Brinnae Bent

Ph.D. Candidate, Biomedical Engineering

Bridging the gap between healthcare, data science, and engineering, my research allows medical care to be a collaborative effort between healthcare professionals and patients, using wearable devices, health informatics, and mHealth technologies. It is my goal to discover data-driven approaches to make healthcare more accessible. 

My passion for biomedical engineering stems from my role as a certified nurse aide at both an Alzheimer's nursing home and with Cerebral Palsy of Mideast Wisconsin back in high school and undergraduate. I developed an interest in wearable devices working in the iBionicS Lab, developing hardware, data analysis procedures, and clinical programs. My PhD in the BIG IDEAS Lab has transitioned into utilizing data from these wearable devices to make actionable decisions with data analytics and machine learning.

Outside of research, I am a passionate educator to K-100 learners. When not in the lab, I can be found teaching an engineering class to senior citizens, tutoring with Mindspire Tutoring, or substitute teaching at NCSSM.

I am a full-fledged adventurer. I frequently go backpacking on primitive trails, summit mountains, compete in ultra-running races, and participate in a range of adventure sports. My favorite spot in Durham is Umstead State Park.

Contact Information

  • Office Location: Hock Plaza 9048
  • Email Address:


  • M.S. Biomedical Engineering, Duke University (2018)
  • B.S. Biomedical Engineering, North Carolina State University (2016)

Research Interests


Discovering Digital Biomarkers of Glycemic Heath from Wearable Sensors

Current Projects:

Past Projects:

  • Machine Learning to Predict Lower Extremity Musculoskeletal Injury Risk in Student Athletes (led team 2019, paper in revisions)
  • Optimizing Sampling Rate of Wrist-worn Optical Sensors for Physiologic Monitoring (published, 2020)
  • Investigating Sources of Inaccuracy in Wearable Optical Heart Rate Sensors (published, 2020)
  • EventDTW - Dynamic Time Warping Algorithm (published, 2020)
  • V3 Framework for Determining Fit-for-Purpose Biometric Monitoring Technologies (published, 2020)
  • Developing a mobile application for asthma management using FHIR HL7 Standards (First prize, HL7 FHIR Global Hackathon, 2019)
  • Simultaneous recording and stimulation during Spinal Cord Stimulation and Dorsal Root Ganglion Stimulation (published, 2019)
  • Analysis of micro-ECoG in epilepsy applications
  • Developing, testing, and implementing protocol for clinical research of various electrodes and systems
  • Assessed chronic reliability of electrode arrays in freely-moving rats (published, 2018, 2020)
  • Developed photoplethysmograph (PPG) probe for chronic respiratory monitor (NSF ASSIST Center) (published, 2015, 2016)
  • Worked on the design of the SleepiBand, a wearable sleep monitoring system (iBionicS Lab) (patent pending, 2016)
  • Coded GUI for clinical studies of the SleepiBand (iBionicS Lab)
  • Created sleep apnea mouthguard monitor (RiOT Hackathon)
  • Developed Premature Ventricular Contraction (PVC) heart monitor (published, 2016)