• Users Online: 299
  • Print this page
  • Email this page


 
 
Table of Contents
ORIGINAL ARTICLE
Year : 2019  |  Volume : 33  |  Issue : 3  |  Page : 148-154

Respiratory sinus arrhythmia biofeedback therapy may increase heart rate variability activity and decrease reactivity in male patients with major depressive disorder: A pilot study


1 Department of Psychiatry, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation; School of Medicine, Tzu-Chi University, Hualien, Taiwan
2 National Defense Medical Center, School of Medicine; Department of Psychiatry, Hualien Armed Forces General Hospital, Hualien County, Taipei, Taiwan
3 Department of Nursing, College of Nursing and Health, Kang Ning University, Taipei, Taiwan
4 Special Education Resource Center, Hung Kuang University, Taichung City, Taiwan
5 Department of Mathematics, Tamkang University, New Taipei City, Taiwan

Date of Submission15-Jun-2019
Date of Decision21-Jul-2019
Date of Acceptance23-Jul-2019
Date of Web Publication30-Sep-2019

Correspondence Address:
Jia- Fu Lee
No. 289, Jianguo Road, Xindian District, New Taipei City 231
Taiwan
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/TPSY.TPSY_29_19

Rights and Permissions
  Abstract 


Objectives: Evidence suggests that depression is associated with a decreased trend of heart rate variability (HRV), which has been considered to be associated with unfavorable physical outcomes, and not resolved using various antidepressant medication treatments despite resolution of depression symptoms. In the present study, we intended to evaluate the effectiveness of HRV in respiratory sinus arrhythmia-biofeedback therapy (RSA-BT) on depression and HRV. Methods: We recruited 67 depressed male patients who received antidepressant or benzodiazepine treatments, received a psychological assessment, and were followed with a 3-week, 6-session RSA-BT. Results: After RSA-BT, HRV reactivity showed a significant mean decrease of 6.06 in low-frequency normal unit (p = 0.001) and 0.24 in the low-frequency/high-frequency (LF/HF) ratio (p < 0.05) and borderline but nonsignificant increase of 2.63 in HF normal unit (HFnu) during the stress task compared with those data at baseline (rest), indicating parasympathetic dominance during mental stress. At resting, post-RSA-BT showed a significant increase in LF, total power, variation (VAR), LFnu, and LF/HF (p = 0.001) and a significant decrease in HFnu (p = 0.001), indicating HRV activity increase and a shift autonomic nervous balance to sympathetic side compared to pre-RSA-BT data. Those patients also showed significant reductions in depression severity post-RSA-BT (p < 0.001) after controlling medication effect. Conclusion: The study results highlight the potential rôle of RSA-BT on the increased HRV activity with a shift sympathetic predominance at rest and decreased HRV reactivity toward parasympathetic dominance during mental stress in patients with depression, which is not related to the effects of antidepressant or benzodiazepine medication.

Keywords: biofeedback therapy, depression, respiratory sinus arrhythmia, treatment response


How to cite this article:
Lin CE, Chen LF, Chen CC, Chang HY, Chang YC, Lee JF. Respiratory sinus arrhythmia biofeedback therapy may increase heart rate variability activity and decrease reactivity in male patients with major depressive disorder: A pilot study. Taiwan J Psychiatry 2019;33:148-54

How to cite this URL:
Lin CE, Chen LF, Chen CC, Chang HY, Chang YC, Lee JF. Respiratory sinus arrhythmia biofeedback therapy may increase heart rate variability activity and decrease reactivity in male patients with major depressive disorder: A pilot study. Taiwan J Psychiatry [serial online] 2019 [cited 2019 Nov 21];33:148-54. Available from: http://www.e-tjp.org/text.asp?2019/33/3/148/268317




  Introduction Top


Respiratory sinus arrhythmia (RSA) is a rhythmical fluctuation in heartbeats in the respiratory frequency, characterized by shortened and lengthened heart periods in a phase relationship with inspiration and expiration, respectively [1]. Respiratory rate regulates the heart rate and blood pressure [2]. Fluctuations in the respiratory rate are directly correlated with those in the heart rate [2]. Fluctuations in heart rate are termed heart rate variability (HRV) [3]. Normal HRV is influenced through the autonomic nervous system, which regulates the heart rate through the sympathetic and parasympathetic nervous systems [4]. Low HRV is associated with excessive sympathetic modulation, inadequate parasympathetic modulation, or both [5].

