What: I developed and deployed a high-resolution, reproducible, and accessible (to clinicians and patients) smartphone-based platform that can be used for early identification and monitoring of individuals who are at risk of developing complications from diabetic peripheral neuropathy (DPN), a common complication that affects half of all individuals with diabetes.
My specific roles:
Reverse-engineered smartphones, characterized smartphone vibrations, and tuned their governing parameters to measure clinically relevant sensory response. Independently built and led clinical collaborations with multiple endocrinologists, neurologists, and primary care physicians at Stanford Hospital. Designed and conducted user studies in over 150 adults with varying DPN risk levels. Directed a team of researchers to assist with participant recruitment and data collection. Established the foundation for predictive metrics by performing statistical tests (multivariable regressions, ANOVAs, etc.) and data visualizations to analyze the relationship between relevant electronic health record (EHR), health survey, and smartphone-based sensory perception data. Our biologically-relevant multivariable regression suggests that certain markers of DPN progression correlate with the sensory data, collected using our platform and processed using custom sensor signal-processing scripts. Won grants to fund the project: Stanford Center for Digital Health ($50k, wrote grant and submitted independently), Stanford Precision Health and Integrated Diagnostics ($200k, contributed figures and text), Stanford Diabetes Research Center ($25k, contributed figures and text). Presented project findings at various peer-reviewed conferences, seminars, and journals.
Skills: Mobile Health Technologies Research Design, Execution, and Analysis | Signal processing and analysis (esp. related to health sensing, mobile devices, and wearables) | Data Visualization | Building and leading collaborations between engineers and clinicians | Technical writing and presenting
Lessons: Always check for edge-cases. Humans are quite variable!
Awards: National Science Foundation Graduate Research Fellow, Stanford Graduate Fellow (Medtronic Foundations Fellow)
Publications and Presentations:
R. A. G. Adenekan, K. T. Yoshida, A. Benyoucef, A. Gonzalez Reyes, A. E. Adenekan, A. M. Okamura, and C. M. Nunez (2024) Reliability of Smartphone-Based Vibration Threshold Measurements. IEEE Haptics Symposium. URL: https://ieeexplore.ieee.org/document/10520838
R. A. G. Adenekan, A. Gonzalez Reyes, K. T. Yoshida, S. Kodali, A. M. Okamura, and C. M. Nunez (2024) A Comparative Analysis of Smartphone and Standard Tools for Touch Perception Assessment Across Multiple Body Sites. IEEE Transactions on Haptics.
URL: ieeexplore.ieee.org/abstract/document/10420501
R. A. G. Adenekan, A. Gonzalez Reyes, K. T. Yoshida, A. M. Okamura†, and C. M. Nunez† (2023) Vibration Sensory Threshold Measurement Using Mobile Devices. At Stanford eWear Annual Meeting Symposium, Poster.
K. T. Yoshida*, J. X. Kiernan*, R. A. G. Adenekan, S. H. Trinh, A. J. Lowber, A. M. Okamura†, and C.M. Nunez† (2023) Cognitive and Physical Activities Impair Perception of Smartphone Vibrations. In IEEE Transactions on Haptics.
URL: https://ieeexplore.ieee.org/abstract/document/10132042
R. A. G. Adenekan, A. J. Lowber, B. N. Huerta, A. M. Okamura, K. T. Yoshida†, and C. M. Nunez† (2022) Vibration Sensory Threshold Measurement Using Mobile Devices. In BioRobotics, Late-Breaking Abstract.
R. A. G. Adenekan, A. J. Lowber, B. N. Huerta, A. M. Okamura, K. T. Yoshida†, and C. M. Nunez† (2022) Feasibility of Smartphone Vibrations as a Sensory Diagnostic Tool. In EuroHaptics, Work-in-Progress.
