Cornell University
Library
Cornell UniversityLibrary

eCommons

Help
Log In(current)
  1. Home
  2. Cornell University Graduate School
  3. Cornell Theses and Dissertations
  4. Mobile Sensing through Vibration: Listening to Health Signals with Acoustic and Electromagnetic Waves

Mobile Sensing through Vibration: Listening to Health Signals with Acoustic and Electromagnetic Waves

File(s)
Rahman_cornellgrad_0058F_10582.pdf (17.29 MB)
Permanent Link(s)
https://doi.org/10.7298/X47P8WKR
https://hdl.handle.net/1813/59033
Collections
Cornell Theses and Dissertations
Author
Rahman, Tauhidur
Abstract

Vibration is ubiquitous in the human body and its surrounding environment. Many internal physiological processes in our body produce subtle vibrations with different frequencies, which carry representative information about the state of our health. Similarly, characteristics of externally induced vibrations in our surrounding material environment can be indicative of whether any materials or chemicals can pose threats to our health. In my research, I exploit acoustic waves, electromagnetic waves, and their interactions to develop mobile systems that passively and unobtrusively listen to underlying health signals. Despite the rapid growth of mobile health applications in recent years, many of these health sensing modalities remain largely untapped. In this dissertation, I will present my recent and ongoing research to demonstrate how naturally generated and backscattered acoustic and electromagnetic waves from the human body (e.g., heart, lung, skin) and its surrounding material environment (e.g., food) can be used to infer intermediate health signals like physiological acoustics, vital signs, and spectral properties of materials. I will also describe how these signals can be mapped to high-level health and behavioral variables including non-speech body sound, sleep stages, and food quality. Finally, I will lay out my future plans to develop low-cost next-generation mobile health systems for individualized and community-wide healthcare.

Date Issued
2017-12-30
Keywords
Electrical engineering
•
Information science
•
Computer science
•
Mobile Health
•
machine learning
•
Food Quality Monitoring
•
Ubiquitous Computing
•
Physiological Acoustics
•
Sleep Sensing
Committee Chair
Choudhury, Tanzeem K.
Committee Member
Erickson, David
Estrin, Deborah
Jung, Malte
Degree Discipline
Information Science
Degree Name
Ph. D., Information Science
Degree Level
Doctor of Philosophy
Type
dissertation or thesis

Site Statistics | Help

About eCommons | Policies | Terms of use | Contact Us

copyright © 2002-2026 Cornell University Library | Privacy | Web Accessibility Assistance