Details below:
Infant Movements Analysis
Title: Analyzing Infant Movements using Kinect V2 Depth Camera
Description: Cerebral palsy is the most common pediatric movement disorder and is caused by an injury to the brain near the time of birth. However, injuries to the brain near birth often go undetected and the average age of cerebral palsy diagnosis remains 19 months of age. Early detection of cerebral palsy and other developmental disorders is crucial for early intervention and preventing long term movement impairments and musculoskeletal deformities. Prior research has demonstrated that analysis of general or fidgety movements in the first months of life can be a useful predictor of development and cerebral palsy. The main goal of this research is to evaluate if depth or RGB data can be used to detect impaired movements from an early stage using computer vision and machine learning techniques. We will collaborate with Nationwide Children’s Hospital and Seattle Children’s Hospital in all stages of this project.
We are looking for a highly motivated student to assist with development, testing, and data analysis. They will work closely with our research laboratory and clinical partners. The student will earn research credit based on his/her contribution.
Minimum Requirements: Undergraduate or Master’s Students in Computer Science with Computer Vision experience.
To Learn More:
Features for Movement Prediction of Cerebral Palsy
Method to Predict Infantile Cerebral Palsy
Identification of Fidgety Movements
Optical Flow Applied to Infant Movement
Assessment of Specific Characteristics of Abnormal General Movements
Fetal and Infant Spontaneous General Movements
General Movements as a Predictive Tool of Neurologic Outcomes
If you are interested in this project, please send your resume and a short description of your interest, career goals, and relevant skills to:
Contact name: Bilge Soran & Keshia Peters
Contact email: bilge@cs.washington.edu & rumbek@uw.edu
_____________________________________________________________________________________________________________
Hand Function Analysis
Title: Comparing hand function in cerebral palsy (CP) using Intel Depth Camera
Description: The most common surgical procedure by hand surgeons in cerebral palsy is for the thumb-in-palm deformity. Clinicians often use qualitative means to determine whether or not to use surgical intervention as a treatment. The overall goal of this research is to provide clinicians with objective treatment suggestions based on a quantitative evaluation. Such a system can be achieved by applying machine learning techniques that help distinguish different cases. Sub-goals include testing the system against clinical findings and creating a user friendly GUI for the clinician’s use.
We are looking for a highly motivated student to assist with development, testing, and data analysis. They will work closely with our research laboratory and clinical partners at Gillette Children’s Specialty Healthcare.
Minimum Requirements: Undergraduates in Computer Science with Computer Vision experience. We expect students to be able to commit to a minimum of three quarters and 10 hours/week.
To Learn More:
Upper extremity surgical treatment within cerebral palsy population
If you are interested in this project, please send your resume and a short description of your interest, career goals, and relevant skills to:
Contact name: Bilge Soran & Keshia Peters
Contact email: bilge@cs.washington.edu & rumbek@uw.edu