2016 Detecting bipolar depression from geographic location data IEEE Trans. Biomed. Eng. https://doi.org/10.1109/TBME.2016.2611862
31. Pan Q et al 2016 Do the deceleration/acceleration capacities of heart rate reflect cardiac sympathetic or vagal activity? a model study Med. Biol. Eng. Comput. 54 1-13
32. Resnick H S et al 1993 Prevalence of civilian trauma and posttraumatic stress disorder in a representative national sample of women J. Consulting Clin. Psychol. 61 984-91
33. Sano A and Picard R W 2013 Stress recognition using wearable sensors and mobile phones Humaine Association Conf. on Affective Computing and Intelligent Interaction Stress https://doi.org/10.1109/ACII.2013.117
34. Shah A J et al 2013 Posttraumatic stress disorder and impaired autonomic modulation in male twins Biol. Psychiatry 73 1103-10
35. Su S et al 2010 Common genes contribute to depressive symptoms and heart rate variability: the twins heart study Twin Res. Hum. Genet. 13 1-9
36. Sundin J et al 2014 Mental health outcomes in US and UK military personnel returning from Iraq Br. J. Psychiatry 204 200-7
37. Tan G et al 2011 Heart rate variability (HRV) and posttraumatic stress disorder (PTSD): a pilot study Appl. Psychophysiol. Biofeedback 36 27-35
38. Tan G et al 2009 Associations among pain, PTSD, mTBI, and heart rate variability in veterans of operation enduring and Iraqi freedom: a pilot study Pain Med. 10 1237-45
39. Tsanas A et al 2016 Daily longitudinal self-monitoring of mood variability in bipolar disorder and borderline personality disorder J. Affective Disorders 205 225-33
40. Vanoli E et al 1995 Heart rate variability during specific sleep stages Circulation 91 1918-22
41. Viola A U et al 2002 Sleep processes exert a predominant influence on the 24 h profile of heart rate variability J. Biol. Rhythms 17 539-47
42. Woodward S H et al 2009 Autonomic activation during sleep in posttraumatic stress disorder and panic: a mattress actigraphic study Biol. Psychiatry 66 41-6
43. Yehuda R 2002 Post-traumatic stress disorder New Engl. J. Med. 346 108-14
44. Yehuda R et al 2015 Post-traumatic stress disorder Nat. Rev. Dis. Primers 1 15057
45. Yesavage J A et al 2014 Longitudinal assessment of sleep disordered breathing in Vietnam veterans with post-traumatic stress disorder Nat. Sci. Sleep 6 123-7