Short term Heart Rate Variability to predict blood pressure drops due to standing: A pilot study

BMC Medical Informatics and Decision Making

Volumn 15, Issue 3, 2015, Pages

  Sannino, G ^a   Melillo, P ^b   Stranges, S ^c   De Pietro, G ^a   Pecchia, L ^d  

^a ICAR CNR   (Italy)

^b SECOND UNIVERSITY OF NAPLES   (Italy)

^c UNIVERSITY OF WARWICK   (United Kingdom)

^d UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

fall prediction in the elderly; Heart Rate Variability; standing hypotension

Indexed keywords

ADULT; BLOOD PRESSURE; ELECTROCARDIOGRAPHY; FEMALE; HEART RATE; HUMAN; MALE; NORMAL HUMAN; ORTHOSTATIC HYPOTENSION; PHYSIOLOGY; PILOT STUDY; THEORETICAL MODEL; YOUNG ADULT;

ADULT; BLOOD PRESSURE; ELECTROCARDIOGRAPHY; FEMALE; HEALTHY VOLUNTEERS; HEART RATE; HUMANS; HYPOTENSION, ORTHOSTATIC; MALE; MODELS, THEORETICAL; PILOT PROJECTS; YOUNG ADULT;

EID: 84977592300     PISSN: None     EISSN: 14726947     Source Type: Journal    
DOI: 10.1186/1472-6947-15-S3-S2     Document Type: Article

References (42)

