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Usefulness and Adequacy of Sensor Data Storage and Retrieval for Rate Response Simulation
Author(s) -
MAHAUX VERONIQUE,
WALEFFE ANDRE,
KULBERTUS HENRI
Publication year - 1992
Publication title -
pacing and clinical electrophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.686
H-Index - 101
eISSN - 1540-8159
pISSN - 0147-8389
DOI - 10.1111/j.1540-8159.1992.tb02956.x
Subject(s) - medicine , predictive value , lead (geology) , simulation , regression analysis , linear regression , acceleration , cardiology , statistics , mathematics , computer science , geomorphology , geology , physics , classical mechanics
The usefulness of sensor data storage for rate response simulation was evaluated using a new dual chamber rate modulated pacemaker sensitive to acceleration forces (Relay 294–03 [lntermedics Inc.]). The pacemaker can store the sensor output during routine exercise and those values can be used to simulate rate profiles for other rate response settings. The predictive value of this feature was evaluated in three studies (mechanical, external pacemaker, and implanted pacemaker). In the first study, the pacemaker was submitted to three runs of eight different mechanical calibrated to‐and‐fro movements. In the second study, nine external pacemakers were strapped on healthy volunteers who performed three jogging tests. Finally, the predictive value of the simulation was studied in five implanted patients during three successive walking tests. In each study, the pacemaker was submitted three times to the same activity. The responsiveness was successively set to 5, 1, and 10, and the pacemaker outputs were continuously recorded on a Holter monitor. At the end of the first run, rate profile simulations for slopes 1 and 10 were performed; slope 5 rate response was simulated after the second run. A regression analysis was used to establish the correlation between predicted and achieved pacing rates for each study. The coefficients of correlation between predicted and measured pacing rates for the mechanical, external, and clinical studies were 0.999, 0.985, and 0.823, respectively. The corresponding slopes of regression lines were 1.005, 0.971, and 0.935. Calculated rate profile has a high predictive value and could be used to optimize rate responsive settings without serial exercise testings.

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