Patients with depression have shown low HRV, which is found to be associated with unfavorable physical outcomes [6],[7],[8]. But low HRV cannot be treated with antidepressants, and depression may be associated with an increased sympathetic nervous system activity [9] and a decreased parasympathetic nervous system activity [7]. Furthermore, improved depression symptoms are associated with increased HRV [10],[11]. Liang et al. [12] have found a distinct contrary trend in the reactive HRV measures in male patients with depression. In patients with depression, the autonomic nervous system is shifted to sympathetic dominance at rest, but to parasympathetic dominance in response to stress [12]. Breathing at resonant frequency stimulates the baroreflex to produce a high-amplitude heart rate and blood pressure oscillation due to the resonance characteristics of the cardiovascular system [13]. The resonant frequency in humans is ranged between 0.075 and 0.120 Hz, which corresponds to 4–6 breaths/min [13]. The breathing at resonance frequency leads to an increased HRV.

RSA-biofeedback therapy (RSA-BT) is used to train individuals to learn how to control their breathing to reduce their respiratory rate to the resonant frequency at which the amplitude is maximized. RSA-BT has been tested as an adjuvant therapy in patients with posttraumatic stress disorder (PTSD) [14],[15]. The results indicated that RSA improves PTSD symptoms with a higher HRV than the control group. But scant research has focused on the treatment response to RSA-BT inpatients with depression.

In this study, we intended to test whether RSA-BT is an effective adjunctive therapy for depression outcomes and HRV. We hypothesized that at baseline, patients diagnosed with depression would have increased HRV activity or reactivity, and that RSA-BT could also improve depressive symptoms.


  Methods Top


Study participants

Participants were recruited from the inpatients of a Taiwanese psychiatric teaching hospital. The institutional review board approved the study protocol with the need of obtaining written informed consent from the study participants. This study only recruited male patients for reducing the gender confounding factor. The IBR project number BT101-01 of Tri-Service General Hospital, National Defense Medical Center was obtained approval on July 12, 2012.

Major depressive disorder (MDD) was diagnosed by board-certified psychiatrists through diagnostic interviews, according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Depression severity was assessed using the Chinese version of the Beck Depression Inventory (BDI)-II [16], to evaluate the improvement of inpatients' depressive symptoms after they received RSA-BT. Totally, 67 male inpatients diagnosed with MDD, aged 18 - 34 years, were recruited from our psychiatric hospital from June 1, 2012, to January 31, 2013. Those with comorbid anxiety were permitted to participate in the study if their main diagnosis was MDD. Participants already taking antidepressants or benzodiazepines were included only if the treatment had been ongoing and unchanged for at least three months. We excluded study patients who were taking any medications other than antidepressants or benzodiazepines. Excluded from the study were those with the presence of psychotic disorders, substance abuse, mental retardation, heart disease, as well as any unstable vital signs, such as hypoglycemia and hypotension. Following the orientation session, we gave participants initial psychological assessments, and a course of six RSA-BT sessions for three weeks (two sessions/week). Five-minute HRV measurements were taken before and after each of the six sessions, and measurements were also taken at rest and under mental stress for HRV reactivity. We measured patients' depression severity again with the BDI-II depression self-rating questionnaire three weeks later before HRV measurement. We asked the participants not to eat excessively, drink caffeine or alcohol, or exercise for four hours before HRV data collection.

Measures for heart rate variability

Power spectral analysis was done to obtain standard frequency-domain measurements, including low-frequency (LF: 0.04–0.15 Hz), high-frequency (HF: 0.15–0.40 Hz), HF power in normalized units (HFnu), LF power in normalized units (LFnu), and total power (TP). The time-domain parameters were variance and mean of the RR interval (VAR and MeanRR).

