Daniel Krauß

Advisors
Robert Richer (M. Sc.), Martin Ullrich (M. Sc.), Prof. Dr. med. Jochen Klucken, Prof. Dr. Björn Eskofier

Duration
09/2018 – 01/2019

Abstract
The measurement of heart rate variability (HRV) changes is commonly used for early detection of autonomic disorders [1]. One prominent example for such a disorder is Parkinson’s Disease (PD). It does not only affect the motor system, but also causes autonomic failures in blood pressure and heart rate regulation, leading to orthostatic dysregulation [2, 3].

To receive valuable information, it is of particular importance to combine HRV measurement with contextual information on posture changes, e.g. changes from lying to sitting or standing. Under these situations, the autonomic nervous system regulates the cardiovascular system mostly to prevent dizziness and impairment of consciousness [2, 4].

A common procedure for the assessment of an orthostatic dysregulation is the tilt table test, where a patient lies on a special table that creates a posture change from lying to standing [5, 6]. However, the procedure is performed in a clinical environment, possibly influencing the patients’ physiology (also referred to as white-coat syndrome [7]). Therefore, HRV analysis should be performed in a natural home environment using unobtrusive measurement techniques to increase the quality of results [7].

The goal of this bachelor’s thesis is therefore to develop a system for home monitoring based on a chest-worn ECG strap and an Android-based application [2]. It should replace clinical tilt table testing by triggering an HRV analysis after automatically detecting posture changes between lying, sitting and standing. HRV parameters are computed from the ECG chest strap. The main focus of this thesis however will lie on the selection of those posture change events out of all events recorded throughout the day which are suitable for a valid HRV analysis. Therefore, heuristic rules to reject non-suitable events, like high activity after posture change, or not remaining in one posture for a sufficient period of time, is significant.

 

Full Thesis

 

References:

1. Camm, A. John, et al. “Heart rate variability. Standards of measurement, physiological interpretation, and clinical use.” European heart journal 17.3 (1996): 354-381.
2. Richer, Robert, et al. “Unobtrusive real-time heart rate variability analysis for the detection of orthostatic dysregulation.” 2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN). IEEE, 2016.
3. Mihci, E., et al. “Orthostatic heart rate variability analysis in idiopathic Parkinson’s disease.” Acta neurologica scandinavica 113.5 (2006): 288-293.
4. Haapaniemi, T. H., et al. “Ambulatory ECG and analysis of heart rate variability in Parkinson’s disease.” Journal of neurology, neurosurgery & psychiatry 70.3 (2001): 305-310.
5. Benditt, David G., et al. “Tilt table testing for assessing syncope.” Journal of the American College of Cardiology 28.1 (1996): 263-275.
6. Lamarre-Cliche, Maxime, and Jean Cusson. “The fainting patient: value of the head-upright tilt-table test in adult patients with orthostatic intolerance.” Canadian Medical Association Journal 164.3 (2001): 372-376.
7. Owens, Patrick, Neil Atkins, and Eoin O’Brien. “Diagnosis of white coat hypertension by ambulatory blood pressure monitoring.” Hypertension 34.2 (1999): 267-272.