<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03777267</url>
  </required_header>
  <id_info>
    <org_study_id>IRB00055280</org_study_id>
    <nct_id>NCT03777267</nct_id>
  </id_info>
  <brief_title>Cereset Research Exploratory Study</brief_title>
  <official_title>Cereset Research Exploratory Study</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Wake Forest University Health Sciences</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>The Susanne Marcus Collins Foundation, Inc</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Wake Forest University Health Sciences</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>Yes</is_fda_regulated_device>
    <is_unapproved_device>Yes</is_unapproved_device>
    <is_us_export>Yes</is_us_export>
  </oversight_info>
  <brief_summary>
    <textblock>
      The purpose of this study is to evaluate the use of Cereset Research to improve autonomic&#xD;
      function in participants with symptoms of stress, anxiety, or insomnia.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The primary objective of this open label exploratory study is to evaluate the effect of CR to&#xD;
      improve autonomic cardiovascular regulation in participants with symptoms of stress, anxiety,&#xD;
      or insomnia.&#xD;
&#xD;
      The secondary objective is to evaluate the effect of CR on a variety of self-reported symptom&#xD;
      inventories.&#xD;
&#xD;
      Tertiary objectives are to explore the impact of selected medications on outcomes associated&#xD;
      with use of CR, the effect size in subgroups of participants who also report specific&#xD;
      co-morbid symptoms or conditions of interest, and any unexpected challenges or barriers for&#xD;
      working with the same. The latter includes those with TBI, PTSD, hypertension, hot flashes,&#xD;
      chronic pain, or prior stroke.&#xD;
&#xD;
      Methods: This will be a single site, open label, pilot clinical trial, enrolling people aged&#xD;
      11 or older, who have self-reported symptoms of stress, anxiety, or insomnia, and meet a&#xD;
      threshold score on self-reported inventories. Up to 150 participants will be enrolled.&#xD;
      Participants will receive between 6 and 12 sessions of audible tones echoing current&#xD;
      brainwave activity (CR). Participants will continue their other current care throughout the&#xD;
      study. There will be pre- and post-intervention data collection of physiological outcomes&#xD;
      (BP, HR, and measures of autonomic cardiovascular regulation assessed by heart rate&#xD;
      variability and baroreflex sensitivity), which will alse serve as the primary outcome.&#xD;
      Secondary outcomes to be collected include symptom inventories for insomnia (Insomnia&#xD;
      Severity Index, ISI; Pittsburgh Sleep Quality Index, PSQI), depression (Center for&#xD;
      Epidemiological Studies- Depression Scale, CES-D), anxiety (Generalized Anxiety Disorder-7,&#xD;
      GAD-7), stress (Perceived Stress Scale, PSS), traumatic stress (PTSD Checklist for civilians,&#xD;
      PCL-C, or military, PCL-M), , and overall quality of life (QOLS). Other secondary outcome&#xD;
      inventories will be collected for physical activity (International Physical Activity&#xD;
      Questionnaire, IPAQ-SF), and physical activity satisfaction questions, as well. Participants&#xD;
      who also self-report having specific co-morbid symptoms or conditions of interest may&#xD;
      complete additional condition-specific outcome measures. All measures will be collected at an&#xD;
      enrollment visit (V1), and the intervention will begin 0-14 days thereafter. Mean contrasts&#xD;
      will be used to compare the changes in measures of autonomic cardiovascular regulation from&#xD;
      V1 to V3, the primary outcome, as well as for secondary outcomes. Linear mixed models, which&#xD;
      can accommodate within-subject correlations due to repeated assessments over time, will be&#xD;
      used to generate point estimates for effect size along with 95% confidence intervals.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Recruiting</overall_status>
  <start_date type="Actual">April 12, 2019</start_date>
  <completion_date type="Anticipated">January 2025</completion_date>
  <primary_completion_date type="Anticipated">January 2024</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <intervention_model_description>This will be a single site, open label, pilot clinical trial, enrolling people aged 11 or older, who have self-reported symptoms of stress, anxiety, or insomnia, and meet a threshold score on self-reported inventories. Up to 100 participants will be enrolled so as to gather pilot data that will help inform regarding effect size, and dosing to support future cohort-specific randomized trials. Participants will receive between 6 and 12 intervention sessions of Cereset Research consisting of audible tones echoing current brainwave activity.</intervention_model_description>
    <primary_purpose>Supportive Care</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Change in Heart Rate Variability</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>Heart rate variability is measured in the time domain as standard deviation of beat-to-beat interval (SDNN, milliseconds). For calculation of SDNN, the R-R intervals are visually inspected, and data considered as artifact is manually removed. Heart rate are acquired from 10 minute recordings of noninvasive finger arterial pressure measurements and ECG with participants lying quietly, supine. Systolic BP and beat to beat, RR intervals files generated via the data acquisition system (BIOPAC acquisition system and Acknowledge 4.2 software, Santa Barbara, CA), at 1000 Hz, are analyzed using Nevrokard BRS software (Nevrokard BRS, Medistar, Ljubljana, Slovenia). Analysis is conducted on the first complete 5-minute epoch that is considered to be acceptable for analysis.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Change in Baroreflex Sensitivity</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>BRS calculated by this method is based on quantification of sequences of at least three beats (n) in which SBP consecutively increases (UP sequence) or decreases (DOWN sequence), which are accompanied by changes in the same direction of the RRI of subsequent beats (n+1). The software scans the RRI and SBP records, identifies sequences, and calculates linear correlation between RRI and SBP for each sequence. The mean of all individual regression coefficients (slopes), a measure of sequence BRS, is calculated for Sequence UP, DOWN and ALL (ms/mmHg). Blood pressure and heart rate are acquired from 10 minute recordings of noninvasive finger arterial pressure measurements and ECG with participants lying quietly, supine. Systolic BP and beat to beat, RR intervals files generated via the data acquisition system (BIOPAC acquisition system and Acknowledge 4.2 software, Santa Barbara, CA), at 1000 Hz, are analyzed using Nevrokard BRS software (Nevrokard BRS, Medistar, Ljubljana, Slovenia).</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Change in Blood Pressure</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>BP measurements will be obtained using an automate oscillometric blood pressure device. Three samples will be obtained and the last two averaged to get the value that will be used as the reading for that visit.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Change in Blood Pressure Variability</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>Systolic BP and beat to beat, RR intervals (RRI) files generated via the data acquisition system (BIOPAC acquisition system and software, Santa Barbara, CA) at 1000 Hz are analyzed using Nevrokard SA-BRS software (by Nevrokard Kiauta, d.o.o., Izola, Slovenia) for measures BPV.Frequency Method. Power spectral densities of SBP and RRI oscillations are computed by 512 points Fast Fourier Transform (FFT) and integrated over specified frequency ranges (LF: 0.04-0.15 Hz; HF: 0.15-0.4 Hz).</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Change in Insomnia Severity Index (ISI)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>The severity of insomnia symptoms is measured using the ISI with each data collection visit. The ISI is a 7 question measure, with responses from 0-4 for each question, yielding scores ranging from 0-28. Higher scores indicate the strength of the insomnia severity.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in Pittsburgh Sleep Quality Index (PSQI)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>The PSQI is a 19 item inventory that assesses sleep quality over a 1-month time interval. Items are weighted on a 0-3 interval scale. A global PSQI score is calculated by totaling the seven component scores, providing an overall score ranging from 0 to 21, where lower scores denote a healthier sleep quality.