Pulse oximetry derived respiratory rate in general care floor patients. We have demonstrated an algorithm for the computation of RR from a standard, commercially available pulse oximetry system during spontaneous breathing in GCF patients in the GCF setting. Program Do Projektowania Konstrukcji Drewnianych Za Darmo here. RRoxi was derived for data collected from a 6. RRETCO2. We found excellent agreement between the two with an RMSD of 1. Significantly, the algorithm was developed and tested using a wide range of in hospital patient data 2, 5. GCF patients. This was done to mitigate overtraining on GCF data and to ensure that the algorithm has the ability to cope with as wide a range of situations in the field as possible. These results are in accordance with a previous study by our group of healthy volunteers 2. Compared to this earlier study, there is a slight decrease in performance mean 0. STD 1. 7. 7 vs. 1. RMSD 1. 8. 3 vs. This may be a result of the more challenging nature of the GCF patients compared to the healthy subjects studied in this earlier work. In order to assess the effects of intra patient dependency within the analysis, we investigated the inter patient variability of the results. The individual statistics for each subject were computed and it was found that the mean RMSD was 1. RMSDs was 1. 2. 8 brpm. This supports the likelihood of an acceptably small intra patient variability in the difference between RRoxi and the reference. Importantly, this performance was accomplished using a single sensor that combines the ability to monitor RR, arterial oxygen saturation Sp. Datex Cardiocap Ii Manual' title='Datex Cardiocap Ii Manual' />O2, and pulse rate these findings highlight a unique, clinically useful approach to monitoring multiple respiratory variables in a continuous, non invasive, and easy to use manner. An advantage of the use of a single senor for Sp. O2, HR and RR is that it potentially reduces the number of alarm modes. For example, a single sensor off or motion artifact alarm could cover all three parameters, whereas in two separate devices there is a likelihood of significant increased false alarm rate, with a corresponding likelihood of increased alarm fatigue and workflow disruption 4. Datascope%20Passport%202%20Large.jpg' alt='Datex Cardiocap Ii Manual' title='Datex Cardiocap Ii Manual' />Big Wheel Rolling stand Small Wheel Rolling stand Brands of Monitors 3F Iris Iris. ADC Adview Vital Sign, Adview 2 Adview Vital Sign, Adview 2 BioLightSunnex. Adox Manual Adox SP702 Nederlands AGA Manual AGA Ventilator UV 705 English Bejing Eternity Electronic Technology CO LTD. Manual Infusion Pump IP300 English. The significance of the magnitude of absolute error associated with respiratory rate depends on the on the true rate. The results published here mostly lie in a central range of respiration between approximately 1. We performed sub analyses of the results for RR lt 1. SD and RMSD to be 1. These sub analyses involved 6. These values are slightly greater than for the whole data set. It is important, however, not to over interpret these results as there are relatively few data at these extremes. Our group is very aware of the importance of the algorithm performance at the extremes and have ongoing work considering patient groups that cover these regions 5. The physiological processes that both enable and confound the measurement of respiratory rate appear well understood in this space and link to the wider literature on the causes of erroneous PPG components including vasotone, vasomotion, posture, patient motion, temperature, metabolic state, pain, drug administration, lung compliance, upper airway obstruction, edema, heart rate, respiratory rate, catheterization, ablation, the venous blood component and arrhythmia. These are documented more fully in the work of others 2, 1. There are little data on GCF monitoring of the PPG for RR as this is an area of care where continuous oximeter monitoring is not regularly carried out. However, we have observed in our own work that operating room data exhibits considerable PPG artifact from motion, drug administration, vasomotion, administration of fluids, heart rate changes, etc., whereas the GCF is a more benign environment. If continuous PPG based RR were to gain traction in the GCF, we expect that much of the signal would be of good quality with intermittent instances of severe artifact due to patient motion voluntary or assisted. It is worth noting that our wavelet based algorithm does not tend to exhibit the erroneous low rates posted across the range of reference rates prevalent in the work Karlen et al. We believe that this is due to increased flexibility in identifying and partitioning respiratory components inherent in our approach over their smart fusion, frequency spectrum based approach. Our results compare favourably with those reported by other groups 1. However, such comparisons should be considered carefully as the results are highly dependent on the characteristics of the raw signal and its manipulation, exclusion criteria, manual selection of data if applicable, the patient group studied and, of course, the algorithmic implementation including pre processing, processing and post processing steps. The determination of a clinically useful physiological parameter is therefore a distinctly non trivial task. An important aspect of our work is that it targets the development of a fully automated algorithm capable of coping with the extremes of data characteristics in the clinical environment i. RRoxi values generated are those that would be displayed on the device screen to the clinician. A sophisticated algorithmic infrastructure is therefore required to take the raw biosignal from the hardware, process it, present it to the core algorithm, then apply further post processing to the output in order to produce a value with the integrity necessary for display on the screen of a medical monitoring device 2. It is well established that many patient deaths on the hospital GCF may be prevented, at least in part, through more vigilant monitoring aimed at detecting clinically meaningful antecedents to patient deterioration 8. For example, Hodgetts et al. GCF were preventable. It has been reported that approximately 4. Despite this, it has been suggested that upon the arrival of a hospital rapid response team, up to date vital signs, such as RR, are not available for three out of four patients 4. Clearly, providing this information in a continuous and timely manner to clinicians could provide the foundation for improved patient outcomes on the GCF. A critical factor contributing to respiratory distress on the GCF is the administration of opioid analgesia and associated respiratory depression 3. Consequently, the Anesthesia Patient Safety Foundation has issued guidance suggesting that for patients receiving post operative opioid analgesia administration, vital sign monitoring should occur with increased frequency 1. Thus, monitoring RR continuously may offer an avenue to specifically reduce the deleterious impact of opioid induced respiratory depression. Despite the overwhelming importance of a patients respiratory status while on the GCF, manual observation remains the standard of care for assessment of RR. It is clear to see that this intermittent approach is lacking because it leaves substantial periods of time in which the patients respiratory status is unmonitored. Given the rapidity with which a patients respiratory status may devolve, critical clinical information during these unmonitored periods of time leave the patient susceptible to the untoward clinical complications mentioned above. In addition to patient safety considerations, there is also a clinical burden placed on the staff to monitor RR at periodic intervals. By establishing a means through which RR can be monitored continuously, in conjunction with pulse oximetry from a single sensor site, our algorithm provides a mechanism to potentially improve patient outcomes on the GCF while improving compliance with vital sign monitoring requirements. Concluding remarks. Our results demonstrate that the RRoxi algorithm is a potentially viable technological approach for monitoring RR in a diverse GCF patient population. Currently, pulse oximeters use the differential absorption of red and infrared light between oxygenated hemoglobin and deoxygenated hemoglobin to provide a measure of oxygen saturation, with heart rate also provided.