Relation between respiratory rate and heart rate – A comparative study

Bahmed, Farah; Khatoon, Farisa; Reddy, B.R.S.

doi:10.5958/2394-2126.2016.00099.2

Cited by 9 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The normal heart beating is called "sinus rhythm", and if the variability between heartbeats is greater than 0.12 s, then this event is called "sinus arrhythmia". Breathing usually induces sinus arrhythmia; thus, HRV can be used to measure breathing rate [22]. The term R-R interval or inter-beat interval (IBI) is the time (measured in milliseconds) between heartbeats.…”

Section: ) Heart Rate (Hr)mentioning

confidence: 99%

Review of Stress Detection Methods Using Wearable Sensors

Taskasaplidis,

Fotiadis,

Bamidis

2024

IEEE Access

View full text Add to dashboard Cite

Stress is a significant factor that affects well-being and health. Factors that trigger stress include work, social interactions, and economic and environmental factors. Stress may cause lower labor productivity, physical and mental health problems, and malfunctions in all social aspects of life. Psychosomatic health can be improved if proper stress detection mechanisms are present in daily life and stress reduction methods can occur. Wearable sensors are currently used in many commercial and scientific applications in a non-destructive or annoying manner. These devices are used in daily routines. In this paper, a comprehensive review of the latest literature and developments in stress detection methods is presented through extensive and holistic research on stress response, both at the level of the autonomic nervous system (ANS) and hypothalamic-pituitary-adrenal axis (HPA). This study focused on the exploitation of various methods, technologies, and data analysis systems to understand stress in a multifaceted and comprehensive manner. Various stress-related factors are presented along with biological signal measurements, and physical secretions or biomarkers are primarily used for stress detection. Furthermore, the manner in which body movement and posture measurements may be related to stress was investigated, together with speech and hand tremors. Various stress-detection technologies have been analyzed, and existing data analysis methods that can be applied to stress-detection systems have been highlighted. This review serves as a reference and guideline for exploring this area of interest, identifying research opportunities, and offering ideas, options, and suggestions for optimized solutions regarding future applications and research.

show abstract

Section: ) Heart Rate (Hr)mentioning

confidence: 99%

Review of Stress Detection Methods Using Wearable Sensors

Taskasaplidis,

Fotiadis,

Bamidis

2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…As such, it is of interest to have an alternative validation approach that can be used for real life cycling situations. It is well known in the medical community that the cardiac system and the respiratory system behave as coupled biological oscillators [16]. Simply put, during exercise the muscles of the body are working harder and need to produce more energy (ATP) for muscle contraction.…”

Section: Validation Of Minimised Pollutionmentioning

confidence: 99%

“…More can be read about heart rate and breathing rate in [16], [18], [19] and [20] which focus on the behaviour of heart rate and breathing rate during exercise.…”

Section: Validation Of Minimised Pollutionmentioning

confidence: 99%

A smart electric bike for smart cities

Sweeney¹,

Shorten²,

Timoney³

et al. 2022

Preprint

View full text Add to dashboard Cite

This thesis has been composed by the author and has not been previously submitted for examination which has led to the award of a degree.Due acknowledgement must always be made for the use of any material contained in, or derived from this thesis. i This project was completed with the help of a number of people. I was fortunate to be jointly supervised by Prof. Robert Shorten and Prof. David Timoney. Thank you to Bob for his enthusiasm throughout the project, for always making time and for his ten new ideas per week. Thank you to David for always having an open door, a lot to say about torque and a newfound expertise in spirometry equipment. Thank you to both for having complementary temperaments. The contributions of Liam, Luke and Declan in the UCD Electronics workshop were essential for the hardware components of this project with Liam commenting that I had "everyone in the workshop working on the project" at one point. A special word of thanks to Luke for showing me how to solder properly. Brian Mulkeen was on hand to deal with multiple hardware crises which were all resolved with thorough, exhaustive logic. Thank you to John Gahan in the UCD Mechanical Engineering department for his stories, for providing somewhere to keep the bike for the first semester and for always knowing how to fix everything. Thank you to Giovanni Russo from IBM Research for his advice in the design of the control system. Thank you to Rodrigo Ordóñez-Hurtado who played a big role in trying to figure out how to use maths to describe an electric bike and then use that maths to get the electric bike to do what we wanted. Thank you to Wynita Griggs for all of her help with Android Studio, SUMO and in getting ready for the demonstration in Trinity College in March. Thank you to Francesco Pilla for his input on the air pollution use case. To my parents, Tommy and Elizabeth, who were my first educators, thank you for 23 years of advice, and 19 years of support during formal education. I promise I will get a job now. A sincere word of thanks to JP McManus, the All Ireland Scholarship programme and the UCD Ad Astra Academy who helped to support me financially during my first four years of study in UCD.

show abstract

“…The fluctuations in pressure due to the respiratory effects could change the resistance in piezoresistive sensors and develop electrical potential (charge) in piezoelectric sensors. The piezoresistive and piezoelectric sensors are potential for wearable and continuous RR monitoring since they could be fabricated into chest straps or clothes (Mahbub et al 2017b), and have been applied as the reference for RR monitoring in related studies (Bahmed et al 2016, Sifuentes et al 2016. Wearable piezoresistive fabric sensors could monitor RR under various moving environments from rapid running to slow walking (Jeong et al 2009).…”

Section: Piezoresistive and Piezoelectric Pressure Sensorsmentioning

confidence: 99%

Recent development of respiratory rate measurement technologies

et al. 2019

View full text Add to dashboard Cite

Respiratory rate (RR) is an important physiological parameter whose abnormality has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to perform, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies.

show abstract

Relation between respiratory rate and heart rate – A comparative study

Cited by 9 publications

References 0 publications

Review of Stress Detection Methods Using Wearable Sensors

Review of Stress Detection Methods Using Wearable Sensors

A smart electric bike for smart cities

Recent development of respiratory rate measurement technologies

Contact Info

Product

Resources

About