Human Movement Biomechanics Lab in Engineering (HUMBLE) Projects
In the Human Movement Biomechanics Lab in Engineering (HUMBLE), we study patellar instability treatment and anterior cruciate ligament (ACL) injury prevention.
Patellar instability is a condition associated with partial or full dislocation of the patella (kneecap) and is common among adolescent athletes. Our ultimate goal is to guide personalized treatment and improve outcomes. Using real patient data, digital models, machine learning, and musculoskeletal simulations, we aim to identify the anatomical and biomechanical factors that contribute to patellar instability.
ACL injury is also common among adolescent athletes, particularly in sports with side-to-side movements. Our goal is to reduce ACL injury. We use motion capture data to study how coaching interventions may improve injury-reducing biomechanics.
We are searching for students to work on the following projects:
1. Determinants of patellar instability treatment outcomes. 30-50% of patellar instability treatments fail. Why? You will develop analysis pipelines and machine learning models to explore the patient demographic, imaging, biomechanical, and clinical factors associated with positive and negative treatment outcomes. View a representative poster here. Project-specific qualifications:
- Comfort with Python beyond CS5 (useful skills: matplotlib, numpy, pandas), Git, and the terminal
- Preferred but not required: experience in statistical modeling (scikit-learn)
- Eagerness to develop clinical knowledge and skills in statistical modeling
- Commitment to conduct research full-time and on campus from May 26-Aug 31 AND for 1-3 credits during each of Spring and Fall 2026.
2. Statistical shape model of knees with patellar instability. Just as a normal distribution can parameterize a single variable, a statistical shape model can parameterize 3D objects. You will label magnetic resonance images and use machine learning methods to enhance our preliminary statistical shape model. View a representative poster here. Project-specific qualifications:
- Comfort with Python beyond CS5 (useful skills: matplotlib, numpy, pandas), Git, and the terminal
- Experience with machine learning (scikit-learn)
- Eagerness to develop clinical knowledge and skills in statistical and 3D modeling
- Commitment to conduct research full-time and on campus from May 26-Aug 31 AND for 1-3 credits during each of Spring and Fall 2026.
3. Musculoskeletal simulations to determine patellar instability structure-function relationships. Simulations allow us to study how joint anatomies influence biomechanical outcomes. You will produce musculoskeletal simulations using digital reconstructions of patient knees to understand how varying anatomies are associated with knee bone movements and forces. View a representative poster here. Project-specific qualifications:
- Comfort with Python beyond CS5 (useful skills: matplotlib, numpy, pandas, scipy), Git, and the terminal
- Eagerness to develop clinical knowledge and skills in musculoskeletal simulation
- Commitment to conduct research full-time and on campus from May 26-Aug 31 AND for 1-3 credits during each of Spring and Fall 2026.
4. Effect of cueing on ACL injury prevention biomechanics. How do the instructions provided to athletes influence their movements and protect against injury? You will assist with movement data collection of Claremont-Mudd-Scripps athletes and will conduct data analysis. Project-specific qualifications:
- Comfort with Python beyond CS5 (useful skills: matplotlib, numpy, pandas), Git, and the terminal
- Eagerness to develop human performance knowledge and experimental and data analysis skills
- Commitment to conduct research for 2-3 credits during each of Spring and Fall 2026 (note: this project is unlikely to run over the summer).
Want to learn more? Stop by our lab space, Parsons B179, during the Engineering Research Open House on November 19, 5:30-6:30pm!
To apply: Please complete this form. Please also ensure that you apply through URO so that Prof. Sinopoli can view your information, transcript, resume, and reference (note: text in the application text section of the URO application will not be read). Form applications will not be reviewed unless you have submitted an application through the URO site.
The Human Movement Biomechanics Lab in Engineering aims to improve health, mobility, and quality of life across the lifespan by studying human movement and performance. Our research uses a variety of techniques from biomechanical data science, musculoskeletal simulation, wearable sensing, medical imaging, statistical modeling, and machine learning to maintain and restore movement, reduce injury, improve treatment, and enhance performance.