Laboratory for Interactive Optimization and Learning


Using 3D Sensors for

Medical Diagnostics

Off-the-shelf 3D sensors can be used to obtain high-resolution 3D imagery tracking pregnancy progression and lymphedema onset.

Volumetric measurements and a wide range of auxiliary anthrophometric measures can be estimated and learned from 3D data.

Currently, we explore the use of 3D cameras together with machine learning and optimization in the following application areas:

Application 1: Predicting obstructed labor in low-resource settings.

Cephalopelvic disproportion (CPD) is one of the most common preventable causes of unfavorable pregnancy outcomes and one of the major contributors to high infant and maternal mortality rates in the developing world. According to the WHO report 8% of the maternal deaths worldwide are still attributable to CPD. A reliable, low-cost screening tool to identify at-risk women is of paramount importance especially in resource-limited areas where ultrasound screening is not available and cesarean sections are not a feasible delivery option. In such cases, early detection of CPD could allow for high-risk patients to be referred to urban clinics for medically observed labor or a cesarean procedure. The technology will present an economical and easy-to-use diagnostic alternative to more sophisticated imaging methods unavailable in the rural developing world.

Application 2: Detecting lymphedema onset.

Nearly every breast cancer patient undergoes some type of surgical intervention, chemotherapy, or radiation as part of their therapy process, and while these procedures have proven to be very effective for cancer removal, they can create an unintended side-effect of severe, permanent arm swelling. This severe limb swelling condition is known as lymphedema and there are approximately 4 million lymphedema patients in the United States. A treatment for lymphedema exists in the form of compression garments and manual lymph massage, but the major limitation of this treatment is that there is an extremely narrow therapeutic window in which it can effectively reverse the disease. Current diagnostics cannot be implemented in a way to reliably detect lymphedema within this window. We will provide an affordable home-based diagnostic that can track limb volumes over time for early detection of lymphedema.

Technology basis.

     - Based on Microsoft Kinect sensor technology

     - Low price point and readily available

     - Employs state-of-the-art machine learning and signal processing techniques


Develop and field test a simple, ultra-low-cost portable technology using off-the-shelf Microsoft Kinect sensors to generate digital 3D models of a patient’s geometry to extract common and novel anthropometric values as well as motion data from scans that takes less than 60 seconds to collect, are non-invasive and contact-free, and do not require skilled (medical) personnel for operation and result interpretation.