URL: https://books.google.com/books?hl=en&lr=&id=tq1wEAAAQBAJ&oi=fnd&pg=PA337&dq=info:lrADC_5FYV4J:scholar.google.com&ots=3q91HIzP6i&sig=lxl8mL08vOx0PC3gieHgHWaZ3Ow#v=onepage&q&f=false
My specific roles:
Reverse-engineered smartphones, characterized smartphone vibrations, and tuned their governing parameters to measure clinically relevant sensory response. Independently built and led clinical collaborations with multiple endocrinologists, neurologists, and primary care physicians at Stanford Hospital. Designed and conducted user studies in over 150 adults with varying DPN risk levels. Directed a team of researchers to assist with participant recruitment and data collection. Established the foundation for predictive metrics by performing statistical tests (multivariable regressions, ANOVAs, etc.) and data visualizations to analyze the relationship between relevant electronic health record (EHR), health survey, and smartphone-based sensory perception data. Our biologically-relevant multivariable regression suggests that certain markers of DPN progression correlate with the sensory data, collected using our platform and processed using custom sensor signal-processing scripts. Won grants to fund the project: Stanford Center for Digital Health ($50k, wrote grant and submitted independently), Stanford Precision Health and Integrated Diagnostics ($200k, contributed figures and text), Stanford Diabetes Research Center ($25k, contributed figures and text). Presented project findings at various peer-reviewed conferences, seminars, and journals.
Skills: Mobile Health Technologies Research Design, Execution, and Analysis | Signal processing and analysis (esp. related to health sensing, mobile devices, and wearables) | Data Visualization | Building and leading collaborations between engineers and clinicians | Technical writing and presenting
Lessons: Always check for edge-cases. Humans are quite variable!
Awards: National Science Foundation Graduate Research Fellow, Stanford Graduate Fellow (Medtronic Foundations Fellow)
Publications and Presentations:
R. A. G. Adenekan, K. T. Yoshida, A. Benyoucef, A. Gonzalez Reyes, A. E. Adenekan, A. M. Okamura, and C. M. Nunez (2024) Reliability of Smartphone-Based Vibration Threshold Measurements. IEEE Haptics Symposium. URL: https://ieeexplore.ieee.org/document/10520838
R. A. G. Adenekan, A. Gonzalez Reyes, K. T. Yoshida, S. Kodali, A. M. Okamura, and C. M. Nunez (2024) A Comparative Analysis of Smartphone and Standard Tools for Touch Perception Assessment Across Multiple Body Sites. IEEE Transactions on Haptics.
URL: ieeexplore.ieee.org/abstract/document/10420501
R. A. G. Adenekan, A. Gonzalez Reyes, K. T. Yoshida, A. M. Okamura†, and C. M. Nunez† (2023) Vibration Sensory Threshold Measurement Using Mobile Devices. At Stanford eWear Annual Meeting Symposium, Poster.
K. T. Yoshida*, J. X. Kiernan*, R. A. G. Adenekan, S. H. Trinh, A. J. Lowber, A. M. Okamura†, and C.M. Nunez† (2023) Cognitive and Physical Activities Impair Perception of Smartphone Vibrations. In IEEE Transactions on Haptics.
URL: https://ieeexplore.ieee.org/abstract/document/10132042
R. A. G. Adenekan, A. J. Lowber, B. N. Huerta, A. M. Okamura, K. T. Yoshida†, and C. M. Nunez† (2022) Vibration Sensory Threshold Measurement Using Mobile Devices. In BioRobotics, Late-Breaking Abstract.
R. A. G. Adenekan, A. J. Lowber, B. N. Huerta, A. M. Okamura, K. T. Yoshida†, and C. M. Nunez† (2022) Feasibility of Smartphone Vibrations as a Sensory Diagnostic Tool. In EuroHaptics, Work-in-Progress.
URL: https://books.google.com/books?hl=en&lr=&id=tq1wEAAAQBAJ&oi=fnd&pg=PA337&dq=info:lrADC_5FYV4J:scholar.google.com&ots=3q91HIzP6i&sig=lxl8mL08vOx0PC3gieHgHWaZ3Ow#v=onepage&q&f=false