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in Center for Epidemiologic Studies Depression Scale (CES-D)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>The CES-D is a 20-item survey assessing affective depressive symptomatology to screen for risk of depression. Scores range from 0-60, with a score of 16 commonly used as a clinically relevant cut-off. Higher scores indicate the presence of more symptomatology.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in Generalized Anxiety Disorder-7 (GAD-7)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>The GAD-7 is a seven item screening tool for anxiety that is widely used in primary care. Scores range from 0-21. A lower score denotes a lower level of anxiety.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in Perceived Stress Scale (PSS)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>The PSS is a ten-item psychological instrument for measuring the perception of stress. It is a measure of the degree to which situations in one's life are appraised as stressful. Scores range from 0-40. A lower score denotes a lower level of perceived stress.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in Quality of Life Scale (QOLS)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>The QOLS is a 16-item scale that was modified from a 15-item scale used in chronic disease patients. Topics include different components of daily life such as relationships, community engagement, personal fulfillment, and recreation. Each item is scaled from 1 to 7 and a sum score is calculated to represent higher levels of satisfaction in life (range is 16-112).</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in PTSD Checklist for Civilians (PCL-C)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>The PCL-C measures the American Psychiatric Association's Diagnostic and statistical manual of mental disorders (DSM-IV) Criteria B, C, &amp; D of PTSD symptoms based on traumatic life experience related to civilians. Seventeen items are rated on a Likert scale with a composite score range of 17 to 85. A score of 44 or higher correlates with probability of civilian-related PTSD.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in International Physical Activity Questionnaire (IPAQ-SF)</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>This is a four item questionnaire asking about physical activity in the last 7 days. Scores are calculated and categorized as low, moderate, or high. A higher score denotes more physical activity.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in HIRREM Physical Activity Satisfaction Questions</measure>
    <time_frame>Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)</time_frame>
    <description>This is a four item questionnaire asking about the participants level of satisfaction with their physical activity. Responses range from 0-6 for each question, yielding scores ranging from 0-24. Higher scores denote a higher level of satisfaction.</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Anticipated">150</enrollment>
  <condition>Neurological Diseases or Conditions</condition>
  <condition>Cardiovascular Conditions After Birth</condition>
  <condition>Psychophysiologic Disorders</condition>
  <arm_group>
    <arm_group_label>Experimental: Active CR</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>For this single arm, open label, exploratory trial this will be the intervention arm using active CR.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Active CR</intervention_name>
    <description>The upgraded platform for medical research using the HIRREM technology has been rebranded as Cereset Research® (CR). This system uses the same core technology and algorithms to echo brainwaves in real-time using audible tones, as with HIRREM. The CR system also includes 64-bit processing architecture for faster feedback, the use of 4 sensors, and the use of standard protocols (with flexibility regarding the length and sequencing of the standard protocols), all done with eyes closed. Four sensors are applied to the scalp at a time. However, only two sensors are actively echoing feedback. The software automatically switches from one sensor pair to the other when needed. This reduces the number of sensor placement changes needed, resulting in shorter session time and fewer interruptions.</description>
    <arm_group_label>Experimental: Active CR</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Subjects must have the ability to comply with basic instructions and be able to sit&#xD;
             still comfortably with the sensor leads attached&#xD;
&#xD;
          -  Subjects experiencing symptoms of stress, anxiety, or insomnia, who meet threshold&#xD;
             scores on one or more self-reported inventories for the same. This includes the&#xD;
             Insomnia Severity Index (ISI, ≥ 8), the Perceived Stress Index (PSS, ≥ 14), or the&#xD;
             Generalized Anxiety Disorder 7-item (GAD-7, ≥ 5) scale.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Unable, unwilling, or incompetent to provide informed consent/assent.&#xD;
&#xD;
          -  Physically unable to come to the study visits, or to sit comfortably in a chair for up&#xD;
             to 1.5 hours.&#xD;
&#xD;
          -  Severe hearing impairment (because the subject will be using ear buds during CR).&#xD;
&#xD;
          -  Anticipated and ongoing use of alcohol or recreational drugs.&#xD;
&#xD;
          -  Weight is over the chair limit (285 pounds).&#xD;
&#xD;
          -  Currently in another active intervention research study.&#xD;
&#xD;
          -  Prior use of HIRREM, Brainwave Optimization, Cereset, or a wearable configuration of&#xD;
             the same (B2, or B2v2).&#xD;
&#xD;
          -  Prior use of electroconvulsive therapy (ECT).&#xD;
&#xD;
          -  Prior use of transcranial magnetic stimulation (TMS), transcranial direct current&#xD;
             stimulation (TDCS), alpha stimulation, neurofeedback, biofeedback, or deep brain&#xD;
             stimulation (DBS) within one month before enrollment.&#xD;
&#xD;
          -  Known seizure disorder.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>11 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Charles Tegeler, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Wake Forest University Health Sciences</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Study Coordinator</last_name>
    <phone>336-716-9447</phone>
    <email>wfhirrem@wakehealth.edu</email>
  </overall_contact>
  <location>
    <facility>
      <name>Department of Neurology, Wake Forest School of Medicine</name>
      <address>
        <city>Winston-Salem</city>
        <state>North Carolina</state>
        <zip>27104</zip>
        <country>United States</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Study Coordinator</last_name>
      <phone>336-716-9447</phone>
      <email>wfhirrem@wakehealth.edu</email>
    </contact>
    <investigator>
      <last_name>Charles Tegeler, MD</last_name>
      <role>Principal Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <reference>
    <citation>Hale TS, Smalley SL, Walshaw PD, Hanada G, Macion J, McCracken JT, McGough JJ, Loo SK. Atypical EEG beta asymmetry in adults with ADHD. Neuropsychologia. 2010 Oct;48(12):3532-9. doi: 10.1016/j.neuropsychologia.2010.08.002. Epub 2010 Aug 10.</citation>
    <PMID>20705076</PMID>
  </reference>
  <reference>
    <citation>Hale TS, Smalley SL, Dang J, Hanada G, Macion J, McCracken JT, McGough JJ, Loo SK. ADHD familial loading and abnormal EEG alpha asymmetry in children with ADHD. J Psychiatr Res. 2010 Jul;44(9):605-15. doi: 10.1016/j.jpsychires.2009.11.012. Epub 2009 Dec 16.</citation>
    <PMID>20006344</PMID>
  </reference>
  <reference>
    <citation>Hale TS, Smalley SL, Hanada G, Macion J, McCracken JT, McGough JJ, Loo SK. Atypical alpha asymmetry in adults with ADHD. Neuropsychologia. 2009 Aug;47(10):2082-8. doi: 10.1016/j.neuropsychologia.2009.03.021. Epub 2009 Apr 5.</citation>
    <PMID>19467358</PMID>
  </reference>
  <reference>
    <citation>Lazarev VV, Pontes A, Mitrofanov AA, deAzevedo LC. Interhemispheric asymmetry in EEG photic driving coherence in childhood autism. Clin Neurophysiol. 2010 Feb;121(2):145-52. doi: 10.1016/j.clinph.2009.10.010. Epub 2009 Dec 1.</citation>
    <PMID>19951847</PMID>
  </reference>
  <reference>
    <citation>Stroganova TA, Nygren G, Tsetlin MM, Posikera IN, Gillberg C, Elam M, Orekhova EV. Abnormal EEG lateralization in boys with autism. Clin Neurophysiol. 2007 Aug;118(8):1842-54. doi: 10.1016/j.clinph.2007.05.005. Epub 2007 Jun 19.</citation>
    <PMID>17581774</PMID>
  </reference>
  <reference>
    <citation>Thibodeau R, Jorgensen RS, Kim S. Depression, anxiety, and resting frontal EEG asymmetry: a meta-analytic review. J Abnorm Psychol. 2006 Nov;115(4):715-29. doi: 10.1037/0021-843X.115.4.715.</citation>
    <PMID>17100529</PMID>
  </reference>
  <reference>
