Obstructive sleep apnea Is a major consideration for anesthesiologists before surgery. Currently, as there is rarely time for a full-sleep study pre-surgery, anesthesiologists use a simplistic 5-question survey that is prone to personal biases and is frequently inaccurate. Getting the sleep apnea diagnosis wrong can be expensive for the hospital and dangerous for the patient. Therefore, we created Appnea in order to calculate AHI, a sleep apnea metric, using everyday equipment (i.e. the accelerometer of an iPhone) to collect ventilation data during sleep, and providing physicians with a cheaper and more accurate alternative.

We collected sleep data with the iphone attached and created a new classification algorithm to detect whether a person has stopped breathing.

Share this project:
×

Updates