Changes in Heart Rate in Response to Cold Pressor Test (HRVW1)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT00678262
Recruitment Status : Completed
First Posted : May 15, 2008
Last Update Posted : September 21, 2010
Information provided by:
Soroka University Medical Center

Brief Summary:


Pain, a subjective sensation, has been increasingly studied, as it has been recognized as an important factor in patients' recovery and quality of life. Pain is charted today as one of the vital signs. For standardization, pain is charted by a number from 0 to 10 indicating its level. The most common practiced pain assessment tool today is the VAS- Visual Analog Score (facial or numerical), by which the patient himself indicates the level of the pain he or she endures. It has been found that the correlation between the reported pain by the patient and the assessed pain by the caregivers or the medical personnel becomes poor as pain intensifies.

Objective assessment of anesthesia using the heart rate and its spectral analyses was done in the past. By using this modality, works on neonatal pain were conducted. In adults, works have shown that there is possibility to assess pain using this modality, though no repeated proof for its ability to detect pain was published.

We know that physiological signals such as ECG consist of mixtures of variety of patterns and phenomena accruing at different patterns and time points. Traditional analysis methods are designed and optimized to handle signals that include a single class of patterns such as pure harmonics or piece-wise constant functions. However, such basic operations that use a single representation method usually yield mediocre results when applied to real complex biological signals as ECG and EEG especially in the case where the Signal to Noise Ratio (SNR) is very low. Recent trends in digital signal processing (DSP) use the novel idea of merging several different representation methods to create a so called over-complete dictionary, examples of this approach include the Matching Pursuit algorithm and the Basis Pursuit algorithm. We intend to develop and apply the novel signal processing tools to the ECG signals during painful experience for the first time. We believe that such tools have the potential to provide much better insight of the signal basic components and their relation to pain.

Condition or disease

  Show Detailed Description

Study Type : Observational
Estimated Enrollment : 20 participants
Observational Model: Case Control
Time Perspective: Prospective
Official Title: Changes in Heart Rate in Response to Cold Pressor Test
Study Start Date : May 2008
Actual Primary Completion Date : October 2008
Study Completion Date : October 2008

Information from the National Library of Medicine

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Ages Eligible for Study:   20 Years to 40 Years   (Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
healthy volunteers

Inclusion Criteria:

  • healthy volunteers age 20-40

Exclusion Criteria:

  • Heart diseases Hypertension Cardiovascular medication Neurological diseases

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT00678262

Soroka University Medical Center
Beer-Sheva, Negev, Israel
Sponsors and Collaborators
Soroka University Medical Center
Principal Investigator: Zvia Rudich, MD Soroka UMC

Responsible Party: Zvia Rudich MD, Soroka Medical Center Beer-Sheva, Israel Identifier: NCT00678262     History of Changes
Other Study ID Numbers: SOR470008CTIL
First Posted: May 15, 2008    Key Record Dates
Last Update Posted: September 21, 2010
Last Verified: September 2010

Keywords provided by Soroka University Medical Center:
Heart rate variability