    <citation>Avram J, Baltes FR, Miclea M, Miu AC. Frontal EEG activation asymmetry reflects cognitive biases in anxiety: evidence from an emotional face Stroop task. Appl Psychophysiol Biofeedback. 2010 Dec;35(4):285-92. doi: 10.1007/s10484-010-9138-6.</citation>
    <PMID>20607389</PMID>
  </reference>
  <reference>
    <citation>Spironelli C, Penolazzi B, Angrilli A. Dysfunctional hemispheric asymmetry of theta and beta EEG activity during linguistic tasks in developmental dyslexia. Biol Psychol. 2008 Feb;77(2):123-31. doi: 10.1016/j.biopsycho.2007.09.009. Epub 2007 Oct 2.</citation>
    <PMID>17997211</PMID>
  </reference>
  <reference>
    <citation>Moscovitch DA, Santesso DL, Miskovic V, McCabe RE, Antony MM, Schmidt LA. Frontal EEG asymmetry and symptom response to cognitive behavioral therapy in patients with social anxiety disorder. Biol Psychol. 2011 Jul;87(3):379-85. doi: 10.1016/j.biopsycho.2011.04.009. Epub 2011 May 13.</citation>
    <PMID>21571033</PMID>
  </reference>
  <reference>
    <citation>Kemp AH, Griffiths K, Felmingham KL, Shankman SA, Drinkenburg W, Arns M, Clark CR, Bryant RA. Disorder specificity despite comorbidity: resting EEG alpha asymmetry in major depressive disorder and post-traumatic stress disorder. Biol Psychol. 2010 Oct;85(2):350-4. doi: 10.1016/j.biopsycho.2010.08.001. Epub 2010 Aug 11.</citation>
    <PMID>20708650</PMID>
  </reference>
  <reference>
    <citation>Rabe S, Beauducel A, Zollner T, Maercker A, Karl A. Regional brain electrical activity in posttraumatic stress disorder after motor vehicle accident. J Abnorm Psychol. 2006 Nov;115(4):687-98. doi: 10.1037/0021-843X.115.4.687.</citation>
    <PMID>17100526</PMID>
  </reference>
  <reference>
    <citation>Metzger LJ, Paige SR, Carson MA, Lasko NB, Paulus LA, Pitman RK, Orr SP. PTSD arousal and depression symptoms associated with increased right-sided parietal EEG asymmetry. J Abnorm Psychol. 2004 May;113(2):324-9. doi: 10.1037/0021-843X.113.2.324.</citation>
    <PMID>15122952</PMID>
  </reference>
  <reference>
    <citation>Marzano C, Ferrara M, Sforza E, De Gennaro L. Quantitative electroencephalogram (EEG) in insomnia: a new window on pathophysiological mechanisms. Curr Pharm Des. 2008;14(32):3446-55. doi: 10.2174/138161208786549326.</citation>
    <PMID>19075720</PMID>
  </reference>
  <reference>
    <citation>Wolynczyk-Gmaj D, Szelenberger W. Waking EEG in primary insomnia. Acta Neurobiol Exp (Wars). 2011;71(3):387-92.</citation>
    <PMID>22068747</PMID>
  </reference>
  <reference>
    <citation>Riemann D, Spiegelhalder K, Feige B, Voderholzer U, Berger M, Perlis M, Nissen C. The hyperarousal model of insomnia: a review of the concept and its evidence. Sleep Med Rev. 2010 Feb;14(1):19-31. doi: 10.1016/j.smrv.2009.04.002. Epub 2009 May 28.</citation>
    <PMID>19481481</PMID>
  </reference>
  <reference>
    <citation>Cohen H, Benjamin J, Geva AB, Matar MA, Kaplan Z, Kotler M. Autonomic dysregulation in panic disorder and in post-traumatic stress disorder: application of power spectrum analysis of heart rate variability at rest and in response to recollection of trauma or panic attacks. Psychiatry Res. 2000 Sep 25;96(1):1-13. doi: 10.1016/s0165-1781(00)00195-5.</citation>
    <PMID>10980322</PMID>
  </reference>
  <reference>
    <citation>Katz-Leurer M, Rotem H, Keren O, Meyer S. Heart rate and heart rate variability at rest and during exercise in boys who suffered a severe traumatic brain injury and typically-developed controls. Brain Inj. 2010 Feb;24(2):110-4. doi: 10.3109/02699050903508234.</citation>
    <PMID>20085448</PMID>
  </reference>
  <reference>
    <citation>Beckham JC, Taft CT, Vrana SR, Feldman ME, Barefoot JC, Moore SD, Mozley SL, Butterfield MI, Calhoun PS. Ambulatory monitoring and physical health report in Vietnam veterans with and without chronic posttraumatic stress disorder. J Trauma Stress. 2003 Aug;16(4):329-35. doi: 10.1023/A:1024457700599.</citation>
    <PMID>12895015</PMID>
  </reference>
  <reference>
    <citation>Spiegelhalder K, Fuchs L, Ladwig J, Kyle SD, Nissen C, Voderholzer U, Feige B, Riemann D. Heart rate and heart rate variability in subjectively reported insomnia. J Sleep Res. 2011 Mar;20(1 Pt 2):137-45. doi: 10.1111/j.1365-2869.2010.00863.x.</citation>
    <PMID>20626615</PMID>
  </reference>
  <reference>
    <citation>Tobaldini E, Nobili L, Strada S, Casali KR, Braghiroli A, Montano N. Heart rate variability in normal and pathological sleep. Front Physiol. 2013 Oct 16;4:294. doi: 10.3389/fphys.2013.00294.</citation>
    <PMID>24137133</PMID>
  </reference>
  <reference>
    <citation>Tsuji H, Larson MG, Venditti FJ Jr, Manders ES, Evans JC, Feldman CL, Levy D. Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study. Circulation. 1996 Dec 1;94(11):2850-5. doi: 10.1161/01.cir.94.11.2850.</citation>
    <PMID>8941112</PMID>
  </reference>
  <reference>
    <citation>Dekker JM, Schouten EG, Klootwijk P, Pool J, Swenne CA, Kromhout D. Heart rate variability from short electrocardiographic recordings predicts mortality from all causes in middle-aged and elderly men. The Zutphen Study. Am J Epidemiol. 1997 May 15;145(10):899-908. doi: 10.1093/oxfordjournals.aje.a009049.</citation>
    <PMID>9149661</PMID>
  </reference>
  <reference>
    <citation>Beauchaine TP, Thayer JF. Heart rate variability as a transdiagnostic biomarker of psychopathology. Int J Psychophysiol. 2015 Nov;98(2 Pt 2):338-350. doi: 10.1016/j.ijpsycho.2015.08.004. Epub 2015 Aug 11.</citation>
    <PMID>26272488</PMID>
  </reference>
  <reference>
    <citation>Lee EA, Bissett JK, Carter MA, Cowan PA, Pyne JM, Speck PM, Theus SA, Tolley EA. Preliminary findings of the relationship of lower heart rate variability with military sexual trauma and presumed posttraumatic stress disorder. J Trauma Stress. 2013 Apr;26(2):249-56. doi: 10.1002/jts.21797.</citation>
    <PMID>23568414</PMID>
  </reference>
  <reference>
    <citation>Shah AJ, Lampert R, Goldberg J, Veledar E, Bremner JD, Vaccarino V. Posttraumatic stress disorder and impaired autonomic modulation in male twins. Biol Psychiatry. 2013 Jun 1;73(11):1103-10. doi: 10.1016/j.biopsych.2013.01.019. Epub 2013 Feb 21.</citation>
    <PMID>23434412</PMID>
  </reference>
  <reference>
    <citation>Minassian A, Geyer MA, Baker DG, Nievergelt CM, O'Connor DT, Risbrough VB; Marine Resiliency Study Team. Heart rate variability characteristics in a large group of active-duty marines and relationship to posttraumatic stress. Psychosom Med. 2014 May;76(4):292-301. doi: 10.1097/PSY.0000000000000056.</citation>
    <PMID>24804881</PMID>
  </reference>
  <reference>
    <citation>Park J, Marvar PJ, Liao P, Kankam ML, Norrholm SD, Downey RM, McCullough SA, Le NA, Rothbaum BO. Baroreflex dysfunction and augmented sympathetic nerve responses during mental stress in veterans with post-traumatic stress disorder. J Physiol. 2017 Jul 15;595(14):4893-4908. doi: 10.1113/JP274269. Epub 2017 Jun 14.</citation>
    <PMID>28503726</PMID>
  </reference>
  <reference>
    <citation>Park JE, Lee JY, Kang SH, Choi JH, Kim TY, So HS, Yoon IY. Heart rate variability of chronic posttraumatic stress disorder in the Korean veterans. Psychiatry Res. 2017 Sep;255:72-77. doi: 10.1016/j.psychres.2017.05.011. Epub 2017 May 9.</citation>
    <PMID>28528244</PMID>
  </reference>
  <reference>
    <citation>Minassian A, Maihofer AX, Baker DG, Nievergelt CM, Geyer MA, Risbrough VB; Marine Resiliency Study Team. Association of Predeployment Heart Rate Variability With Risk of Postdeployment Posttraumatic Stress Disorder in Active-Duty Marines. JAMA Psychiatry. 2015 Oct;72(10):979-86. doi: 10.1001/jamapsychiatry.2015.0922.</citation>
    <PMID>26353072</PMID>
  </reference>
  <reference>
    <citation>Pyne JM, Constans JI, Wiederhold MD, Gibson DP, Kimbrell T, Kramer TL, Pitcock JA, Han X, Williams DK, Chartrand D, Gevirtz RN, Spira J, Wiederhold BK, McCraty R, McCune TR. Heart rate variability: Pre-deployment predictor of post-deployment PTSD symptoms. Biol Psychol. 2016 Dec;121(Pt A):91-98. doi: 10.1016/j.biopsycho.2016.10.008. Epub 2016 Oct 20.</citation>
    <PMID>27773678</PMID>
  </reference>
  <reference>
    <citation>Kleiger RE, Miller JP, Bigger JT Jr, Moss AJ. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol. 1987 Feb 1;59(4):256-62. doi: 10.1016/0002-9149(87)90795-8.</citation>
    <PMID>3812275</PMID>
  </reference>
  <reference>
    <citation>Carnethon MR, Golden SH, Folsom AR, Haskell W, Liao D. Prospective investigation of autonomic nervous system function and the development of type 2 diabetes: the Atherosclerosis Risk In Communities study, 1987-1998. Circulation. 2003 May 6;107(17):2190-5. doi: 10.1161/01.CIR.0000066324.74807.95. Epub 2003 Apr 14.</citation>
    <PMID>12695289</PMID>
  </reference>
  <reference>
    <citation>Chandra P, Sands RL, Gillespie BW, Levin NW, Kotanko P, Kiser M, Finkelstein F, Hinderliter A, Pop-Busui R, Rajagopalan S, Saran R. Predictors of heart rate variability and its prognostic significance in chronic kidney disease. Nephrol Dial Transplant. 2012 Feb;27(2):700-9. doi: 10.1093/ndt/gfr340. Epub 2011 Sep 12.</citation>
