Improving accelerometer-based rate adaptive pacing by means of second-generation signal processing.

Abstract

Accelerometer-based rate adaptive pacing has gained widespread clinical use. Limitations exist for the distinction between walking upstairs and downstairs. It was the aim of this study to evaluate a new signal processing algorithm for more physiological rate adaptation. A custom-made pacemaker incorporating an accelerometer was randomly fixed to the left or right chest of 16 pacemaker patients (7 females, age: 64 +/- 11 years), 18 elderly study participants (6 females, age: 62 +/- 11 years), and 15 students (7 females age: 23 +/- 2 years). Study participants walked on level ground, upstairs and downstairs at five different step rates (72, 84, 96, 108, and 120 steps/min) controlled by an acoustic quartz metronome. The accelerometer signals, recorded on a portable data recorder, were analyzed with respect to frequency content, peak average of the mean acceleration, and morphology characteristics of the acceleration signal above and below zero baseline. By calculating the quotient of the signal's duration above and below zero baseline, a reliable discrimination between walking upstairs and downstairs was possible. A correction of the Leaky integrator signal by the new quotient yielded a more adequate rate adaptation to walking up and downstairs to represent at the patient's daily life activities. A more physiological rate adaptation can be achieved when using not only the accelerometer signal's amplitude, but applying additionally the morphology criterium of the acceleration signal's content in the positive and negative direction.