Developing novel methods to extract bladder and stomach muscle activity from new skin-surface wearable sensors
Sandya Subramanian, Professor
Computational Precision Health
Applications for Fall 2025 are closed for this project.
Our lab develops novel clinical-grade wearable sensors for at-home monitoring of chronic disease. We currently have or are in the process of developing new sensors for monitoring stomach muscle activity and bladder muscle activity from the surface of the skin, which would be a groundbreaking advance for many diseases, including functional digestive disorders, chronic pelvic pain, and complex neurological disorders like Parkinson’s and multiple sclerosis. Along with the hardware, we develop sophisticated methods and data analysis pipelines to extract the health-relevant information from these signals. These are electrical signals that are generated by the body, which can tell us something about a person’s health. We have an existing pipeline for stomach muscle activity; however, it requires refinement to be more robust to noise during continuous monitoring at home while people are moving around etc. We are developing a similar pipeline for bladder muscle activity, which has never been done before. This project presents a unique opportunity to work at the intersection of engineering, data analysis, physiology, and medicine and see the fruits of student efforts be validated for impact immediately.
Role: Task → Learning outcome
1. Assist with hardware prototyping → Gain familiarity with electronics and firmware
2. Assist with simple in-lab experimentation to collect test data → Gain familiarity with setting up data acquisition experiments using wearables on human subjects
3. Brainstorm and apply data cleaning and signal processing techniques on the resulting data to separate signal from noise → Gain experience applying techniques on real-world data
4. Help build first iteration of bladder muscle activity processing pipeline → Get in on the ground of proving scientific validity of a new approach (opportunities for intellectual property generation if genuinely innovative insights generated)
5. Troubleshoot and refine existing data analysis pipelines to improve signal quality and results of data analysis on human data → Generate and help interpret new insights about disease from human data using your own methods!
Qualifications: Required:
(1) Strong foundational understanding of basic electrical engineering and digital signal processing concepts for time series signals (e.g. FIR and IIR filtering, aliasing, Nyquist, signal-to-noise ratio, Fourier transform, spectral analysis, coupling, coherence, etc.)
(2) Previous experience having done signal processing and data analysis on some real-world data (beyond theory)
(3) Strong mathematical and statistical foundations, including multivariate calculus, linear algebra, differential equations, and probability and statistics
(4) Strong coding skills in Python (2+ years experience)
Desirable but not essential:
(1) Experience with hardware and/or firmware development
(2) Experience with Java and C coding
(3) Experience coding in Matlab
Hours: 9-11 hrs
Related website: https://subramanianlab.com/
Mathematical and Physical Sciences Engineering, Design & Technologies Biological & Health Sciences