    <PMID>21765187</PMID>
  </reference>
  <reference>
    <citation>Marsac J. [Heart rate variability: a cardiometabolic risk marker with public health implications]. Bull Acad Natl Med. 2013 Jan;197(1):175-86. French.</citation>
    <PMID>24672989</PMID>
  </reference>
  <reference>
    <citation>Thayer JF, Hansen AL, Saus-Rose E, Johnsen BH. Heart rate variability, prefrontal neural function, and cognitive performance: the neurovisceral integration perspective on self-regulation, adaptation, and health. Ann Behav Med. 2009 Apr;37(2):141-53. doi: 10.1007/s12160-009-9101-z. Epub 2009 May 8.</citation>
    <PMID>19424767</PMID>
  </reference>
  <reference>
    <citation>Nolan RP, Jong P, Barry-Bianchi SM, Tanaka TH, Floras JS. Effects of drug, biobehavioral and exercise therapies on heart rate variability in coronary artery disease: a systematic review. Eur J Cardiovasc Prev Rehabil. 2008 Aug;15(4):386-96. doi: 10.1097/HJR.0b013e3283030a97.</citation>
    <PMID>18677161</PMID>
  </reference>
  <reference>
    <citation>Lee SW, Gerdes L, Tegeler CL, Shaltout HA, Tegeler CH. A bihemispheric autonomic model for traumatic stress effects on health and behavior. Front Psychol. 2014 Aug 1;5:843. doi: 10.3389/fpsyg.2014.00843. eCollection 2014.</citation>
    <PMID>25136325</PMID>
  </reference>
  <reference>
    <citation>Bellesi M, Riedner BA, Garcia-Molina GN, Cirelli C, Tononi G. Enhancement of sleep slow waves: underlying mechanisms and practical consequences. Front Syst Neurosci. 2014 Oct 28;8:208. doi: 10.3389/fnsys.2014.00208. eCollection 2014.</citation>
    <PMID>25389394</PMID>
  </reference>
  <reference>
    <citation>Gerdes L, Gerdes P, Lee SW, H Tegeler C. HIRREM: a noninvasive, allostatic methodology for relaxation and auto-calibration of neural oscillations. Brain Behav. 2013 Mar;3(2):193-205. doi: 10.1002/brb3.116. Epub 2013 Jan 14.</citation>
    <PMID>23532171</PMID>
  </reference>
  <reference>
    <citation>Sterling P. Allostasis: a model of predictive regulation. Physiol Behav. 2012 Apr 12;106(1):5-15. doi: 10.1016/j.physbeh.2011.06.004. Epub 2011 Jun 12.</citation>
    <PMID>21684297</PMID>
  </reference>
  <reference>
    <citation>Tegeler CH, Kumar SR, Conklin D, Lee SW, Gerdes L, Turner DP, Tegeler CL, C Fidali B, Houle TT. Open label, randomized, crossover pilot trial of high-resolution, relational, resonance-based, electroencephalic mirroring to relieve insomnia. Brain Behav. 2012 Nov;2(6):814-24. doi: 10.1002/brb3.101. Epub 2012 Oct 28.</citation>
    <PMID>23170244</PMID>
  </reference>
  <reference>
    <citation>Tegeler CH, Tegeler CL, Cook JF, Lee SW, Pajewski NM. Reduction in menopause-related symptoms associated with use of a noninvasive neurotechnology for autocalibration of neural oscillations. Menopause. 2015 Jun;22(6):650-5. doi: 10.1097/GME.0000000000000422.</citation>
    <PMID>25668305</PMID>
  </reference>
  <reference>
    <citation>Tegeler CH, Tegeler CL, Cook JF, Lee SW, Gerdes L, Shaltout HA, Miles CM, Simpson SL. A Preliminary Study of the Effectiveness of an Allostatic, Closed-Loop, Acoustic Stimulation Neurotechnology in the Treatment of Athletes with Persisting Post-concussion Symptoms. Sports Med Open. 2016 Dec;2(1):39. doi: 10.1186/s40798-016-0063-y. Epub 2016 Sep 14.</citation>
    <PMID>27747793</PMID>
  </reference>
  <reference>
    <citation>Tegeler CL, Gerdes L, Shaltout HA, Cook JF, Simpson SL, Lee SW, Tegeler CH. Successful use of closed-loop allostatic neurotechnology for post-traumatic stress symptoms in military personnel: self-reported and autonomic improvements. Mil Med Res. 2017 Dec 22;4(1):38. doi: 10.1186/s40779-017-0147-0.</citation>
    <PMID>29502530</PMID>
  </reference>
  <reference>
    <citation>Fortunato JE, Tegeler CL, Gerdes L, Lee SW, Pajewski NM, Franco ME, Cook JF, Shaltout HA, Tegeler CH. Use of an allostatic neurotechnology by adolescents with postural orthostatic tachycardia syndrome (POTS) is associated with improvements in heart rate variability and changes in temporal lobe electrical activity. Exp Brain Res. 2016 Mar;234(3):791-8. doi: 10.1007/s00221-015-4499-y. Epub 2015 Dec 8.</citation>
    <PMID>26645307</PMID>
  </reference>
  <reference>
    <citation>Tegeler CH, Shaltout HA, Tegeler CL, Gerdes L, Lee SW. Rightward dominance in temporal high-frequency electrical asymmetry corresponds to higher resting heart rate and lower baroreflex sensitivity in a heterogeneous population. Brain Behav. 2015 Jun;5(6):e00343. doi: 10.1002/brb3.343. Epub 2015 May 1.</citation>
    <PMID>26085968</PMID>
  </reference>
  <reference>
    <citation>Lee SW, Laurienti PJ, Burdette JH, Tegeler CL, Morgan AR, Simpson SL, Gerdes L, Tegeler CH. Functional Brain Network Changes Following Use of an Allostatic, Closed-Loop, Acoustic Stimulation Neurotechnology for Military-Related Traumatic Stress. J Neuroimaging. 2019 Jan;29(1):70-78. doi: 10.1111/jon.12571. Epub 2018 Oct 10.</citation>
    <PMID>30302866</PMID>
  </reference>
  <reference>
    <citation>Tegeler CL, Howard LJ, Schmidt KD, Cook JF, Kumar S, Simpson SL, Lee SW, Gerdes L, Tegeler CH. 0389 USE OF A CLOSED-LOOP ACOUSTIC STIMULATION NEUROTECHNOLOGY IMPROVES SYMPTOMS OF MODERATE TO SEVERE INSOMNIA: RESULTS OF A PLACEBO-CONTROLLED TRIAL. Sleep. 2017;40:A145-A.</citation>
  </reference>
  <reference>
    <citation>Shaltout HA, Tegeler CL, Lee SW, Tegeler CH. 0363 IN SUBJECTS WITH INSOMNIA, USE OF A CLOSED-LOOP ACOUSTIC STIMULATION NEUROTECHNOLOGY IMPROVES HEART RATE VARIABILITY AND BAROREFLEX SENSITIVITY: RESULTS OF A PLACEBO-CONTROLLED CLINICAL TRIAL. Sleep. 2017;40:A135-A</citation>
  </reference>
  <reference>
    <citation>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 Mar 1;93(5):1043-65. No abstract available.</citation>
    <PMID>8598068</PMID>
  </reference>
  <reference>
    <citation>Kaplan NM RB. Technique of blood pressure measurement in the diagnosis of hypertension. UpToDate. Barkris GL, Sheridan AM, eds. Waltham, MA; 2010.</citation>
  </reference>
  <reference>
    <citation>Bastien CH, Vallieres A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001 Jul;2(4):297-307. doi: 10.1016/s1389-9457(00)00065-4.</citation>
    <PMID>11438246</PMID>
  </reference>
  <reference>
    <citation>Morin CM, Belleville G, Belanger L, Ivers H. The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep. 2011 May 1;34(5):601-8. doi: 10.1093/sleep/34.5.601.</citation>
    <PMID>21532953</PMID>
  </reference>
  <reference>
    <citation>Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989 May;28(2):193-213. doi: 10.1016/0165-1781(89)90047-4.</citation>
    <PMID>2748771</PMID>
  </reference>
  <reference>
    <citation>Radloff LS. The CES-D Scale: A Self-Report Depression Scale for Research in the General Population. Applied Psychological Measurement. 1977;1:385-401.</citation>
  </reference>
  <reference>
    <citation>Smarr KL, Keefer AL. Measures of depression and depressive symptoms: Beck Depression Inventory-II (BDI-II), Center for Epidemiologic Studies Depression Scale (CES-D), Geriatric Depression Scale (GDS), Hospital Anxiety and Depression Scale (HADS), and Patient Health Questionnaire-9 (PHQ-9). Arthritis Care Res (Hoboken). 2011 Nov;63 Suppl 11:S454-66. doi: 10.1002/acr.20556. No abstract available.</citation>
    <PMID>22588766</PMID>
  </reference>
  <reference>
    <citation>Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006 May 22;166(10):1092-7. doi: 10.1001/archinte.166.10.1092.</citation>
    <PMID>16717171</PMID>
  </reference>
  <reference>
    <citation>FW W, BT L, DS H, JA H, TM K. The PTSD Checklist (PCL): Reliability, validity, and diagnostic utility. 9th Annual Meeting of the International Society for Traumatic Stress Studies. San Antonio, TX.</citation>
  </reference>
  <reference>
    <citation>Blanchard EB, Jones-Alexander J, Buckley TC, Forneris CA. Psychometric properties of the PTSD Checklist (PCL). Behav Res Ther. 1996 Aug;34(8):669-73. doi: 10.1016/0005-7967(96)00033-2.</citation>
    <PMID>8870294</PMID>
  </reference>
  <reference>
    <citation>Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983 Dec;24(4):385-96. No abstract available.</citation>
    <PMID>6668417</PMID>
  </reference>
  <reference>
    <citation>Offenbacher M, Sauer S, Kohls N, Waltz M, Schoeps P. Quality of life in patients with fibromyalgia: validation and psychometric properties of the German Quality of Life Scale (QOLS-G). Rheumatol Int. 2012 Oct;32(10):3243-52. doi: 10.1007/s00296-011-2184-4. Epub 2011 Oct 30.</citation>
    <PMID>22038277</PMID>
  </reference>
  <reference>
    <citation>Burckhardt CS, Anderson KL. The Quality of Life Scale (QOLS): reliability, validity, and utilization. Health Qual Life Outcomes. 2003 Oct 23;1:60. doi: 10.1186/1477-7525-1-60.</citation>
    <PMID>14613562</PMID>
  </reference>
  <reference>
    <citation>Burckhardt CS, Woods SL, Schultz AA, Ziebarth DM. Quality of life of adults with chronic illness: a psychometric study. Res Nurs Health. 1989 Dec;12(6):347-54. doi: 10.1002/nur.4770120604.</citation>