Beck's Depression Inventory-II for assessing depression severity

The Beck's Depression Inventory-II (BDI-II), a 21-item self-report instrument, is used to measure depression severity [17]. The BDI-II includes several questions related to the frequency and intensity of 21 depressive symptoms. The BDI-II contains four options for each item, ranging from 0 (not present) to 3 (severe). The instrument's original authors proposed the following rules for scoring severity: 0 - 13 indicates minimal or no depression; 14 - 19 indicates mild depression, 20 - 28 indicates moderate depression, and 29 - 63 indicates severe depression. The psychometric properties of the BDI-II are comprehensive. The coefficient alpha estimate of reliability for the BDI-II for outpatients is 0.92 (0.93 for the nonclinical sample) [17].

Heart rate variability-recording procedures in the resting and mental stress states

HRV analysis procedures have been previously detailed, and we have briefly summarized elsewhere [18]. Before measurement, the participants were instructed to refrain from alcohol and caffeine drinking for 24 hours as well as from smoking, exercising, and binge eating for at least 4 hours. All participants ate a standard breakfast on the day of the study to ensure standardized HRV recording. After the participants had rested for 15 min in a quiet, air-conditioned room, we recorded HRV for 5 min in the standardized conditions. The participants were asked to relax, breathe naturally, and move as little as possible. Immediately after HRV was recorded during a quiet rest, we asked the participants to watch videos featuring domestic violence, aiming at simulating real-life stress; subsequently, HRV was recorded again while the participants watched the stress-provoking videos. A recognized autonomic nervous system stressor paradigm can cause considerable HRV changes in those watching the stress-provoking videos [19]. Stress tasks are recognized as active, self-relevant stressors [20]. When the participants were asked to watch the videos featuring domestic violence, an experiment operator monitored the HRV results. The video lasted seven minutes, which is designated as the stress phase.

HF indicates parasympathetic nervous activity and is associated with respiratory activity [3],[21],[22], whereas LF indicates a combined sympathetic and parasympathetic nervous activity, occurring in synchrony with vasomotor waves [23],[24]. LFnu reflects the most close fluctuations in sympathetic tone [21],[25],[26]. The LF/HF ratio is a marker of sympathovagal balance [21],[25]. VAR varies inversely with the heart rate and directly with the interbeat interval [27],[28]. VAR is closely related to the absolute units of various power spectral components and probably reflects the level of overall autonomic and renin–angiotensin control of the heart rate [3]. We assessed RSA-BT with recording the blood volume pulse using an ambulatory HRV biofeedback device StressEraser ® (Helicor Inc., New York, USA) to provide an excellent estimate of the dynamic changes in heart rate and HRV. StressEraser ® is activated when participants insert their fingers into the pulse sensor [29],[30].

Study procedures

After obtaining informed consent, we asked all participants to complete a standard battery of measures, including the BDI-II and HRV assessments using spectral analysis (described in the measures paragraph) as pretests. Among the pretests, HRV assessment was repeated after watching the video on domestic violence to induce stress. Domestic violence videos have been selected because they induce psychological stress [31]. Subsequently, we gave the 67 participants with depression two sessions of 20-min RSA-BT per week for three weeks. In total, everyone received six sessions (120 min). The Lehrer's protocol has been referenced [32]. After the baseline HRV was obtained [32], participants' resonant frequency was determined using a pacer stimulus. To determine each participant's optimal resonant frequency, the pacer was set at various frequencies (e.g., 6.5, 6, 5.5, 5, and 4.5 breaths/min), and we asked the participants to breathe for 2 min. Breathing for 2 min enables computing the frequency spectra from at least 10 breaths at each frequency to determine personal resonant frequency. Heart rate oscillation amplitudes were measured, resulting in a series of highest-to-lowest frequency HRV. Subsequently, we asked the participants to continue breathing at their personal resonant frequency for 20 min to produce maximal increases in HRV amplitude. We asked the participants to breathe slowly and naturally, enabling exhalation to be longer than inhalation, thus preventing hyperventilation.

