Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.

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Development and Preliminary Validation of Heart Rate and Breathing Rate Detection Using a Passive, Ballistocardiography-Based Sleep Monitoring System

IEEE Transactions on Information Technology in Biomedicine ◽

10.1109/titb.2008.2007194 ◽

2009 ◽

Vol 13 (1) ◽

pp. 111-120 ◽

Cited By ~ 121

Author(s):

D.C. Mack ◽

J.T. Patrie ◽

P.M. Suratt ◽

R.A. Felder ◽

...

Keyword(s):

Heart Rate ◽

Monitoring System ◽

Breathing Rate ◽

Sleep Monitoring ◽

Preliminary Validation

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Short-Term Impact of Traffic-Related Particulate Matter and Noise Exposure on Cardiac Function

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17041220 ◽

2020 ◽

Vol 17 (4) ◽

pp. 1220 ◽

Cited By ~ 2

Author(s):

Jean Marie Buregeya ◽

Philippe Apparicio ◽

Jérémy Gelb

Keyword(s):

Heart Rate ◽

Particulate Matter ◽

High Frequency ◽

Noise Exposure ◽

Personal Exposure ◽

High Frequency Power ◽

Short Term ◽

Rr Intervals ◽

Total Noise ◽

Frequency Power

Exposure to traffic-related air pollution and noise exposure contributes to detrimental effects on cardiac function, but the underlying short-term effects related to their simultaneous personal exposure remain uncertain. The aim is to assess the impact of total inhaled dose of particulate matter and total noise exposure on the variations of electrocardiogram (ECG) parameters between pre-cycling and post-cycling periods. Mid-June 2019, we collected four participants’ personal exposure data related to traffic-related noise and particulate matter (PM2.5 and PM10) as well as ECG parameters. Several Bayesian linear models were built to examine a potential association between air pollutants and noise exposure and ECG parameters: heart rate (HR), standard deviation of the normal-to-normal intervals (SDNN), percentage of successive RR intervals that differ by more than 50 ms (pNN50), root mean square of successive RR interval differences (rMSSD), low-frequency power (LF), high-frequency power (HF), and ratio of low- to high-frequency power (LF/HF). We analyzed in total 255 5-min segments of RR intervals. We observed that per 1 µg increase in cumulative inhaled dose of PM2.5 was associated with 0.48 (95% CI: 0.22; 15.61) increase in variation of the heart rate, while one percent of total noise dose was associated with 0.49 (95% CI: 0.17; 0.83) increase in variation of heart rate between corresponding periods. Personal noise exposure was no longer significant once the PM2.5 was introduced in the whole model, whilst coefficients of the latter that were significant previously remained unchanged. Short-term exposure to traffic-related air and noise pollution did not, however, have an impact on heart rate variability.

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Sensor Based Automatic Neonate Respiration Monitoring System

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.a4463.129219 ◽

2019 ◽

Vol 9 (2) ◽

pp. 1296-1299

Keyword(s):

Heart Rate ◽

Internet Of Things ◽

Monitoring System ◽

Respiratory System ◽

Medical Information ◽

Low Cost ◽

Research Work ◽

Breathing Rate ◽

Flow Sensors ◽

Respiration Monitoring

This research work aims to create awareness and monitor the breath rate of a neonate using the air flow sensors and to reduce the number of infants’ death. It is designed based on the Arduino which is open-source electronics platform for hardware and software use. This prototype is developed for reliable and efficient baby monitoring system and play as infant care and monitoring system.A cardio respiratory system is used to monitor the infant’s heart rate, rhythm, breathing rate and other relevant and useful medical information using Electro Cardio Graph (ECG) and other IoT (Internet of Things) devices.This research work proved that the respiration monitoring system for infants can be implemented at low cost and also can prevent the respiration failure deaths.