    <PMID>2602575</PMID>
  </reference>
  <reference>
    <citation>Lee PH, Macfarlane DJ, Lam TH, Stewart SM. Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act. 2011 Oct 21;8:115. doi: 10.1186/1479-5868-8-115.</citation>
    <PMID>22018588</PMID>
  </reference>
  <reference>
    <citation>Eckner JT, Kutcher JS, Richardson JK. Pilot evaluation of a novel clinical test of reaction time in national collegiate athletic association division I football players. J Athl Train. 2010 Jul-Aug;45(4):327-32. doi: 10.4085/1062-6050-45.4.327.</citation>
    <PMID>20617905</PMID>
  </reference>
  <reference>
    <citation>Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, Sayer AA. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011 Jul;40(4):423-9. doi: 10.1093/ageing/afr051. Epub 2011 May 30.</citation>
    <PMID>21624928</PMID>
  </reference>
  <reference>
    <citation>Bradley KA, Bush KR, Epler AJ, Dobie DJ, Davis TM, Sporleder JL, Maynard C, Burman ML, Kivlahan DR. Two brief alcohol-screening tests From the Alcohol Use Disorders Identification Test (AUDIT): validation in a female Veterans Affairs patient population. Arch Intern Med. 2003 Apr 14;163(7):821-9. doi: 10.1001/archinte.163.7.821.</citation>
    <PMID>12695273</PMID>
  </reference>
  <reference>
    <citation>Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998 Sep 14;158(16):1789-95. doi: 10.1001/archinte.158.16.1789.</citation>
    <PMID>9738608</PMID>
  </reference>
  <reference>
    <citation>Bradley KA, DeBenedetti AF, Volk RJ, Williams EC, Frank D, Kivlahan DR. AUDIT-C as a brief screen for alcohol misuse in primary care. Alcohol Clin Exp Res. 2007 Jul;31(7):1208-17. doi: 10.1111/j.1530-0277.2007.00403.x. Epub 2007 Apr 19.</citation>
    <PMID>17451397</PMID>
  </reference>
  <verification_date>October 2022</verification_date>
  <study_first_submitted>December 14, 2018</study_first_submitted>
  <study_first_submitted_qc>December 14, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 17, 2018</study_first_posted>
  <last_update_submitted>October 26, 2022</last_update_submitted>
  <last_update_submitted_qc>October 26, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">October 27, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Stress</keyword>
  <keyword>Neurotechnology</keyword>
  <keyword>Autonomic Dysregulation</keyword>
  <keyword>Hyperarousal</keyword>
  <keyword>Brain electrical activity</keyword>
  <keyword>Allostasis</keyword>
  <keyword>HIRREM</keyword>
  <keyword>Cereset Research</keyword>
  <keyword>Insomnia</keyword>
  <keyword>Anxiety</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Nervous System Diseases</mesh_term>
    <mesh_term>Disease</mesh_term>
    <mesh_term>Psychophysiologic Disorders</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03777267
org study id: IRB00055280
nct id: NCT03777267
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: Yes
is unapproved device: Yes
is us export: Yes
The purpose of this study is to evaluate the use of Cereset Research to improve autonomic
      function in participants with symptoms of stress, anxiety, or insomnia.
The primary objective of this open label exploratory study is to evaluate the effect of CR to
      improve autonomic cardiovascular regulation in participants with symptoms of stress, anxiety,
      or insomnia.

      The secondary objective is to evaluate the effect of CR on a variety of self-reported symptom
      inventories.

      Tertiary objectives are to explore the impact of selected medications on outcomes associated
      with use of CR, the effect size in subgroups of participants who also report specific
      co-morbid symptoms or conditions of interest, and any unexpected challenges or barriers for
      working with the same. The latter includes those with TBI, PTSD, hypertension, hot flashes,
      chronic pain, or prior stroke.

      Methods: This will be a single site, open label, pilot clinical trial, enrolling people aged
      11 or older, who have self-reported symptoms of stress, anxiety, or insomnia, and meet a
      threshold score on self-reported inventories. Up to 150 participants will be enrolled.
      Participants will receive between 6 and 12 sessions of audible tones echoing current
      brainwave activity (CR). Participants will continue their other current care throughout the
      study. There will be pre- and post-intervention data collection of physiological outcomes
      (BP, HR, and measures of autonomic cardiovascular regulation assessed by heart rate
      variability and baroreflex sensitivity), which will alse serve as the primary outcome.
      Secondary outcomes to be collected include symptom inventories for insomnia (Insomnia
      Severity Index, ISI; Pittsburgh Sleep Quality Index, PSQI), depression (Center for
      Epidemiological Studies- Depression Scale, CES-D), anxiety (Generalized Anxiety Disorder-7,
      GAD-7), stress (Perceived Stress Scale, PSS), traumatic stress (PTSD Checklist for civilians,
      PCL-C, or military, PCL-M), , and overall quality of life (QOLS). Other secondary outcome
      inventories will be collected for physical activity (International Physical Activity
      Questionnaire, IPAQ-SF), and physical activity satisfaction questions, as well. Participants
      who also self-report having specific co-morbid symptoms or conditions of interest may
      complete additional condition-specific outcome measures. All measures will be collected at an
      enrollment visit (V1), and the intervention will begin 0-14 days thereafter. Mean contrasts
      will be used to compare the changes in measures of autonomic cardiovascular regulation from
      V1 to V3, the primary outcome, as well as for secondary outcomes. Linear mixed models, which
      can accommodate within-subject correlations due to repeated assessments over time, will be
      used to generate point estimates for effect size along with 95% confidence intervals.
allocation: N/A
intervention model: Single Group Assignment
intervention model description: This will be a single site, open label, pilot clinical trial, enrolling people aged 11 or older, who have self-reported symptoms of stress, anxiety, or insomnia, and meet a threshold score on self-reported inventories. Up to 100 participants will be enrolled so as to gather pilot data that will help inform regarding effect size, and dosing to support future cohort-specific randomized trials. Participants will receive between 6 and 12 intervention sessions of Cereset Research consisting of audible tones echoing current brainwave activity.
primary purpose: Supportive Care
masking: None (Open Label)
measure: Change in Heart Rate Variability
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: Heart rate variability is measured in the time domain as standard deviation of beat-to-beat interval (SDNN, milliseconds). For calculation of SDNN, the R-R intervals are visually inspected, and data considered as artifact is manually removed. Heart rate are acquired from 10 minute recordings of noninvasive finger arterial pressure measurements and ECG with participants lying quietly, supine. Systolic BP and beat to beat, RR intervals files generated via the data acquisition system (BIOPAC acquisition system and Acknowledge 4.2 software, Santa Barbara, CA), at 1000 Hz, are analyzed using Nevrokard BRS software (Nevrokard BRS, Medistar, Ljubljana, Slovenia). Analysis is conducted on the first complete 5-minute epoch that is considered to be acceptable for analysis.
measure: Change in Baroreflex Sensitivity
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: BRS calculated by this method is based on quantification of sequences of at least three beats (n) in which SBP consecutively increases (UP sequence) or decreases (DOWN sequence), which are accompanied by changes in the same direction of the RRI of subsequent beats (n+1). The software scans the RRI and SBP records, identifies sequences, and calculates linear correlation between RRI and SBP for each sequence. The mean of all individual regression coefficients (slopes), a measure of sequence BRS, is calculated for Sequence UP, DOWN and ALL (ms/mmHg). Blood pressure and heart rate are acquired from 10 minute recordings of noninvasive finger arterial pressure measurements and ECG with participants lying quietly, supine. Systolic BP and beat to beat, RR intervals files generated via the data acquisition system (BIOPAC acquisition system and Acknowledge 4.2 software, Santa Barbara, CA), at 1000 Hz, are analyzed using Nevrokard BRS software (Nevrokard BRS, Medistar, Ljubljana, Slovenia).
measure: Change in Blood Pressure
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: BP measurements will be obtained using an automate oscillometric blood pressure device. Three samples will be obtained and the last two averaged to get the value that will be used as the reading for that visit.
