Ignite Creation Date:
2024-05-06 @ 1:07 AM
Last Modification Date:
2024-10-26 @ 10:59 AM
Study NCT ID:
NCT01732029
Status:
COMPLETED
Last Update Posted:
2017-06-26
First Post:
2012-11-16
Brief Title:
Calibration and Evaluation of an Audio Pulse Oximeter Sensor AudioOx at Ascent and Descent From Simulated Altitude
Sponsor:
University of British Columbia
Organization:
University of British Columbia
Study Overview
Official Title:
Calibration and Evaluation of an Audio Pulse Oximeter Sensor AudioOx at Ascent and Descent From Simulated Altitude
Status:
COMPLETED
Status Verified Date:
2017-06
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Pulse oximetry is a standard non-invasive method of measuring blood oxygen saturation SpO2 In developing countries pulse oximeters are rare because of expense and electricity requirements Our ECEM group has developed the Phone Oximeter which uses a cell phone which are widely available in developing countries to compute and analyze information from a pulse oximeter sensor To further reduce costs we have developed an oximeter sensor AudioOx that plugs into the audio jack of a standard cell phone This study aims to calibrate the AudioOx by exposing 30 healthy adult volunteers to various altitudes in UBCs hypoxia chamber
Detailed Description:
Purpose
We at the Electrical and Computer Engineering in Medicine Group ECEM at the University of British Columbia Vancouver Canada plan to make pulse oximetry available to resource poor countries by designing a low-cost battery-powered pulse oximeter device consisting of a low-cost pulse oximeter sensor connected to a cell phone The use of cell phones as patient monitors is appealing as they are widely available in many developing countries Utilizing battery power cell phones do not rely on a continuous source of electricity This is essential as most low-resource settings lack adequate infrastructure and thus cannot provide the uninterrupted power supply required for conventional patient monitoring Furthermore a cell phone has the efficiency integrated display and processing power required to analyze and store the raw data derived from the pulse oximeter sensors Data from the pulse oximeter can be transmitted to referral centers for diagnostic and advisory purposes where cellular and networking services permit
Proprietary oximeter sensors and modules are expensive To reduce cost we are proposing to develop a simple audio pulse oximeter sensor AudioOx that that does not require a sensor module and interfaces via the audio jack of any standard cell phone By utilizing the audio jack for transmission of data from the sensor to phone we can ensure that cell phone types most common in various areas of the world are universally supported Preliminary laboratory tests showed that oximetry data from the AudioOx has sufficient signal strength and resolution for extraction of heart rate and SpO2
Hypothesis
We hypothesize that this study will allow us to successfully calibrate the AudioOx
Justification
Development of pulse oximeters requires calibration and evaluation for accuracy There is no acceptable surrogate calibration tool for pulse oximeters To quote the current International Organization for Standardization ISO Pulse Oximetry standard document There is today no accepted method of verifying the correct calibration of a pulse oximeter probepulse oximeter monitor combination other than testing on human beings This is due to the complexity of the optical intricacies of the interaction of light and human tissue upon which pulse oximetry depends
A previous calibration study was performed on volunteers during a concurrent study in the UBC hypoxia chamber The results demonstrated that the AudioOx can be calibrated to within the 4 accuracy required by ISO The study setup however was suboptimal as the measured SpO2 data was predominantly hypoxic Motion artifacts were also abundant as the subjects had unrestricted movement
Objectives
Our main objective is to improve the calibration of the AudioOx by
Asking subjects to remain relatively immobile during data measurement
Exposing subjects to a very gradual change in oxygen concentration so that measurements are distributed over the entire clinical range of SpO2 70 to 100
Using two instead of one clinically-approved pulse oximeters from different manufacturers as secondary reference standards
Our secondary objective is to evaluate and compare the performance of the AudioOx during motion low perfusion and rapidly changing SpO2 by
Asking the subjects to perform standardized hand and finger motions during data measurement
Simulating low perfusion via two methods by partially occluding the brachial artery using a blood pressure cuff and by having the patient raise their arm for two minutes and using light filters to reduce the red and infra-red signals detected by the pulse oximeter sensors
Measuring SpO2 as the subject enters and exits the hypoxia chamber
Research Method
This will be a non-invasive concurrent observational study of healthy voluntary adult subjects in a normobaric sea-level atmospheric pressure hypoxia low oxygen chamber
Study subjects will be put into a hypoxic state by exposing them to normobaric hypoxia by administrating an air mix containing a reduced O2 concentration This is achieved in a hypoxia chamber where O2 concentration is gradually reduced to simulate high altitude about 4500 m
The goals of the current study are very similar to another study conducted in the hypoxia chamber REB IDH12-02362 The Camera Oximeter the same methodology is applied This will allow recruiting subjects for both studies and will reduce the total number of subjects necessary for achieving our goal
Statistical Analysis
Calibration of SpO2 Data from the initial set of subjects at least 10 in the study will be used to calibrate the AudioOx oximetry data Firstly ratio R is calculated from the red and infra-red IR photo-absorbance signals where
R ACRED DCRED ACIR DCIR
ACRED and ACIR are pulsatile components of the red and infra-red light detected by the oximeter photosensor DCRED and DCIR are constant components of the red and infra-red light detected by the oximeter photosensor
R values are paired to the reference SpO2 values average of the two readings from the two reference pulse oximeters and plotted on a scatter plot Depending on the shape of the plot the R values are translated to SpO2 values using a linear equation multiple linear equations or polynomial equations
Evaluation of Accuracy
Readings from the oximeter sensors are grouped into six ranges 70-75 76-80 81-85 86-90 91-95 and 96-100 For each range of SpO2 and the overall range 70-100 accuracy will be calculated as per ISO definitions
