Ryan Becker

RF Resonant Biosensing

For my graduate studies, I worked with Dr. Cluff on a NASA funded grant to develop a sensor for measuring biofluid shifts in microgravity. To accomplish this, I designed a planar spiral RF resonator to non-invasively measure multiple physiological conditions in the body. Developed as a flexible, conformable skin patch, the sensor exploits capacitive coupling to biological tissue to measure changes in the effective electromagnetic properties present in the body, such as those due to fluid volume changes. This approach provides a broad platform for measuring a number of important biometrics such as blood flow, blood pressure, intracranial pressure, bone density, blood glucose and cancer; all of the aforementioned conditions cause changes of the effective permittivity in the detection field of the sensor, and can be detected by measuring the scattering parameters the planar spiral produces.

In order to design the skin patch sensor, I synthesized tissue phantoms that mimicked the electrical properties of human tissues to determine the detection depth and geometric parameters needed to accurately measure pulsatile blood flow. I used the results from my phantom work to iteratively design a skin patch that could detect blood flow in a human, and tested the sensor response from a number of arterial sites on the body, ranging from superficial to deep. To measure time-varying information, such as blood volume shifts, scattering parameters were measured and plotted at a single frequency. The resulting waveforms closely resembled those obtained by photoplethysmograph (PPG), the sensors used in Fitbits and many of our phones. Unlike PPG sensors, our RF resonant sensors penetrate deep into the body and measure the actual change in arterial blood volume, providing a more accurate way to measure blood flow. We have conducted multiple large-scale human studies now to validate these sensor responses and demonstrate its ability for diagnosing disease and assessing the health of individuals.

Raman Spectral Analysis of Ischemic Muscle from Peripheral Artery Disease (PAD) Patients

Peripheral artery disease is a serious cardiovascular disease that affects many of us as we get older. Identified as arterial blockages that reduce blood flow to our lower limbs, the disease can cause serious damage to our legs, and can even result leg amputation if it gets severe enough. With modern medicine physicians have had more success screening and diagnosing the condition, however often times even when the blockages are removed muscle damage still occurs and the patients still need an amputation! Unfortunately there are no screening methods for muscle damage until it is too late, and the mechanisms for the damage are currently unknown. My research set out to answer the question as to why this was occurring, and help create better therapies for PAD by finding key spectral biomarkers in the muscle caused by the disease using spectroscopy.

Finding a new biomarker for a disease is like trying to find a needle in a haystack, in a room full of hundreds of haystacks: it is extremely difficult, and many scientists will theorize a mechanism and spend the rest of their career attempting to validate their hypothesis. My approach was to use a label-free techniques to search for biomarkers in a broad-based manner, as opposed to the more narrow approach many biochemists employ. This was accomplished by measuring the changes in key spectral peaks that are identified as specific cell components, and applying multivariate statistical methods to provide a larger picture of the overall disease progression at a cellular level and identify candidate biomarkers for PAD-induced muscle damage.

I explored Raman spectroscopy, ATR-FTIR spectrscopy, and energy dispersive X-ray spectroscopy to provide different biochemical aspects of the damaged muscle cells. Raman and FTIR spectroscopy detect complimentary chemical bonds in a material, and X-ray spectroscopy illustrates the changes in elemental concentrations; by applying machine learning to each method, a comprehensive map of the disease progression was able to be obtained, and highlighted potential mechanisms for muscle damage caused by PAD. Many of the changes in cell constituents suggested mitochondrial damage, which is now being targeted as a primary biomarker for chronically ischemic muscle damage. This study not only provided a foundation for developing targeted therapeutics, it also demonstrated the potential for using statistically driven screening methods for muscle damage at an early stage.