measure: Change in Blood Pressure Variability
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: Systolic BP and beat to beat, RR intervals (RRI) files generated via the data acquisition system (BIOPAC acquisition system and software, Santa Barbara, CA) at 1000 Hz are analyzed using Nevrokard SA-BRS software (by Nevrokard Kiauta, d.o.o., Izola, Slovenia) for measures BPV.Frequency Method. Power spectral densities of SBP and RRI oscillations are computed by 512 points Fast Fourier Transform (FFT) and integrated over specified frequency ranges (LF: 0.04-0.15 Hz; HF: 0.15-0.4 Hz).
measure: Change in Insomnia Severity Index (ISI)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: The severity of insomnia symptoms is measured using the ISI with each data collection visit. The ISI is a 7 question measure, with responses from 0-4 for each question, yielding scores ranging from 0-28. Higher scores indicate the strength of the insomnia severity.
measure: Change in Pittsburgh Sleep Quality Index (PSQI)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: The PSQI is a 19 item inventory that assesses sleep quality over a 1-month time interval. Items are weighted on a 0-3 interval scale. A global PSQI score is calculated by totaling the seven component scores, providing an overall score ranging from 0 to 21, where lower scores denote a healthier sleep quality.
measure: Change in Center for Epidemiologic Studies Depression Scale (CES-D)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: The CES-D is a 20-item survey assessing affective depressive symptomatology to screen for risk of depression. Scores range from 0-60, with a score of 16 commonly used as a clinically relevant cut-off. Higher scores indicate the presence of more symptomatology.
measure: Change in Generalized Anxiety Disorder-7 (GAD-7)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: The GAD-7 is a seven item screening tool for anxiety that is widely used in primary care. Scores range from 0-21. A lower score denotes a lower level of anxiety.
measure: Change in Perceived Stress Scale (PSS)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: The PSS is a ten-item psychological instrument for measuring the perception of stress. It is a measure of the degree to which situations in one's life are appraised as stressful. Scores range from 0-40. A lower score denotes a lower level of perceived stress.
measure: Change in Quality of Life Scale (QOLS)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: The QOLS is a 16-item scale that was modified from a 15-item scale used in chronic disease patients. Topics include different components of daily life such as relationships, community engagement, personal fulfillment, and recreation. Each item is scaled from 1 to 7 and a sum score is calculated to represent higher levels of satisfaction in life (range is 16-112).
measure: Change in PTSD Checklist for Civilians (PCL-C)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: The PCL-C measures the American Psychiatric Association's Diagnostic and statistical manual of mental disorders (DSM-IV) Criteria B, C, & D of PTSD symptoms based on traumatic life experience related to civilians. Seventeen items are rated on a Likert scale with a composite score range of 17 to 85. A score of 44 or higher correlates with probability of civilian-related PTSD.
measure: Change in International Physical Activity Questionnaire (IPAQ-SF)
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: This is a four item questionnaire asking about physical activity in the last 7 days. Scores are calculated and categorized as low, moderate, or high. A higher score denotes more physical activity.
measure: Change in HIRREM Physical Activity Satisfaction Questions
time frame: Baseline, V2 (0-14 days after final session), and V3 (4-6 weeks after V2)
description: This is a four item questionnaire asking about the participants level of satisfaction with their physical activity. Responses range from 0-6 for each question, yielding scores ranging from 0-24. Higher scores denote a higher level of satisfaction.
arm group label: Experimental: Active CR
arm group type: Experimental
description: For this single arm, open label, exploratory trial this will be the intervention arm using active CR.
intervention type: Device
intervention name: Active CR
description: The upgraded platform for medical research using the HIRREM technology has been rebranded as Cereset Research® (CR). This system uses the same core technology and algorithms to echo brainwaves in real-time using audible tones, as with HIRREM. The CR system also includes 64-bit processing architecture for faster feedback, the use of 4 sensors, and the use of standard protocols (with flexibility regarding the length and sequencing of the standard protocols), all done with eyes closed. Four sensors are applied to the scalp at a time. However, only two sensors are actively echoing feedback. The software automatically switches from one sensor pair to the other when needed. This reduces the number of sensor placement changes needed, resulting in shorter session time and fewer interruptions.
arm group label: Experimental: Active CR
criteria: 
gender: All
minimum age: 11 Years
maximum age: N/A
healthy volunteers: No
last name: Charles Tegeler, MD
role: Principal Investigator
affiliation: Wake Forest University Health Sciences
last name: Study Coordinator
phone: 336-716-9447
email: wfhirrem@wakehealth.edu
facility: 
status: Recruiting
contact: 
investigator: 
country: United States
citation: Hale TS, Smalley SL, Walshaw PD, Hanada G, Macion J, McCracken JT, McGough JJ, Loo SK. Atypical EEG beta asymmetry in adults with ADHD. Neuropsychologia. 2010 Oct;48(12):3532-9. doi: 10.1016/j.neuropsychologia.2010.08.002. Epub 2010 Aug 10.
PMID: 20705076
citation: Hale TS, Smalley SL, Dang J, Hanada G, Macion J, McCracken JT, McGough JJ, Loo SK. ADHD familial loading and abnormal EEG alpha asymmetry in children with ADHD. J Psychiatr Res. 2010 Jul;44(9):605-15. doi: 10.1016/j.jpsychires.2009.11.012. Epub 2009 Dec 16.
PMID: 20006344
citation: Hale TS, Smalley SL, Hanada G, Macion J, McCracken JT, McGough JJ, Loo SK. Atypical alpha asymmetry in adults with ADHD. Neuropsychologia. 2009 Aug;47(10):2082-8. doi: 10.1016/j.neuropsychologia.2009.03.021. Epub 2009 Apr 5.
PMID: 19467358
citation: Lazarev VV, Pontes A, Mitrofanov AA, deAzevedo LC. Interhemispheric asymmetry in EEG photic driving coherence in childhood autism. Clin Neurophysiol. 2010 Feb;121(2):145-52. doi: 10.1016/j.clinph.2009.10.010. Epub 2009 Dec 1.
PMID: 19951847
citation: Stroganova TA, Nygren G, Tsetlin MM, Posikera IN, Gillberg C, Elam M, Orekhova EV. Abnormal EEG lateralization in boys with autism. Clin Neurophysiol. 2007 Aug;118(8):1842-54. doi: 10.1016/j.clinph.2007.05.005. Epub 2007 Jun 19.
PMID: 17581774
citation: Thibodeau R, Jorgensen RS, Kim S. Depression, anxiety, and resting frontal EEG asymmetry: a meta-analytic review. J Abnorm Psychol. 2006 Nov;115(4):715-29. doi: 10.1037/0021-843X.115.4.715.
PMID: 17100529
citation: Avram J, Baltes FR, Miclea M, Miu AC. Frontal EEG activation asymmetry reflects cognitive biases in anxiety: evidence from an emotional face Stroop task. Appl Psychophysiol Biofeedback. 2010 Dec;35(4):285-92. doi: 10.1007/s10484-010-9138-6.
PMID: 20607389
citation: Spironelli C, Penolazzi B, Angrilli A. Dysfunctional hemispheric asymmetry of theta and beta EEG activity during linguistic tasks in developmental dyslexia. Biol Psychol. 2008 Feb;77(2):123-31. doi: 10.1016/j.biopsycho.2007.09.009. Epub 2007 Oct 2.
PMID: 17997211
citation: Moscovitch DA, Santesso DL, Miskovic V, McCabe RE, Antony MM, Schmidt LA. Frontal EEG asymmetry and symptom response to cognitive behavioral therapy in patients with social anxiety disorder. Biol Psychol. 2011 Jul;87(3):379-85. doi: 10.1016/j.biopsycho.2011.04.009. Epub 2011 May 13.
PMID: 21571033
citation: Kemp AH, Griffiths K, Felmingham KL, Shankman SA, Drinkenburg W, Arns M, Clark CR, Bryant RA. Disorder specificity despite comorbidity: resting EEG alpha asymmetry in major depressive disorder and post-traumatic stress disorder. Biol Psychol. 2010 Oct;85(2):350-4. doi: 10.1016/j.biopsycho.2010.08.001. Epub 2010 Aug 11.
PMID: 20708650
citation: Rabe S, Beauducel A, Zollner T, Maercker A, Karl A. Regional brain electrical activity in posttraumatic stress disorder after motor vehicle accident. J Abnorm Psychol. 2006 Nov;115(4):687-98. doi: 10.1037/0021-843X.115.4.687.
PMID: 17100526
citation: Metzger LJ, Paige SR, Carson MA, Lasko NB, Paulus LA, Pitman RK, Orr SP. PTSD arousal and depression symptoms associated with increased right-sided parietal EEG asymmetry. J Abnorm Psychol. 2004 May;113(2):324-9. doi: 10.1037/0021-843X.113.2.324.
PMID: 15122952
citation: Marzano C, Ferrara M, Sforza E, De Gennaro L. Quantitative electroencephalogram (EEG) in insomnia: a new window on pathophysiological mechanisms. Curr Pharm Des. 2008;14(32):3446-55. doi: 10.2174/138161208786549326.