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Levels of agreement for RR intervals and short-term heart rate variability obtained from the Polar S810 and an alternative system

European Journal of Applied Physiology ◽

10.1007/s00421-008-0742-6 ◽

2008 ◽

Vol 103 (5) ◽

pp. 529-537 ◽

Cited By ~ 65

Author(s):

David Nunan ◽

Djordje G. Jakovljevic ◽

Gay Donovan ◽

Lynette D. Hodges ◽

Gavin R. H. Sandercock ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Short Term ◽

Rr Intervals ◽

Alternative System

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Short-term Heart Rate Variability Analysis in Healthy Dogs of Different Ages

Acta Scientiae Veterinariae ◽

10.22456/1679-9216.118578 ◽

2022 ◽

Vol 50 ◽

Author(s):

Luciene Maria Martinello Romão ◽

Amanda Sarita Cruz Aleixo ◽

Felipe Gazza Romão ◽

Mayra De Castro Ferreira Lima ◽

Miriam Tsunemi ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Frequency Domain ◽

Time Domain ◽

Age Groups ◽

The Other ◽

Short Term ◽

Heart Rate Monitor ◽

Rr Intervals ◽

Healthy Dogs

Background: The modulation of heart rate by autonomic nervous system may be evaluated by the heart rate variability (HRV), which illustrates the fluctuations between RR intervals. To evaluate this analysis, the intervals between 2 QRS complexes are measured. In general, high HRV values are expected in healthy individuals; otherwise, low values are indicative of organism dysfunction. Studies conducted in healthy humans show that HRV suffers reduction with ageing and that there is autonomic immaturity in neonates. The aim of this study was to describe the characteristic pattern of cardiac autonomic behavior in healthy dogs in different age groups through short-term HRV analysis.Materials, Methods & Results: A total of 87 healthy dogs were studied. HRV was analyzed in time and frequency domain, using Holter and heart rate monitor. It was observed that puppies (below one year old) presented a lower parasympathetic predominance and, consequently, lower HRV values on time domain (SDNN, PNN50% e RMSSD) compared to the other 2 groups and on frequency domain (LF, HF and LF/HF) compared to the adult animals group (between 1 and 7-year-old), which presented higher HRV values when compared to the other groups. Elderly dogs (over 8-year-old) exhibited a natural tendency to decrease cardiac parasympathetic HRV indexes.Discussion: The use of the HRV method as a prognostic index and as an arrhythmogenic marker for various canine heart diseases presents interesting perspectives. However, before it may be employed for these purposes, a better understanding should be established regarding the physiological behavior of autonomic cardiac modulation in different age groups to serve as a basis for future analyses. This study observed that puppies presented higher values for HR and, therefore, shorter RR intervals than the other groups (adult and elderly dogs), what was observed on Holter and heart rate monitor methods (HRM). There were significant differences between puppies and the other 2 groups (adults and elderly) for all time-domain variables using both methods (Holter and HRM methods). SDNN was significantly lower in puppies compared to adults and elderly dogs. In addition, both RMSSD and PNN50%, which were more reliable over shorter periods of time, also presented means and medians that were significantly lower in puppies. Regarding frequency-domain HRV parameters observed on Holter method, these indexes were decreased on the elderly group compared to adult dogs, which is a possible effect of aging. Also, puppies revealed lower frequency-domain HRV parameters on both methods when compared to adult dogs. The influence of age on HRV is possibly related to the stage of development of an individual, starting at conception up to the maturity in relation to the mechanisms that cause variations in HR. There are studies in humans that suggest a gradual increase in parasympathetic activity during childhood, followed by a steady decrease as aging occur. The present study observed the same pattern in dogs. The balance between sympathetic and parasympathetic systems is influenced by age in dogs, which alters HRV values in the short-term. The HRV method´s analysis is relatively simple and non-invasive for assessing cardiac autonomic function; also, it is widely used in human medicine as a risk measure for sudden cardiac death. The 24-hour HRV analysis is highly challenging, as it is time-consuming, expensive, delays diagnosis, and has a large number of artifacts; in this way, standards for its short-term analysis were developed. Keywords: cardiology, autonomic nervous system, heart rate monitor, Holter.

