From September 2017 to January 2018 I worked on the Blood Pressure Imager, a joint project between the Laboratory for Human and Machine Haptics (TouchLab) at MIT, and the Tufts University School of Medicine.
The Blood Pressure Imager is wrist-based, beat-to-beat blood pressure monitor. It uses a technology called GelSight combined with an inflating cuff to analyze a high spatial- and time- resolution 3D reconstruction of the pulse through the radial artery at varying cuff pressures. Blood pressure measurements are calculated using a proprietary algorithm that is a combination of oscillometric and auscultatory methods, as well as new methods developed in-house that take advantage of additional information that the 3D images provide. The combination of methods used to calculate blood pressure provides readings that are more accurate and consistent than traditional oscillometric blood pressure cuffs. Using various methods also help to damp noise and artifacts that would otherwise dominate one specific measurement method.
As a research assistant and study coordinator, I had the opportunity to work on both technical challenges as well as interfacing directly with study volunteers.
The Blood Pressure Imager is wrist-based, beat-to-beat blood pressure monitor. It uses a technology called GelSight combined with an inflating cuff to analyze a high spatial- and time- resolution 3D reconstruction of the pulse through the radial artery at varying cuff pressures. Blood pressure measurements are calculated using a proprietary algorithm that is a combination of oscillometric and auscultatory methods, as well as new methods developed in-house that take advantage of additional information that the 3D images provide. The combination of methods used to calculate blood pressure provides readings that are more accurate and consistent than traditional oscillometric blood pressure cuffs. Using various methods also help to damp noise and artifacts that would otherwise dominate one specific measurement method.
As a research assistant and study coordinator, I had the opportunity to work on both technical challenges as well as interfacing directly with study volunteers.
- Coordinated and conducted a human subject study to validate, optimize, and test the Blood Pressure Imager
- Repaired or replaced mechanical and electrical components as needed. Modified device software in C++ as needed
- Collaborated with community partners to secure study locations and recruit participants
- Improved study protocol by standardizing methods for device mounting and preload to radial artery
- Formatted data collection and storage to allow for future simulation and analysis
- Designed and wrote a system using MATLAB that automates optimization of variable values and permutations to produce device calibration curves that improve with each new human subject dataset