PMID: 19075720
citation: Wolynczyk-Gmaj D, Szelenberger W. Waking EEG in primary insomnia. Acta Neurobiol Exp (Wars). 2011;71(3):387-92.
PMID: 22068747
citation: Riemann D, Spiegelhalder K, Feige B, Voderholzer U, Berger M, Perlis M, Nissen C. The hyperarousal model of insomnia: a review of the concept and its evidence. Sleep Med Rev. 2010 Feb;14(1):19-31. doi: 10.1016/j.smrv.2009.04.002. Epub 2009 May 28.
PMID: 19481481
citation: Cohen H, Benjamin J, Geva AB, Matar MA, Kaplan Z, Kotler M. Autonomic dysregulation in panic disorder and in post-traumatic stress disorder: application of power spectrum analysis of heart rate variability at rest and in response to recollection of trauma or panic attacks. Psychiatry Res. 2000 Sep 25;96(1):1-13. doi: 10.1016/s0165-1781(00)00195-5.
PMID: 10980322
citation: Katz-Leurer M, Rotem H, Keren O, Meyer S. Heart rate and heart rate variability at rest and during exercise in boys who suffered a severe traumatic brain injury and typically-developed controls. Brain Inj. 2010 Feb;24(2):110-4. doi: 10.3109/02699050903508234.
PMID: 20085448
citation: Beckham JC, Taft CT, Vrana SR, Feldman ME, Barefoot JC, Moore SD, Mozley SL, Butterfield MI, Calhoun PS. Ambulatory monitoring and physical health report in Vietnam veterans with and without chronic posttraumatic stress disorder. J Trauma Stress. 2003 Aug;16(4):329-35. doi: 10.1023/A:1024457700599.
PMID: 12895015
citation: Spiegelhalder K, Fuchs L, Ladwig J, Kyle SD, Nissen C, Voderholzer U, Feige B, Riemann D. Heart rate and heart rate variability in subjectively reported insomnia. J Sleep Res. 2011 Mar;20(1 Pt 2):137-45. doi: 10.1111/j.1365-2869.2010.00863.x.
PMID: 20626615
citation: Tobaldini E, Nobili L, Strada S, Casali KR, Braghiroli A, Montano N. Heart rate variability in normal and pathological sleep. Front Physiol. 2013 Oct 16;4:294. doi: 10.3389/fphys.2013.00294.
PMID: 24137133
citation: Tsuji H, Larson MG, Venditti FJ Jr, Manders ES, Evans JC, Feldman CL, Levy D. Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study. Circulation. 1996 Dec 1;94(11):2850-5. doi: 10.1161/01.cir.94.11.2850.
PMID: 8941112
citation: Dekker JM, Schouten EG, Klootwijk P, Pool J, Swenne CA, Kromhout D. Heart rate variability from short electrocardiographic recordings predicts mortality from all causes in middle-aged and elderly men. The Zutphen Study. Am J Epidemiol. 1997 May 15;145(10):899-908. doi: 10.1093/oxfordjournals.aje.a009049.
PMID: 9149661
citation: Beauchaine TP, Thayer JF. Heart rate variability as a transdiagnostic biomarker of psychopathology. Int J Psychophysiol. 2015 Nov;98(2 Pt 2):338-350. doi: 10.1016/j.ijpsycho.2015.08.004. Epub 2015 Aug 11.
PMID: 26272488
citation: Lee EA, Bissett JK, Carter MA, Cowan PA, Pyne JM, Speck PM, Theus SA, Tolley EA. Preliminary findings of the relationship of lower heart rate variability with military sexual trauma and presumed posttraumatic stress disorder. J Trauma Stress. 2013 Apr;26(2):249-56. doi: 10.1002/jts.21797.
PMID: 23568414
citation: Shah AJ, Lampert R, Goldberg J, Veledar E, Bremner JD, Vaccarino V. Posttraumatic stress disorder and impaired autonomic modulation in male twins. Biol Psychiatry. 2013 Jun 1;73(11):1103-10. doi: 10.1016/j.biopsych.2013.01.019. Epub 2013 Feb 21.
PMID: 23434412
citation: Minassian A, Geyer MA, Baker DG, Nievergelt CM, O'Connor DT, Risbrough VB; Marine Resiliency Study Team. Heart rate variability characteristics in a large group of active-duty marines and relationship to posttraumatic stress. Psychosom Med. 2014 May;76(4):292-301. doi: 10.1097/PSY.0000000000000056.
PMID: 24804881
citation: Park J, Marvar PJ, Liao P, Kankam ML, Norrholm SD, Downey RM, McCullough SA, Le NA, Rothbaum BO. Baroreflex dysfunction and augmented sympathetic nerve responses during mental stress in veterans with post-traumatic stress disorder. J Physiol. 2017 Jul 15;595(14):4893-4908. doi: 10.1113/JP274269. Epub 2017 Jun 14.
PMID: 28503726
citation: Park JE, Lee JY, Kang SH, Choi JH, Kim TY, So HS, Yoon IY. Heart rate variability of chronic posttraumatic stress disorder in the Korean veterans. Psychiatry Res. 2017 Sep;255:72-77. doi: 10.1016/j.psychres.2017.05.011. Epub 2017 May 9.
PMID: 28528244
citation: Minassian A, Maihofer AX, Baker DG, Nievergelt CM, Geyer MA, Risbrough VB; Marine Resiliency Study Team. Association of Predeployment Heart Rate Variability With Risk of Postdeployment Posttraumatic Stress Disorder in Active-Duty Marines. JAMA Psychiatry. 2015 Oct;72(10):979-86. doi: 10.1001/jamapsychiatry.2015.0922.
PMID: 26353072
citation: Pyne JM, Constans JI, Wiederhold MD, Gibson DP, Kimbrell T, Kramer TL, Pitcock JA, Han X, Williams DK, Chartrand D, Gevirtz RN, Spira J, Wiederhold BK, McCraty R, McCune TR. Heart rate variability: Pre-deployment predictor of post-deployment PTSD symptoms. Biol Psychol. 2016 Dec;121(Pt A):91-98. doi: 10.1016/j.biopsycho.2016.10.008. Epub 2016 Oct 20.
PMID: 27773678
citation: Kleiger RE, Miller JP, Bigger JT Jr, Moss AJ. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol. 1987 Feb 1;59(4):256-62. doi: 10.1016/0002-9149(87)90795-8.
PMID: 3812275
citation: Carnethon MR, Golden SH, Folsom AR, Haskell W, Liao D. Prospective investigation of autonomic nervous system function and the development of type 2 diabetes: the Atherosclerosis Risk In Communities study, 1987-1998. Circulation. 2003 May 6;107(17):2190-5. doi: 10.1161/01.CIR.0000066324.74807.95. Epub 2003 Apr 14.
PMID: 12695289
citation: Chandra P, Sands RL, Gillespie BW, Levin NW, Kotanko P, Kiser M, Finkelstein F, Hinderliter A, Pop-Busui R, Rajagopalan S, Saran R. Predictors of heart rate variability and its prognostic significance in chronic kidney disease. Nephrol Dial Transplant. 2012 Feb;27(2):700-9. doi: 10.1093/ndt/gfr340. Epub 2011 Sep 12.
PMID: 21765187
citation: Marsac J. [Heart rate variability: a cardiometabolic risk marker with public health implications]. Bull Acad Natl Med. 2013 Jan;197(1):175-86. French.
PMID: 24672989
citation: Thayer JF, Hansen AL, Saus-Rose E, Johnsen BH. Heart rate variability, prefrontal neural function, and cognitive performance: the neurovisceral integration perspective on self-regulation, adaptation, and health. Ann Behav Med. 2009 Apr;37(2):141-53. doi: 10.1007/s12160-009-9101-z. Epub 2009 May 8.
PMID: 19424767
citation: Nolan RP, Jong P, Barry-Bianchi SM, Tanaka TH, Floras JS. Effects of drug, biobehavioral and exercise therapies on heart rate variability in coronary artery disease: a systematic review. Eur J Cardiovasc Prev Rehabil. 2008 Aug;15(4):386-96. doi: 10.1097/HJR.0b013e3283030a97.
PMID: 18677161
citation: Lee SW, Gerdes L, Tegeler CL, Shaltout HA, Tegeler CH. A bihemispheric autonomic model for traumatic stress effects on health and behavior. Front Psychol. 2014 Aug 1;5:843. doi: 10.3389/fpsyg.2014.00843. eCollection 2014.
PMID: 25136325
citation: Bellesi M, Riedner BA, Garcia-Molina GN, Cirelli C, Tononi G. Enhancement of sleep slow waves: underlying mechanisms and practical consequences. Front Syst Neurosci. 2014 Oct 28;8:208. doi: 10.3389/fnsys.2014.00208. eCollection 2014.
PMID: 25389394
citation: Gerdes L, Gerdes P, Lee SW, H Tegeler C. HIRREM: a noninvasive, allostatic methodology for relaxation and auto-calibration of neural oscillations. Brain Behav. 2013 Mar;3(2):193-205. doi: 10.1002/brb3.116. Epub 2013 Jan 14.
