![]() ![]() ![]() By employing advanced signal processing techniques–including parallel engines and adaptive filters–they believed they could find the true arterial signal that would allow accurate monitoring of arterial oxygen saturation and pulse rate, even during the most challenging conditions. When Joe Kiani and Mohamed Diab looked at the same pulse oximetry signal differently than anyone had before, they created new possibilities. This causes conventional pulse oximeters to display false low or high SpO 2 and pulse rates–resulting in false alarms as high as 90% in ICUs and recovery rooms. Unfortunately for conventional pulse oximetry, venous blood moves every time the patient moves or breathes. Although this was a big step forward in the evolution of pulse oximetry, it has one major flaw–it assumes the only pulsating component is arterial blood. The industry had given up and considered the problem "unsolvable." Clinicians were forced to live with the results–excessive false alarms, delayed notification due to long averaging times, inaccurate data, and an inability to obtain data on the most critical patients.Ĭonventional pulse oximetry works under the assumption that by looking at only the pulse and normalizing the pulsating signal over the non-pulsating signal, oxygen saturation (SpO 2) can be measured without calibration. ![]() Since its inception, pulse oximetry was plagued by unreliability when it was needed most–during patient motion and low perfusion. Overcoming the Limitations of Conventional Pulse Oximetry ![]()
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