During the course of RSA-BT, five patients withdrew from the study, and the remaining 62 participants completed the six sessions of RSA-BT as scheduled. The 62 participants repeatedly received a standard battery of measures, including the BDI-II and HRV assessment, as posttests. Subsequently, we asked the participants to watch the domestic violence video again, and their HRV reactivity was assessed during stress.

Statistical analysis

To address the first hypothesis (i.e., patients diagnosed with depression have lower baseline HRV or HRV reactivity than those who have completed RSA-BT), we did a paired t-test to compare the baseline and post-treatment HRV-related variables, including the time-domain indexes MeanRR and VAR and the frequency-domain indexes TP, VLF, LF, HF, LFnu, HFnu, and LF/HF ratio. To address the second hypothesis (i.e., RSA-BT improves depression symptoms), we did a second paired t-test to compare the baseline and posttreatment BDI-II findings.

We used Statistical Package for Social Science software version 17 for Windows (SPSS, Inc., Chicago, Illinois, USA) to compute all the study data. The differences between the group were considered significant if p < 0.05.


  Results Top


All the 67 male participants were aged 18–34 years (mean age = 24.43 years, standard deviation = 3.43 years). The mean baseline heart rate at rest and after watching the domestic violence video was 70.77 ± 10.72 beats/min and 74.39 ± 15.56 beats/min, respectively. All the 67 patients received a three-week RSA-BT, and 41 of them also received antidepressant or benzodiazepines. None of the participants had any changes of psychotropic medications in the inpatient unit during the study period. The total BDI-II scores of the participants revealed statistically significant improvement (30.54 ± 14.12 vs. 23.47 ± 15.09, t = 4.26, p < 0.001) after a three week RSA-BT intervention.

Before administering RSA-BT, HRV reactivity demonstrated a significant mean decrease of 0.29 ms2 in LF (p < 0.01) and 0.21 ms2 in HF (p < 0.01, [Table 1]) during the period of mental stress compared with those data at baseline during the rest state. After RSA-BT, HRV reactivity showed a significant mean decrease of 6.06% in LFnu (p = 0.001) and 0.24 in the LF/HF ratio (p < 0.05, [Table 2]) during the period of mental stress compared with those data at baseline during the rest state.
Table 1: Heart rate variability reactivity before respiratory sinus arrhythmia-biofeedback therapy

Click here to view
Table 2: Heart rate variability reactivity after respiratory sinus arrhythmia-biofeedback therapy

Click here to view


At rest, the HRV activity exhibited a significant mean increase in LF (p < 0.001), LFnu (p < 0.001), LF/HF (p < 0.001), VAR (p < 0.001), and TP (p < 0.001) and a mean decrease in HFnu (p < 0.001) after 3 weeks' RSA-BT [Table 3]. During the stress task, the HRV activity demonstrated a significant mean increase in LFnu (p < 0.001), LF/HF ratio (p < 0.001), and VAR (p < 0.05) and a mean decrease in HFnu (p < 0.001) when compared the variables after RSA-BT with those of before RSA-BT [Table 4].
Table 3: Changes in heart rate variability measures after 3 weeks' respiratory sinus arrhythmia-biofeedback therapy at rest

Click here to view
Table 4: Changes in heart rate variability measures from prerespiratory sinus arrhythmia-biofeedback therapy to postrespiratory sinus arrhythmia-biofeedback therapy during stress