Accuracy of the pulse oximeter shall be stated in terms of the root-mean-square rms difference between AudioOx values SpO2i and reference values SRi as given by
Arms i1 to nSpO2i- SRi2 n
To express Accuracy relative to the gold-standard blood gas analysis the error of the secondary standard pulse oximeter errorref will be included
Accuracy Arms2 errorref2
Motion low perfusion will be quantified by the proportion of time that the test measurements either gave no readings or were more than 4 different from the corresponding control measurements
We at the Electrical and Computer Engineering in Medicine Group ECEM at the University of British Columbia Vancouver Canada plan to make pulse oximetry available to resource poor countries by designing a low-cost battery-powered pulse oximeter device consisting of a low-cost pulse oximeter sensor connected to a cell phone The use of cell phones as patient monitors is appealing as they are widely available in many developing countries Utilizing battery power cell phones do not rely on a continuous source of electricity This is essential as most low-resource settings lack adequate infrastructure and thus cannot provide the uninterrupted power supply required for conventional patient monitoring Furthermore a cell phone has the efficiency integrated display and processing power required to analyze and store the raw data derived from the pulse oximeter sensors Data from the pulse oximeter can be transmitted to referral centers for diagnostic and advisory purposes where cellular and networking services permit
Proprietary oximeter sensors and modules are expensive To reduce cost we are proposing to develop a simple audio pulse oximeter sensor AudioOx that that does not require a sensor module and interfaces via the audio jack of any standard cell phone By utilizing the audio jack for transmission of data from the sensor to phone we can ensure that cell phone types most common in various areas of the world are universally supported Preliminary laboratory tests showed that oximetry data from the AudioOx has sufficient signal strength and resolution for extraction of heart rate and SpO2
Hypothesis
We hypothesize that this study will allow us to successfully calibrate the AudioOx
Justification
Development of pulse oximeters requires calibration and evaluation for accuracy There is no acceptable surrogate calibration tool for pulse oximeters To quote the current International Organization for Standardization ISO Pulse Oximetry standard document There is today no accepted method of verifying the correct calibration of a pulse oximeter probepulse oximeter monitor combination other than testing on human beings This is due to the complexity of the optical intricacies of the interaction of light and human tissue upon which pulse oximetry depends
A previous calibration study was performed on volunteers during a concurrent study in the UBC hypoxia chamber The results demonstrated that the AudioOx can be calibrated to within the 4 accuracy required by ISO The study setup however was suboptimal as the measured SpO2 data was predominantly hypoxic Motion artifacts were also abundant as the subjects had unrestricted movement
Objectives
Our main objective is to improve the calibration of the AudioOx by
Asking subjects to remain relatively immobile during data measurement
Exposing subjects to a very gradual change in oxygen concentration so that measurements are distributed over the entire clinical range of SpO2 70 to 100
Using two instead of one clinically-approved pulse oximeters from different manufacturers as secondary reference standards
Our secondary objective is to evaluate and compare the performance of the AudioOx during motion low perfusion and rapidly changing SpO2 by
Asking the subjects to perform standardized hand and finger motions during data measurement
Simulating low perfusion via two methods by partially occluding the brachial artery using a blood pressure cuff and by having the patient raise their arm for two minutes and using light filters to reduce the red and infra-red signals detected by the pulse oximeter sensors
Measuring SpO2 as the subject enters and exits the hypoxia chamber
Research Method
This will be a non-invasive concurrent observational study of healthy voluntary adult subjects in a normobaric sea-level atmospheric pressure hypoxia low oxygen chamber
Study subjects will be put into a hypoxic state by exposing them to normobaric hypoxia by administrating an air mix containing a reduced O2 concentration This is achieved in a hypoxia chamber where O2 concentration is gradually reduced to simulate high altitude about 4500 m
The goals of the current study are very similar to another study conducted in the hypoxia chamber REB IDH12-02362 The Camera Oximeter the same methodology is applied This will allow recruiting subjects for both studies and will reduce the total number of subjects necessary for achieving our goal
Statistical Analysis
Calibration of SpO2 Data from the initial set of subjects at least 10 in the study will be used to calibrate the AudioOx oximetry data Firstly ratio R is calculated from the red and infra-red IR photo-absorbance signals where
R ACRED DCRED ACIR DCIR
ACRED and ACIR are pulsatile components of the red and infra-red light detected by the oximeter photosensor DCRED and DCIR are constant components of the red and infra-red light detected by the oximeter photosensor
R values are paired to the reference SpO2 values average of the two readings from the two reference pulse oximeters and plotted on a scatter plot Depending on the shape of the plot the R values are translated to SpO2 values using a linear equation multiple linear equations or polynomial equations
Evaluation of Accuracy
Readings from the oximeter sensors are grouped into six ranges 70-75 76-80 81-85 86-90 91-95 and 96-100 For each range of SpO2 and the overall range 70-100 accuracy will be calculated as per ISO definitions
Accuracy of the pulse oximeter shall be stated in terms of the root-mean-square rms difference between AudioOx values SpO2i and reference values SRi as given by
Arms i1 to nSpO2i- SRi2 n
To express Accuracy relative to the gold-standard blood gas analysis the error of the secondary standard pulse oximeter errorref will be included
Accuracy Arms2 errorref2
Motion low perfusion will be quantified by the proportion of time that the test measurements either gave no readings or were more than 4 different from the corresponding control measurements
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None