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Heart rate and heart rate variability of healthy cats in home and hospital environments

Journal of Feline Medicine and Surgery ◽

10.1016/j.jfms.2004.12.003 ◽

2005 ◽

Vol 7 (3) ◽

pp. 195-202 ◽

Cited By ~ 47

Author(s):

Jonathan A Abbott

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Fourier Transform ◽

Fast Fourier Transform ◽

Sinus Arrhythmia ◽

Rr Intervals ◽

Rr Interval ◽

Hospital Environments ◽

Echocardiographic Examination ◽

Veterinary Hospital

To investigate heart rate and its variability, a telemetry device was affixed to 16 healthy, young cats. Prior to inclusion in the study, cats were subject to echocardiographic examination. The heart rate (HR) when cats were restrained for echocardiography (HRr) was calculated from 4–5 consecutive RR intervals obtained from a simultaneously recorded electrocardiogram. Electrocardiographic data were then acquired by telemetry in a quiet room in the veterinary hospital (VTH) and later, in the owner's home (home). The ambulatory data were digitally sampled and the RR interval tachogram from a 4 min epoch subject to Fast Fourier Transform to yield measures of heart rate variability (HRV). Sinus arrhythmia was often observed in resting cats. Heart rates (bpm) expressed as mean (±SD) were: HRr: 187 (±25), HRVTH: 150 (±23), HRhome: 132 (±19); each of these rates was significantly different from the others. Significant differences in profiles of HRV suggested that sympathetic tone was higher (and parasympathetic tone lower) when cats were in the hospital.

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LI-Care: A LabVIEW and IoT Based eHealth Monitoring System

Electronics ◽

10.3390/electronics10243137 ◽

2021 ◽

Vol 10 (24) ◽

pp. 3137

Author(s):

Kunjabihari Swain ◽

Murthy Cherukuri ◽

Sunil Kumar Mishra ◽

Bhargav Appasani ◽

Suprava Patnaik ◽

...

Keyword(s):

Heart Rate ◽

Monitoring System ◽

Virtual Instrument ◽

Diastolic Pressure ◽

Systolic Pressure ◽

Attractive Alternative ◽

Breathing Rate ◽

Oxygen Level ◽

Web Based ◽

Rms Errors

This paper presents a Laboratory Virtual Instrument Engineering Workbench (LabVIEW) and Internet of Things (IoT)-based eHealth monitoring system called LI-Care to facilitate the diagnosis of the health condition cost-effectively. The system measures the heart rate, body temperature, blood pressure, oxygen level, and breathing rate, and provides an electrocardiogram (ECG). The required sensors are integrated on a web-based application that keeps track of the essential parameters and gives an alarm indication if one or more physiological parameters go beyond the safe level. It also employs a webcam to obtain the patient view at any time. LabVIEW enables the effortless interfacing of various biomedical sensors with the computer and provides high-speed data acquisition and interactive visualizations. It also provides a web publishing tool to access the interactive window remotely through a web browser. The web-based application is accessible to doctors who are experts in that particular field. They can obtain the real-time reading and directly perform a diagnosis. The parameters measured by the proposed system were validated using the traditional measurement systems, and the Root Mean Square (RMS) errors were obtained for the various parameters. The maximum RMS error as a percentage was 0.159%, which was found in the temperature measurement, and its power consumption is 1 Watt/h. The other RMS errors were 0.05% in measurement of systolic pressure, 0.029% in measurement of diastolic pressure, 0.059% in measurement of breathing rate, 0.002% in measurement of heart rate, 0.076% in measurement of oxygen level, and 0.015% in measurement of ECG. The low RMS errors and ease of deployment make it an attractive alternative for traditional monitoring systems. The proposed system has potential applications in hospitals, nursing homes, remote monitoring of the elderly, non-contact monitoring, etc.

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