Click here to view



  Discussion Top


The results of this pilot study [Table 3] indicated that male inpatients with depression showed significantly higher LF (p < 0.001), TP (p < 0.001), VAR (p < 0.001), LFnu (p < 0.001), and LF/HF (p < 0.001) and significantly lower HFnu (p < 0.001) at rest after RSA-BT compared with the baseline HRV data before RSA-BT. The pilot study also examined the potential efficacy of RSA-BT as a depression treatment. Our findings indicated that male inpatients with depression who received six sessions (i.e., 120 min of treatment) of RSA-BT exhibited significant reductions in depression symptoms, according to the BDI-II measures. Notably, the HRV activity indicated significantly decreased HFnu and increased LFnu, LF, and LF/HF ratio after RSA-BT [Table 5], suggesting that increased sympathetic and autonomic nervous activity existed in male patients with depression after RSA-BT. In other words, our study results showed that patients with depression exhibited diminished HRV reactivity (decreased LF and HF) to the mental stressor before RSA-BT and subsequently exhibited more HRV activity with also increased sympathetic nervous activity in LFnu and LF/HF and decreased HF during mental stress after RSA-BT [Table 5].
Table 5: Comparisons of heart rate variability reactivity between prerespiratory sinus arrhythmia-biofeedback therapy and postrespiratory sinus arrhythmia-biofeedback therapy in depressive male patients, as well as of heart rate variability activity change from at resting to under mental stress state

Click here to view


Regarding HRV reactivity, the HRV measures revealed significantly increased MeanRR and decreased LF and HF before RSA-BT [Table 1] and [Table 5] and significantly decreased LFnu (p < 0.001) and LF/HF ratio (p < 0.001) after RSA-BT [Table 2] and [Table 5]. The results showed both decreased sympathetic and parasympathetic nervous activity (i.e., decreased LF and HF) in participants with depression during a mental stress task before RSA-BT. Thus, HRV reactivity may shift the sympathovagal balance to more parasympathetic activity for increased MeanRR in our patient population with depression. The reactive HRV pattern in our study is similar to Liang et al.'s finding [12] in decreased LF reactivity, but contrary to the HF reactivity during mental stress test. The reason of contrary trend in the HF reactivity during mental stress (Liang et al.'s study used serial 7 subtraction test, but our study employed watching domestic violence film mental stress test) for the two studies should be further verified in future. Shinba [33] investigated HRV reactivity during depressive episodes in a group of 22 unmedicated patients with depression and 47 matched controls. The investigator has discovered an increase in HF power and LF/HF ratio during a stress task [33], also suggesting an increased parasympathetic dominance in participants with depression during a stress task. After RSA-BT, although autonomic and sympathetic nervous activity was increased, it has still shown parasympathetic dominance during mental stress. This means although RSA-BT can improve HRV activity, the HRV reactivity (i.e., autonomic dysfunction in reactive HRV) has not been reversed successfully. But whether parasympathetic nervous activity is reduced in participants with depression remains unknown because the number of patients with depression was insufficient and the lack of a control group made drawing a conclusion in our and Shinba's [33] study difficult.

Our data suggest that RSA-BT is an effective adjuvant therapy for reducing depressive symptoms and increasing HRV activity. Confirming the efficacy of RSA-BT for improving depression symptoms is challenging because certain problems hindered our study. For instance, some of our patients were medicated using antidepressants and adjuvant benzodiazepines. Thus, the confounding effects of the treatment response related to antidepressant agents could not completely be excluded. But a large meta-analysis indicated that various antidepressant treatments do not resolve HRV decrease despite the resolution of depressive symptoms [34]. The effects of medicines on HRV were expected to be minimal in this study.

RSA-BT may play a key rôle for increased HRV activity, decreased LFnu, LF/HF reactivity, as well as improved depressive symptoms. Furthermore, ceasing therapy using antidepressants with proven efficacy to try a new nonpharmacological therapy of unknown efficacy, such as RSA-BT, is unethical. Therefore, our participants were permitted to continue to use their previously prescribed medicines.

The mechanism of RSA-BT on the treatment response in patients with MDD is not adequately understood. Our study extended that of Liang et al. [12] and used similar inclusion criteria to discover that depressed patients exhibited the same result of a decreasing trend in LF; conversely, it had also an decreasing trend in HF in response to stress. Through RSA-BT, our patients with depression exhibited consistently increased HRV activity in Var, LFnu, and LF/HF as well as decreased HFnu both at rest and during stress [Table 5]. Depressive symptoms may be improved by reversal of the decreased LF through RSA-BT related to increased autonomic function. LF activity showed decrease during stress before RSA-BT and increase in the rest state after RSA-BT [Table 5].