1. Freeman R, Wieling W, Axelrod FB, Benditt DG, Benarroch E, Biaggioni I, Cheshire WP, Chelimsky T, Cortelli P, Gibbons CH: Consensus statement on the definition of orthostatic hypotension, neurally mediated syncope and the postural tachycardia syndrome. Clinical Autonomic Research. 2011, 21 (2): 69-72. 10.1007/s10286-011-0119-5.
2. Kemp AH, Quintana DS, Gray MA, Felmingham KL, Brown K, Gatt JM: Impact of depression and antidepressant treatment on heart rate variability: A review and meta-analysis. Biological psychiatry. 2010, 67 (11): 1067-1074. 10.1016/j.biopsych.2009.12.012.
3. Koschke M, Boettger MK, Schulz S, Berger S, Terhaar J, Voss A, Yeragani VK, Bar KJ: Autonomy of autonomic dysfunction in major depression. Psychosomatic medicine. 2009, 71 (8): 852-860. 10.1097/PSY.0b013e3181b8bb7a.
4. Yamasaki Y, Kodama M, Matsuhisa M, Kishimoto M, Ozaki H, Tani A, Ueda N, Ishida Y, Kamada T: Diurnal heart rate variability in healthy subjects: Effects of aging and sex difference. The American journal of physiology. 1996, 271 (1 Pt 2): H303-310.
5. Niskanen JP, Tarvainen MP, Ranta-Aho PO, Karjalainen PA: Software for advanced hrv analysis. Computer methods and programs in biomedicine. 2004, 76 (1): 73-81. 10.1016/j.cmpb.2004.03.004.
6. Tarvainen MP, Ranta-Aho PO, Karjalainen PA: An advanced detrending method with application to hrv analysis. IEEE transactions on bio-medical engineering. 2002, 49 (2): 172-175. 10.1109/10.979357.
7. Daskalov I, Christov I: Improvement of resolution in measurement of electrocardiogram rr intervals by interpolation. Medical engineering & physics. 1997, 19 (4): 375-379. 10.1016/S1350-4533(96)00067-7.
8. Mateo J, Laguna P: Improved heart rate variability signal analysis from the beat occurrence times according to the ipfm model. IEEE transactions on bio-medical engineering. 2000, 47 (8): 985-996. 10.1109/10.855925.
9. Electrophysiology TFotESoCtNASoP: Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Circulation. 1996, 93 (5): 1043-1065. 10.1161/01.CIR.93.5.1043.
10. Melillo P, Pecchia L, Ursino M: Nonlinear analysis research in biomedical engineering. Focus on nonlinear analysis research. 2013, Nova Science Publishers
11. Rajendra Acharya U, Paul Joseph K, Kannathal N, Lim CM, Suri JS: Heart rate variability: A review. Medical & biological engineering & computing. 2006, 44 (12): 1031-1051. 10.1007/s11517-006-0119-0.
12. Melillo P, Izzo R, De Luca N, Pecchia L: Heart rate variability and target organ damage in hypertensive patients. BMC Cardiovasc Disord. 2012, 12 (105)
13. Melillo P, Bracale M, Pecchia L: Nonlinear heart rate variability features for real-life stress detection. Case study: Students under stress due to university examination. Biomedical engineering online. 2011, 10 (1): 96-10.1186/1475-925X-10-96.
14. Melillo P, Izzo R, Orrico A, Scala P, Attanasio M, Mirra M, De Luca N, Pecchia L: Automatic prediction of cardiovascular and cerebrovascular events using heart rate variability analysis. PLoS ONE. 2015, 10 (3): e0118504-10.1371/journal.pone.0118504.
15. Naschitz JE, Rosner I: Orthostatic hypotension: Framework of the syndrome. Postgraduate medical journal. 2007, 83 (983): 568-574. 10.1136/pgmj.2007.058198.
16. Gibbons CH, Freeman R: Delayed orthostatic hypotension: A frequent cause of orthostatic intolerance. Neurology. 2006, 67 (1): 28-32. 10.1212/01.wnl.0000223828.28215.0b.
17. Huber PJ: Frontmatter. Robust statistics. 1981, John Wiley & Sons, Inc, i-xi.
18. Holland PW, Welsch RE: Robust regression using iteratively reweighted least-squares. Communications in Statistics-Theory and Methods. 1977, 6 (9): 813-827. 10.1080/03610927708827533.
19. Street JO, Carroll RJ, Ruppert D: A note on computing robust regression estimates via iteratively reweighted least squares. The American Statistician. 1988, 42 (2): 152-154.
20. Jain AK, Duin RPW, Jianchang M: Statistical pattern recognition: A review. Pattern Analysis and Machine Intelligence, IEEE Transactions. 2000, 22 (1): 4-37. 10.1109/34.824819.
21. Legua MP, Morales I, S LM, Ruiz n: The heaviside step function and matlab. Proceeding sof the international conference on Computational Science and Its Applications, Part I, Perugia, Italy. 2008, 1212-1221. Abs
22. Brennan M, Palaniswami M, Kamen P: Do existing measures of poincare plot geometry reflect nonlinear features of heart rate variability?. IEEE Trans Bio Med Eng. 2001, 48 (11): 1342-1347. 10.1109/10.959330.
23. Malik M, Bigger JT, Camm AJ, Kleiger RE, Malliani A, Moss AJ, Schwartz PJ: Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Eur Heart J. 1996, 17 (3): 354-381. 10.1093/oxfordjournals.eurheartj.a014868.
24. Mohr E, Langbein J, Nurnberg G: Heart rate variability: A noninvasive approach to measure stress in calves and cows. Physiol Behav. 2002, 75 (1-2): 251-259. 10.1016/S0031-9384(01)00651-5.
25. Vasudev A, O'Brien JT, Tan MP, Parry SW, Thomas AJ: A study of orthostatic hypotension, heart rate variability and baroreflex sensitivity in late-life depression. Journal of Affective Disorders. 2011, 131 (1-3): 374-378. 10.1016/j.jad.2010.11.001.
26. Barbic F, Perego F, Canesi M, Gianni M, Biagiotti S, Costantino G, Pezzoli G, Porta A, Malliani A, Furlan R: Early abnormalities of vascular and cardiac autonomic control in parkinson's disease without orthostatic hypotension. Hypertension. 2007, 49 (1): 120-126. 10.1161/01.HYP.0000250939.71343.7c.
27. Melillo P, Jovic A, De Luca N, Morgan S, Pecchia L: Automatic prediction of falls via heart rate variability and data mining in hypertensive patients: The share project experience.
28. Liu Y, Redmond SJ, Wang N, Blumenkron F, Narayanan MR, Lovell NH: Spectral analysis of accelerometry signals from a directed-routine for falls-risk estimation. Ieee T Bio-Med Eng. 2011, 58 (8)
29. Narayanan MR, Redmond SJ, Scalzi ME, Lord SR, Celler BG, Lovell NH: Longitudinal falls-risk estimation using triaxial accelerometry. Ieee T Bio-Med Eng. 2010, 57 (3): 534-541.
30. Greene BR, O'Donovan A, Romero-Ortuno R, Cogan L, Scanaill CN, Kenny RA: Quantitative falls risk assessment using the timed up and go test. Ieee T Bio-Med Eng. 2010, 57 (12): 2918-2926.
31. Mariani B, Rochat S, Buela CJ, Aminian K: Heel and toe clearance estimation for gait analysis using wireless inertial sensors. Ieee T Bio-Med Eng. 2012, 59 (11): 3162-3168.
32. Mirmahboub B, Samavi S, Karimi N, Shirani S: Automatic monocular system for human fall detection based on variations in silhouette area. Ieee T Bio-Med Eng. 2013, 60 (2): 427-436.
33. Li Y, Ho KC, Popescu M: Efficient source separation algorithms for acoustic fall detection using a microsoft kinect. Ieee T Bio-Med Eng. 2014, 61 (3): 745-755.
34. Li Y, Ho KC, Popescu M: A microphone array system for automatic fall detection. Ieee T Bio-Med Eng. 2012, 59 (5): 1291-1301.
35. Wang F, Skubic M, Rantz M, Cuddihy PE: Quantitative gait measurement with pulse-doppler radar for passive in-home gait assessment. IEEE transactions on bio-medical engineering. 2014, 61 (9): 2434-2443.
36. Zigel Y, Litvak D, Gannot I: A method for automatic fall detection of elderly people using floor vibrations and sound-proof of concept on human mimicking doll falls. Ieee T Bio-Med Eng. 2009, 56 (12): 2858-2867.
37. Ariani A, Redmond SJ, Chang D, Lovell NH: Simulated unobtrusive falls detection with multiple persons. Ieee T Bio-Med Eng. 2012, 59 (11): 3185-3196.
38. Kosse N, Brands K, Bauer J, Hortobagyi T, Lamoth C: Sensor technologies aiming at fall prevention in institutionalized old adults: A synthesis of current knowledge. International journal of medical informatics. 2013, 82 (9): 743-752. 10.1016/j.ijmedinf.2013.06.001.
39. Hamacher D, Singh NB, Van Dieen JH, Heller MO, Taylor WR: Kinematic measures for assessing gait stability in elderly individuals: A systematic review. Journal of the Royal Society, Interface / the Royal Society. 2011, 8 (65): 1682-1698. 10.1098/rsif.2011.0416.
40. Yang CC, Hsu YL: A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors-Basel. 2010, 10 (8): 7772-7788. 10.3390/s100807772.
41. Allet L, Knols RH, Shirato K, de Bruin ED: Wearable systems for monitoring mobility-related activities in chronic disease: A systematic review. Sensors-Basel. 2010, 10 (10): 9026-9052. 10.3390/s101009026.
42. Gates S, Smith LA, Fisher JD, Lamb SE: Systematic review of accuracy of screening instruments for predicting fall risk among independently living older adults. Journal of rehabilitation research and development. 2008, 45 (8): 1105-1116. 10.1682/JRRD.2008.04.0057.