PMID: 23532171
citation: Sterling P. Allostasis: a model of predictive regulation. Physiol Behav. 2012 Apr 12;106(1):5-15. doi: 10.1016/j.physbeh.2011.06.004. Epub 2011 Jun 12.
PMID: 21684297
citation: Tegeler CH, Kumar SR, Conklin D, Lee SW, Gerdes L, Turner DP, Tegeler CL, C Fidali B, Houle TT. Open label, randomized, crossover pilot trial of high-resolution, relational, resonance-based, electroencephalic mirroring to relieve insomnia. Brain Behav. 2012 Nov;2(6):814-24. doi: 10.1002/brb3.101. Epub 2012 Oct 28.
PMID: 23170244
citation: Tegeler CH, Tegeler CL, Cook JF, Lee SW, Pajewski NM. Reduction in menopause-related symptoms associated with use of a noninvasive neurotechnology for autocalibration of neural oscillations. Menopause. 2015 Jun;22(6):650-5. doi: 10.1097/GME.0000000000000422.
PMID: 25668305
citation: Tegeler CH, Tegeler CL, Cook JF, Lee SW, Gerdes L, Shaltout HA, Miles CM, Simpson SL. A Preliminary Study of the Effectiveness of an Allostatic, Closed-Loop, Acoustic Stimulation Neurotechnology in the Treatment of Athletes with Persisting Post-concussion Symptoms. Sports Med Open. 2016 Dec;2(1):39. doi: 10.1186/s40798-016-0063-y. Epub 2016 Sep 14.
PMID: 27747793
citation: Tegeler CL, Gerdes L, Shaltout HA, Cook JF, Simpson SL, Lee SW, Tegeler CH. Successful use of closed-loop allostatic neurotechnology for post-traumatic stress symptoms in military personnel: self-reported and autonomic improvements. Mil Med Res. 2017 Dec 22;4(1):38. doi: 10.1186/s40779-017-0147-0.
PMID: 29502530
citation: Fortunato JE, Tegeler CL, Gerdes L, Lee SW, Pajewski NM, Franco ME, Cook JF, Shaltout HA, Tegeler CH. Use of an allostatic neurotechnology by adolescents with postural orthostatic tachycardia syndrome (POTS) is associated with improvements in heart rate variability and changes in temporal lobe electrical activity. Exp Brain Res. 2016 Mar;234(3):791-8. doi: 10.1007/s00221-015-4499-y. Epub 2015 Dec 8.
PMID: 26645307
citation: Tegeler CH, Shaltout HA, Tegeler CL, Gerdes L, Lee SW. Rightward dominance in temporal high-frequency electrical asymmetry corresponds to higher resting heart rate and lower baroreflex sensitivity in a heterogeneous population. Brain Behav. 2015 Jun;5(6):e00343. doi: 10.1002/brb3.343. Epub 2015 May 1.
PMID: 26085968
citation: Lee SW, Laurienti PJ, Burdette JH, Tegeler CL, Morgan AR, Simpson SL, Gerdes L, Tegeler CH. Functional Brain Network Changes Following Use of an Allostatic, Closed-Loop, Acoustic Stimulation Neurotechnology for Military-Related Traumatic Stress. J Neuroimaging. 2019 Jan;29(1):70-78. doi: 10.1111/jon.12571. Epub 2018 Oct 10.
PMID: 30302866
citation: Tegeler CL, Howard LJ, Schmidt KD, Cook JF, Kumar S, Simpson SL, Lee SW, Gerdes L, Tegeler CH. 0389 USE OF A CLOSED-LOOP ACOUSTIC STIMULATION NEUROTECHNOLOGY IMPROVES SYMPTOMS OF MODERATE TO SEVERE INSOMNIA: RESULTS OF A PLACEBO-CONTROLLED TRIAL. Sleep. 2017;40:A145-A.
citation: Shaltout HA, Tegeler CL, Lee SW, Tegeler CH. 0363 IN SUBJECTS WITH INSOMNIA, USE OF A CLOSED-LOOP ACOUSTIC STIMULATION NEUROTECHNOLOGY IMPROVES HEART RATE VARIABILITY AND BAROREFLEX SENSITIVITY: RESULTS OF A PLACEBO-CONTROLLED CLINICAL TRIAL. Sleep. 2017;40:A135-A
citation: 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 Mar 1;93(5):1043-65. No abstract available.
PMID: 8598068
citation: Kaplan NM RB. Technique of blood pressure measurement in the diagnosis of hypertension. UpToDate. Barkris GL, Sheridan AM, eds. Waltham, MA; 2010.
citation: Bastien CH, Vallieres A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001 Jul;2(4):297-307. doi: 10.1016/s1389-9457(00)00065-4.
PMID: 11438246
citation: Morin CM, Belleville G, Belanger L, Ivers H. The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep. 2011 May 1;34(5):601-8. doi: 10.1093/sleep/34.5.601.
PMID: 21532953
citation: Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989 May;28(2):193-213. doi: 10.1016/0165-1781(89)90047-4.
PMID: 2748771
citation: Radloff LS. The CES-D Scale: A Self-Report Depression Scale for Research in the General Population. Applied Psychological Measurement. 1977;1:385-401.
citation: Smarr KL, Keefer AL. Measures of depression and depressive symptoms: Beck Depression Inventory-II (BDI-II), Center for Epidemiologic Studies Depression Scale (CES-D), Geriatric Depression Scale (GDS), Hospital Anxiety and Depression Scale (HADS), and Patient Health Questionnaire-9 (PHQ-9). Arthritis Care Res (Hoboken). 2011 Nov;63 Suppl 11:S454-66. doi: 10.1002/acr.20556. No abstract available.
PMID: 22588766
citation: Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006 May 22;166(10):1092-7. doi: 10.1001/archinte.166.10.1092.
PMID: 16717171
citation: FW W, BT L, DS H, JA H, TM K. The PTSD Checklist (PCL): Reliability, validity, and diagnostic utility. 9th Annual Meeting of the International Society for Traumatic Stress Studies. San Antonio, TX.
citation: Blanchard EB, Jones-Alexander J, Buckley TC, Forneris CA. Psychometric properties of the PTSD Checklist (PCL). Behav Res Ther. 1996 Aug;34(8):669-73. doi: 10.1016/0005-7967(96)00033-2.
PMID: 8870294
citation: Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983 Dec;24(4):385-96. No abstract available.
PMID: 6668417
citation: Offenbacher M, Sauer S, Kohls N, Waltz M, Schoeps P. Quality of life in patients with fibromyalgia: validation and psychometric properties of the German Quality of Life Scale (QOLS-G). Rheumatol Int. 2012 Oct;32(10):3243-52. doi: 10.1007/s00296-011-2184-4. Epub 2011 Oct 30.
PMID: 22038277
citation: Burckhardt CS, Anderson KL. The Quality of Life Scale (QOLS): reliability, validity, and utilization. Health Qual Life Outcomes. 2003 Oct 23;1:60. doi: 10.1186/1477-7525-1-60.
PMID: 14613562
citation: Burckhardt CS, Woods SL, Schultz AA, Ziebarth DM. Quality of life of adults with chronic illness: a psychometric study. Res Nurs Health. 1989 Dec;12(6):347-54. doi: 10.1002/nur.4770120604.
PMID: 2602575
citation: Lee PH, Macfarlane DJ, Lam TH, Stewart SM. Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act. 2011 Oct 21;8:115. doi: 10.1186/1479-5868-8-115.
PMID: 22018588
citation: Eckner JT, Kutcher JS, Richardson JK. Pilot evaluation of a novel clinical test of reaction time in national collegiate athletic association division I football players. J Athl Train. 2010 Jul-Aug;45(4):327-32. doi: 10.4085/1062-6050-45.4.327.
PMID: 20617905
citation: Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, Sayer AA. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011 Jul;40(4):423-9. doi: 10.1093/ageing/afr051. Epub 2011 May 30.
PMID: 21624928
citation: Bradley KA, Bush KR, Epler AJ, Dobie DJ, Davis TM, Sporleder JL, Maynard C, Burman ML, Kivlahan DR. Two brief alcohol-screening tests From the Alcohol Use Disorders Identification Test (AUDIT): validation in a female Veterans Affairs patient population. Arch Intern Med. 2003 Apr 14;163(7):821-9. doi: 10.1001/archinte.163.7.821.
PMID: 12695273
citation: Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998 Sep 14;158(16):1789-95. doi: 10.1001/archinte.158.16.1789.
PMID: 9738608
citation: Bradley KA, DeBenedetti AF, Volk RJ, Williams EC, Frank D, Kivlahan DR. AUDIT-C as a brief screen for alcohol misuse in primary care. Alcohol Clin Exp Res. 2007 Jul;31(7):1208-17. doi: 10.1111/j.1530-0277.2007.00403.x. Epub 2007 Apr 19.
PMID: 17451397
responsible party type: Sponsor
mesh term: Nervous System Diseases
mesh term: Disease
mesh term: Psychophysiologic Disorders
sharing ipd: No