Validation of Respiration Rate Algorithms
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Respiratory Rate
- Sponsor
- Guy's and St Thomas' NHS Foundation Trust
- Enrollment
- 130
- Locations
- 1
- Primary Endpoint
- The coefficient of variation for each respiration rate algorithm
- Status
- Completed
- Last Updated
- 12 years ago
Overview
Brief Summary
Continuous accurate unobtrusive respiratory rate monitoring may lead to improved patient outcomes, as respiratory rate is thought to be a sensitive marker of patient deterioration. Currently systems are not suitable for long term monitoring, particularly in ambulant patients as they are too restrictive. To ensure that our algorithms are suitable for use in a clinical context we need to demonstrate their performance not only in the optimal situation, healthy volunteers at rest, but also in more challenging situations such as where the person being monitored is moving and also in patients who have conditions which may affect their physiology in such a way that the accuracy of the respiration rate estimation may be affected.
No previous study has systematically tested algorithms deriving respiratory rate from either the ECG or the photoplethysmography (PPG) waveforms in a real -world setting.
The algorithms work by looking for changes in intervals between heartbeats and also changes in the sizes of the ECG and PPG waveforms, both of which may be caused by respiration. These changes tend to diminish with increasing age and also conditions which alter the chest movement and cardiac reflexes. Thus it is important to test our algorithms' accuracy in participants exhibiting these conditions. It is also important to ensure that the calculations of respiratory rate are accurate across a range of heart rates and respiratory rates. Our testing covers all these variables.
Investigators
Richard Beale
Clinical Director
Guy's and St Thomas' NHS Foundation Trust
Eligibility Criteria
Inclusion Criteria
- •Young Healthy Volunteers
- •Participant is willing and able to give informed consent for participation in the study.
- •Male or Female, aged between 18 and 40 years old.
- •Older Healthy Volunteers
- •Participant is willing and able to give informed consent for participation in the study.
- •Male or Female, aged 70 years or above.
- •Participant is willing and able to give informed consent for participation in the study.
- •Male or Female, aged 18-70 years old.
- •Participant has one of the following conditions:
- •Atrial fibrillation
Exclusion Criteria
- •Young Healthy Volunteers
- •Any condition which might increase the risk of exercise testing
- •Any history of ischaemic heart disease
- •Any history of heart failure
- •Any structural heart disease (eg: valvular lesions, hypertrophic obstructive cardiomyopathy)
- •Any abnormalities on a resting ECG
- •Deep vein thrombosis diagnosed within the last 6 months or under active treatment
- •Uncontrolled hypertension (systolic blood pressure \>220 mm Hg, diastolic \>120 mm Hg)
- •Aortic aneurysm
- •Aortic or cardiovascular surgery within 6 months of recruitment
Outcomes
Primary Outcomes
The coefficient of variation for each respiration rate algorithm
Time Frame: 5-6 months
The algorithms to be tested are: one which calculates respiration rate (RR) from ECG only, one which calculates RR from PPG only, one which calculates RR from simultaneous ECG and PPG
Secondary Outcomes
- The coefficient of variation for the respiration rate calculated from a second pulse oximeter(5-6 months)