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| Name | Class |
|---|---|
| Engineering and Physical Sciences Research Council, UK | OTHER |
| University of Oxford | OTHER |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Young Healthy Volunteers | Healthy volunteers under the age of 40 |
| |
| Older healthy volunteers | Healthy volunteers over the age of 70 |
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| Patients with atrial fibrillation | Patients with permanent AF |
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| Patients with a pacemaker | Patients who have an implanted pacemaker that is continually pacing |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Recording of 12 lead ECG | Other | Recording of 12 lead ECG |
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| Measure | Description | Time Frame |
|---|---|---|
| The coefficient of variation for each respiration rate algorithm | 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 | 5-6 months |
| Measure | Description | Time Frame |
|---|---|---|
| The coefficient of variation for the respiration rate calculated from a second pulse oximeter | Participants will wear two different PPG monitors to assess whether PPG monitors from different manufacturers introduce artefactual changes to the PPG morphology | 5-6 months |
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Inclusion Criteria:
Young Healthy Volunteers
Older Healthy Volunteers
Patients
Exclusion Criteria:
Young Healthy Volunteers
Older Healthy Volunteers
Patients
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Healthy volunteers and hospital outpatients
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| Name | Affiliation | Role |
|---|---|---|
| Richard Beale, MBBS, FRCA | Guy's and St Thomas' Foundation Trust | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| St Thomas' Hospital | London | SE1 7EH | United Kingdom |
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| Patients with restricted chest movement | Patients whose chest expansion is less than 2.5cm |
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| Recording of lying and standing blood pressure | Other | Recording of lying and standing blood pressure |
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| Recording of chest wall movement | Other | Recording of chest wall movement |
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| Recording of heart rate variability | Other | Done during deep breathing and a valsalva manoeuvre |
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| Recording of ECG and Pulse oximeter waveform at rest | Other | For 10 mins |
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| Recording of ECG and Pulse oximeter waveform during exercise | Other | Recording of ECG and Pulse oximeter waveform during exercise |
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