A provisional model to predict blood pressure response to biofeedback-assisted relaxation

Michael T. Weaver, Angele McGrady

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Blood pressure (BP) response to biofeedback-assisted relaxation is not uniform among hypertensive individuals. The purpose of this exploratory study was to determine if selected psychophysiological variables could be used to identify individuals able to lower blood pressure using biofeedback-assisted relaxation. Responders were defined using a preset criterion of 5 mm Hg or greater decrease in mean arterial pressure. A logistic regression model derived from five variables (heart rate, finger temperature, forehead muscle tension, plasma renin response to furosemide, and mean arterial pressure response to furosemide) provided significant predictive power for BP response, exhibiting a sensitivity of 84.6% and a specificity of 80.0%. With future validation, the proposed model may provide useful information to identify patients likely to benefit from biofeedback-assisted relaxation.

Original languageEnglish (US)
Pages (from-to)229-240
Number of pages12
JournalBiofeedback and Self-Regulation
Volume20
Issue number3
DOIs
StatePublished - Sep 1995
Externally publishedYes

Fingerprint

furosemide
blood pressure
Furosemide
Blood Pressure
renin
hypotension
Arterial Pressure
model validation
Logistic Models
heart rate
Muscle Tonus
Forehead
Renin
muscles
Fingers
Heart Rate
temperature
Temperature

Keywords

  • biofeedback
  • hypertension
  • prediction

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)

Cite this

A provisional model to predict blood pressure response to biofeedback-assisted relaxation. / Weaver, Michael T.; McGrady, Angele.

In: Biofeedback and Self-Regulation, Vol. 20, No. 3, 09.1995, p. 229-240.

Research output: Contribution to journalArticle

Weaver, Michael T. ; McGrady, Angele. / A provisional model to predict blood pressure response to biofeedback-assisted relaxation. In: Biofeedback and Self-Regulation. 1995 ; Vol. 20, No. 3. pp. 229-240.
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