From another point of view, while testing the correlation between HRV change and BDI improvement, we observed a significant positive correlation between BDI score change and MeanRR interval change (r = 0.299, p < 0.05). When the BDI score was improved, the RR interval was also increased. In other words, the improvement of depression may be positively correlated to the increased parasympathetic function. Lehrer and Gevirtz [35] have supported the possible mechanism of RSA-BT for strengthening homeostasis in the baroreceptor. The effect on the vagal afferent pathway to the frontal cortical areas might explain the positive effects of RSA-BT.

We only included patients with MDD and no control group. Thus, residual factors, such as the use of medications and placebo effects, may have confounded the results. Additional effectively designed studies should be conducted to elucidate the treatment effects of RSA-BT on the relationship between depression and HRV.

All the 67 patients who participated in the study received a three-week RSA-BT, and 41 of them also received antidepressants or benzodiazepines for clinical need. None of the participants had changes of psychotropic medications in the inpatient unit during the study period. The total BDI-II scores of the participants revealed significantly improvement (30.54 ± 14.12 vs. 23.47 ± 15.09, t = 4.26, p < 0.001) after a three-week RSA-BT intervention. We defined the treatment responder as a ≧ 50% decrease from baseline depression scale scores to trial endpoint. The result showed 24.24% depressive cases belong to treatment responders. In all cases of RSABT treatment, we divided them into medication and nonmedication groups. No significant difference between the two groups both in BDI scores and HRV indices was found before and after RSA-BT. Therefore, we conclude that the effect of RSA-BT in the response rate of depression and HRV indices and HRV reactivity is not significantly affected by medication.

The study was only for (1) use of drugs (including antidepressant ± BZD), n = 41 (61.2%) and (0) unused drugs, n = 26 (38.8%). Therefore, the results show that although the control of the “drug use or not” variable does not affect the results of HRV activity or reactivity, it is a limitation to determine the effect of using BZD on HRV. Selection bias may exist in this study because the study sample was likely to be formed by convenience sampling. Multiple comparisons were carried out in the present analyses, which may lead to the type 1 error.

Study limitations

The readers are warned against overinterpreting the study findings because this study has the following three major limitations:

  • The major limitation of this study is of lacking a control group for comparing the between-group differences in reactive HRV. Thus, our results may be attributable to nonspecific factors, including passage of time and placebo factors. But we excluded potential confounding factors, such as illnesses and illicit drug use.
  • The generalizability of our results is limited because of the narrow inclusion criteria and only inpatient male patients were included in this study. Inpatients may have severe forms of depression than outpatients do. Furthermore, the presentation of HRV between men and women may differ [36].
  • Whether domestic violence video-induced stress mirrors real-life stress, which can be chronic, intermittent, and psychosocial in nature, is unclear.


Study summary

The study results highlight the potential rôle of RSA-BT on improved HRV reactivity in patients with depression which is not related to the effects of antidepressants.


  Acknowledgments Top


JFL contributed to study design and literature review and provided overall scientific supervision. CEL and LFC contributed to editing the manuscript. HYC contributed in data collection and writing the manuscript. CCC contributed to study design, supervised the assessment of the patients, and managed the literature searches. YCC did the statistical analysis and interpreted the results. All authors contributed to and approved the final manuscript.

The sponsorer of the study, Civilian Administration Division, had no further rôle in study design, data collection, analysis, and interpretation, as well as writing of the report and deciding where to submit the paper for publication. This manuscript was edited by Wallace Academic Editing.


  Financial Support And Sponsorship Top


Funding for this study was provided by Civilian Administration Division of Beitou Branch, Tri-Service General Hospital, National Defense Medical Center (BAFH-100-01).


  Conflicts Of Interest Top


All authors declare no conflicts of interest in writing this report.



