Process for detection of physical position of a human being

Details Process for detection of physical position of a human being Process for detection of physical position of a human being

1999-09-08

2001-10-23

Evanisko, George R. (Department: 3762)

Surgery: light, thermal, and electrical application

Light, thermal, and electrical application

Electrical therapeutic systems

C600S547000

Reexamination Certificate

active

06308098

ABSTRACT:

FIELD OF THE INVENTION
The invention concerns a process for the detection of the physical positions of a human being by evaluating the morphology of individual signals detected from a sympathetic/parasympathetic nerve system and the relationship of their spectral power densities, as well as an apparatus for performance of this process and an implantable cardiotherapy device containing such an apparatus.
BACKGROUND OF THE INVENTION
Rate-adaptive cardiac pacemakers are known which control the adaptive stimulation rate by the use of a comparison between the current sensor signal morphology and the morphology determined in the resting patient. Thus, for example, in the case of the “Inos” pacemaker of the applicant the respective current intracardial impedance curve is compared with a reference curve and the adaptive rate is determined from the integral difference. In the case of such pacemakers, it is important to keep the reference curve constantly current on the one hand, but on the other hand to only actually update it in the resting patient. For such an automatic updating of the reference curve, detection of the physical positions (standing or sitting or lying down) of the patient is desirable, since, within certain limits, the position detection also enables the detection of resting phases of the patient.
With rate-adaptive cardiac pacemakers, an additional problem may exist in that the signal morphology of a measured signal used for the rate adaptation exhibits great changes when the patient changes positions without the cause being capable of detection by a rate adaptation algorithm. This can result in paradoxical pacemaker behavior, such as a counterproductive drop in the stimulation rate when the patient stands up. A means of independent position detection would be of great utility, so that the rate adaptation algorithm could receive an additional input signal in order to be able to react properly to changes in position.
Of no less importance, is a determination of the proper time for an automatic night reduction in the stimulation rate by setting the time basis of the pacemaker independent of the influence of time zone changes or changing daily rhythm of the patient using the patient's actual lying down and resting phases; cf. PCT International Publication No. W091/08017.
Proposals have long been known to detect the physical position of patients using mercury or similar position-sensitive switches. However, because of various problems, to date, these have not proven to be effective in practice. In basic research, the heart rate variability in predefined low frequency (LF) intervals (0.05-0.15 Hz) and high frequency (HF) intervals (0.15-0.4 Hz) is used as an indicator of sympathovagal equilibrium which is affected by a change in position; cf. S. Akselrod et al. in “Hemodynamic Regulation: Investigation by Spectral Analysis”, Am. J. Physiol., 249, H 867-875 (1985). The process is not applicable in the particularly important and practical area of pacemaker patients since the variability of the heart rate in pacemaker patients is usually not available.
OBJECTS AND SUMMARY OF THE INVENTION
Consequently, the principal object of the invention is to report a reliable process, also suitable for pacemaker patients, for position detection of a human being and an apparatus for performance of this process.
The principal object of the present invention more specifically, relies on the relationship of spectral power densities in both the HF and the LF internals.
The invention includes the basic teaching of describing a process for position detection, termed orthostasis, a change between standing and lying, using the morphology of intracardial physiological sensor signals. The sensor signals which are dependent on sympathetic/parasympathetic nerve systems, are suitable for the purposes of the invention. In particular, hemodynamic signals, such as impedance or pressure, and electrical signals such as ventricular evoked response (VER) signals may also be used.
The process of the present invention extracts a specific signal parameter from the signal morphology of an individual heart cycle. This signal parameter is determined for a large number of heart cycles, and its beat by beat fluctuations are determined. The beat by beat fluctuations are subjected to a frequency analysis to obtain a spectral power density. The spectral power density represents a measure of the beat by beat variability of the signal parameter with specific variation frequencies. A high power density at a specific frequency indicates a high variability with this same variation frequency. In a standing patient, the relationship between high (between approximately 0.15 and 0.4 Hz) and low (between about 0.05 and 0.15 Hz) variation frequencies of signals under sympathetic/parasympathetic influence is low; in contrast, in a reclining patient, this relationship is high. Consequently, the spectral power density is, in each case, integrated over the high frequency range and the low frequency range in order to be able to determine the position of the patient from beat to beat from the relationship of the two intervals.
In a preferred embodiment, the beat by beat variability of the intracardial impedance signal is used for detection of position changes of a patient. For measurement of an impedance signal, preferably a high frequency alternating current pulse with an average current strength of 1.3 mA is fed in via a unipolar pacemaker electrode, and a voltage drop between an electrode point and a pacemaker housing is measured.
The slope of the impedance signal at a fixed point during a heart cycle is determined as a suitable parameter to construct the time series from a signal curve. Analogously to the above-mentioned analysis of heart rate variability, time-dependent frequency analyses of a time series of a slope parameter extracted from the impedance curve are performed, in particular. In order to investigate an entire frequency spectrum with time resolution, autoregressive spectral analysis is used (ARSA). A linear model is fitted to the measured time series of a parameter and the spectral power density is calculated from the coefficients. This occurs preferably at each point of the time series with an autoregressive model of order
20
. The calculated spectral power density is in each case integrated into the subdomains of lower frequencies (LF—blood pressure variability) and higher frequencies (HF—breath variability) and subsequently compared.


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S. Akselrod et al., “Hemodynamic Regulation: Investigation by Spectral Analysis” Am. J. Physiol. 1985, H867-H875.

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