Mikko Peltokangas

Night-Time EKG and HRV Monitoring With Bed Sheet Integrated Textile Electrodes

A system for unobtrusive night-time electrocardiogram (EKG) and heart rate variability (HRV) monitoring as well as data analysis methods are presented, comparing bed sheet HR and HRV values with corresponding parameters obtained by a reference measurement. Our system uses eight embroidered textile electrodes attached laterally to a bed sheet for measuring bipolar contact EKG from multiple channels. The electrodes are arranged in a line so that at least two adjacent electrodes make sufficient skin contact. The focus of the signal processing development has been on selecting the best measurement channel for further analysis and minimizing the amount of incorrectly detected R-peaks. The test measurements were performed with four healthy men without previously known cardiac disorders and one who frequently had premature ventricular contractions (ectopic beats). For healthy test subjects, an average of 94.9% heartbeat detection coverage was achieved with the system during 29 measurement nights (in total 213.8 h of data). In most cases, the quality of the signal obtained from bed sheet electrodes is good enough for the computer-assisted cardiac arrhythmia detection. Applications for EKG derived RR-interval data include the calculation of HRV parameters that can be utilized in sleep quality analysis and other wellness-related topics as well as sleep apnoea detection.

Comparison of HRV parameters derived from photoplethysmography and electrocardiography signals

Heart rate variability (HRV) has become a useful tool in analysis of cardiovascular system in both research and clinical fields. HRV has been also used in other applications such as stress level estimation in wearable devices. HRV is normally obtained from ECG as the time interval of two successive R waves. Recently PPG has been proposed as an alternative for ECG in HRV analysis to overcome some difficulties in measurement of ECG. In addition, PPG-HRV is also used in some commercial devices such as modern optical wrist-worn heart rate monitors. However, some researches have shown that PPG is not a surrogate for heart rate variability analysis. In this work, HRV analysis was applied on beat-to-beat intervals obtained from ECG and PPG in 19 healthy male subjects. Some important HRV parameters were calculated from PPG-HRV and ECG-HRV. Maximum of PPG and its second derivative were considered as two methods for obtaining the beat-to-beat signals from PPG and the results were compared with those achieved from ECG-HRV. Our results show that the smallest error happens in SDNN and SD2 with relative error of 2.46% and 2%, respectively. The most affected parameter is pNN50 with relative error of 29.89%. In addition, in our trial, using the maximum of PPG gave better results than its second derivative.

Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis

With the worldwide growth of mobile wireless technologies, healthcare services can be provided at anytime and anywhere. Usage of wearable wireless physiological monitoring system has been extensively increasing during the last decade. These mobile devices can continuously measure e.g. the heart activity and wirelessly transfer the data to the mobile phone of the patient. One of the significant restrictions for these devices is usage of energy, which leads to requiring low sampling rate. This article is presented in order to investigate the lowest adequate sampling frequency of ECG signal, for achieving accurate enough time domain heart rate variability (HRV) parameters. For this purpose the ECG signals originally measured with high 5 kHz sampling rate were down-sampled to simulate the measurement with lower sampling rate. Down-sampling loses information, decreases temporal accuracy, which was then restored by interpolating the signals to their original sampling rates. The HRV parameters obtained from the ECG signals with lower sampling rates were compared. The results represent that even when the sampling rate of ECG signal is equal to 50 Hz, the HRV parameters are almost accurate with a reasonable error.

Age dependence of arterial pulse wave parameters extracted from dynamic blood pressure and blood volume pulse waves

Atherosclerosis is a significant cause of mortality in the aged population, and it affects arterial wall properties causing differences in measured arterial pulse wave (PW). In this study, both dynamic arterial blood pressure PWs and blood volume PWs are analyzed. The PWs are recorded noninvasively from multiple measurement points from the upper and lower limbs from 52 healthy (22–90-year-old) volunteers without known cardiovascular diseases. For each signal, various parameters earlier proposed in the literature are computed, and 25 different novel parameters are formed by combining these parameters. The results are evaluated in terms of age and heart rate (HR) dependence of the parameters. In general, the results show that 14 out of 25 tested combined parameters have stronger age dependence than any of the individual parameters. The highest obtained linear correlation coefficients between the age and combined parameter and individual parameter equal to 0.85 (

Parameters Extracted From Arterial Pulse Waves as Markers of Atherosclerotic Changes: Performance and Repeatability

p < 10^{-4}

Monitoring arterial pulse waves with synchronous body sensor network.

) and 0.79 (

Unobtrusive night-time EKG and HRV monitoring system

p < 10^{-4}

Combining finger and toe photoplethysmograms for the detection of atherosclerosis

), respectively. Most of the combined parameters have also improved discrimination capability when classifying the test subjects into different age groups. This is a promising result for further studies, but indicate that the age dependence of the parameters must be taken into account in further studies with atherosclerotic patients.

Areas under peripheral pulse waves: a potential marker of atherosclerotic changes

Arterial diseases are significant and increasing cause of mortality and morbidity. In this study, we analyze and compare the discrimination capability of different arterial pulse wave (PW) based indices, both earlier proposed and novel ones, for describing the vascular health. The repeatability of the indices is also evaluated. Both volume PWs and dynamic pressure PWs are recorded by using photoplethysmographic and electromechanical film (EMFi) sensors connected to a wireless body sensor network. The study population consists of 82 subjects, 30 atherosclerotic patients, and 52 control subjects. In addition, day-to-day variability of the derived indices is studied with ten test subjects examined on three different days. The results are evaluated in terms of statistical tests and receiver operating characteristic (ROC) curves as well as coefficient of variation (CV) and intraclass correlation coefficient (ICC). Altogether 24 out of the evaluated 40 PW parameters showed statistical differences (

Combining unobtrusive electrocardiography and ballistography for more accurate monitoring of sleep

p < 0.05