 
  References Top

1.
Berntson GG, Bigger JT Jr., Eckberg DL, et al.: Heart rate variability: origins, methods, and interpretive caveats. Psychophysiology 1997; 34: 623-48.  Back to cited text no. 1
    
2.
Censi F, Calcagnini G, Cerutti S: Coupling patterns between spontaneous rhythms and respiration in cardiovascular variability signals. Comput Methods Programs Biomed 2002; 68: 37-47.  Back to cited text no. 2
    
3.
Akselrod S, Gordon D, Ubel FA, et al.: Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 1981; 213: 220-2.  Back to cited text no. 3
    
4.
Cohen H, Matar MA, Kaplan Z, et al.: Power spectral analysis of heart rate variability in psychiatry. Psychother Psychosom 1999; 68: 59-66.  Back to cited text no. 4
    
5.
Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 1996; 93: 1043-65.  Back to cited text no. 5
    
6.
Catipović-Veselica K, Galić A, Jelić K, et al.: Relation between major and minor depression and heart rate, heart-rate variability, and clinical characteristics of patients with acute coronary syndrome. Psychol Rep 2007; 100: 1245-54.  Back to cited text no. 6
    
7.
Rottenberg J, Clift A, Bolden S, et al.: RSA fluctuation in major depressive disorder. Psychophysiology 2007; 44: 450-8.  Back to cited text no. 7
    
8.
Siepmann M, Grossmann J, Mück-Weymann M, et al.: Effects of sertraline on autonomic and cognitive functions in healthy volunteers. Psychopharmacology (Berl) 2003; 168: 293-8.  Back to cited text no. 8
    
9.
Hughes JW, Watkins L, Blumenthal JA, et al.: Depression and anxiety symptoms are related to increased 24-hour urinary norepinephrine excretion among healthy middle-aged women. J Psychosom Res 2004; 57: 353-8.  Back to cited text no. 9
    
10.
Carney RM, Freedland KE, Stein PK, et al.: Change in heart rate and heart rate variability during treatment for depression in patients with coronary heart disease. Psychosom Med 2000; 62: 639-47.  Back to cited text no. 10
    
11.
Khaykin Y, Dorian P, Baker B, et al.: Autonomic correlates of antidepressant treatment using heart-rate variability analysis. Can J Psychiatry 1998; 43: 183-6.  Back to cited text no. 11
    
12.
Liang CS, Lee JF, Chen CC, et al.: Reactive heart rate variability in male patients with first-episode major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2015; 56: 52-7.  Back to cited text no. 12
    
13.
Vaschillo E, Lehrer P, Rishe N, et al.: Heart rate variability biofeedback as a method for assessing baroreflex function: a preliminary study of resonance in the cardiovascular system. Appl Psychophysiol Biofeedback 2002; 27: 1-27.  Back to cited text no. 13
    
14.
Tan G, Dao TK, Farmer L, et al.: Heart rate variability (HRV) and posttraumatic stress disorder (PTSD): a pilot study. Appl Psychophysiol Biofeedback 2011; 36: 27-35.  Back to cited text no. 14
    
15.
Zucker TL, Samuelson KW, Muench F, et al.: The effects of respiratory sinus arrhythmia biofeedback on heart rate variability and posttraumatic stress disorder symptoms: a pilot study. Appl Psychophysiol Biofeedback 2009; 34: 135-43.  Back to cited text no. 15
    
16.
Beck AT, Ward CH, Mendelson M, et al.: An inventory for measuring depression. Arch Gen Psychiatry 1961; 4: 561-71.  Back to cited text no. 16
    
17.
Beck AT, Steer RA, Brown GK: Manual for the Beck Depression Inventory-II. San Antonio, Texas, USA: Psychological Corporation, 1996.  Back to cited text no. 17
    
18.
Kuo TB, Lin T, Yang CC, et al.: Effect of aging on gender differences in neural control of heart rate. Am J Physiol 1999; 277: H2233-9.  Back to cited text no. 18
    
19.
Jern S, Pilhall M, Jern C, et al.: Short-term reproducibility of a mental arithmetic stress test. Clin Sci (Lond) 1991; 81: 593-601.  Back to cited text no. 19
    
