A reliable, low-cost screening tool to identify high-risk cephalopelvic disproportion (CPD) patients is of paramount importance especially in resource-limited areas where a timely referral to a medical facility for assisted delivery or cesarean section would make the difference between saving the life of mother and child and potential loss of both patients. To address this pressing need we propose to develop and test a simple, ultra-low cost portable technology using off-the-shelf Microsoft Kinect sensor to quantify an obstructive score to identify women at high risk for CPD. The technology will create very high precision 3D patient models from which a plethora of traditional and novel anthropometric and volume measures can be extracted and used in conjunction with machine learning algorithms to establish a clinical score identifying high risk for CPD. This novel technology has the potential to establish a better risk assessment for obstruction than currently available clinical practice in low-resource setting, thus providing a low-cost avenue to save lives at birth.
More information about Saving Lives at Birth (Round 5)