A wireless, battery operated pulse oximeter system with a forehead mounted optical sensor was designed in our laboratory. This wireless pulse oximeter (WPO) would enable field medics to monitor arterial oxygen saturation (SpO2) and heart rate (HR) information accurately following injuries, thereby help to prioritize life saving medical interventions when resources are limited. Pulse oximeters developed for field-based applications must be resistant to motion artifacts since motion artifacts degrade the signal quality of the photoplethysmographic (PPG) signals from which measurements are derived. This study was undertaken to investigate if accelerometer-based adaptive noise cancellation (ANC) can be used to reduce SpO2 and HR errors induced by motion artifacts typically encountered during field applications. Preliminary studies conducted offline showed that ANC can minimize SpO2 and HR errors during jogging, running, and staircase climbing. An 8th order LMS filter with ì = 0.01 was successfully implemented in the WPO's embedded microcontroller. After real-time adaptive filtering of motion corrupted PPG signals, errors for HR values ranging between 60 - 180BPM were reduced from 12BPM to 6BPM. Similarly, ambient breathing SpO2 errors were reduced from 5% to 2%.