20.
Schwerdtfeger A, Rosenkaimer AK. Depressive symptoms and attenuated physiological reactivity to laboratory stressors. Biol Psychol 2011; 87: 430-8.  Back to cited text no. 20
    
21.
Malliani A, Pagani M, Lombardi F, et al.: Cardiovascular neural regulation explored in the frequency domain. Circulation 1991; 84: 482-92.  Back to cited text no. 21
    
22.
Ori Z, Monir G, Weiss J, et al.: Heart rate variability. frequency domain analysis. Cardiol Clin 1992; 10: 499-537.  Back to cited text no. 22
    
23.
Koepchen HP, Hilton S, Trzebski A: Central Interaction between Respiratory and Cardiovascular Control Systems. Berlin, Germany: Springer Science and Business Media, 2012.  Back to cited text no. 23
    
24.
Draghici AE, Taylor JA. The physiological basis and measurement of heart rate variability in humans. J Physiol Anthropol 2016; 35: 22.  Back to cited text no. 24
    
25.
Pomeranz B, Macaulay RJ, Caudill MA, et al.: Assessment of autonomic function in humans by heart rate spectral analysis. J Physiol Anthrop 1985; 248: H151-3.  Back to cited text no. 25
    
26.
Rich MW, Saini JS, Kleiger RE, et al.: Correlation of heart rate variability with clinical and angiographic variables and late mortality after coronary angiography. Am J Cardiol 1988; 62: 714-7.  Back to cited text no. 26
    
27.
Rajendra Acharya U, Paul Joseph K, Kannathal N, et al.: Heart rate variability: a review. Med Biol Eng Comput 2006; 44: 1031-51.  Back to cited text no. 27
    
28.
Voss A, Baier V, Schulz S, et al: Linear and nonlinear methods for analyses of cardiovascular variability in bipolar disorders. Bipolar Disord 2006; 8: 441-52.  Back to cited text no. 28
    
29.
Ebben MR, Kurbatov V, Pollak CP: Moderating laboratory adaptation with the use of a heart-rate variability biofeedback device (StressEraser). Appl Psychophysiol Biofeedback 2009; 34: 245-9.  Back to cited text no. 29
    
30.
Heilman KJ, Handelman M, Lewis G, et al.: Accuracy of the StressEraser in the detection of cardiac rhythms. Appl Psychophysiol Biofeedback 2008; 33: 83-9.  Back to cited text no. 30
    
31.
Rottenberg J, Wilhelm FH, Gross JJ, et al.: Vagal rebound during resolution of tearful crying among depressed and nondepressed individuals. Psychophysiology 2003; 40: 1-6.  Back to cited text no. 31
    
32.
Lehrer PM, Vaschillo E, Vaschillo B: Resonant frequency biofeedback training to increase cardiac variability: rationale and manual for training. Appl Psychophysiol Biofeedback 2000; 25: 177-91.  Back to cited text no. 32
    
33.
Shinba T: Altered autonomic activity and reactivity in depression revealed by heart-rate variability measurement during rest and task conditions. Psychiatry Clin Neurosci 2014; 68: 225-33.  Back to cited text no. 33
    
34.
Kemp AH, Quintana DS, Gray MA, et al.: Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis. Biol Psychiatry 2010; 67: 1067-74.  Back to cited text no. 34
    
35.
Lehrer PM, Gevirtz R: Heart rate variability biofeedback: how and why does it work? Front Psychol 2014; 5: 756.  Back to cited text no. 35
    
36.
Liao D, Barnes RW, Chambless LE, et al.: Age, race, and sex differences in autonomic cardiac function measured by spectral analysis of heart rate variability – he ARIC study. Atherosclerosis risk in communities. Am J Cardiol 1995; 76: 906-12.  Back to cited text no. 36
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
   Abstract
  Introduction
  Methods
  Results
  Discussion
  Acknowledgments
   Financial Suppor...
   Conflicts Of Int...
   References
   Article Tables

 Article Access Statistics
    Viewed219    
    Printed11    
    Emailed0    
    PDF Downloaded27    
    Comments [Add]    

Recommend this journal