Bioimpedance sensing to characterization osteoarthritis knee-tissue alterations
Faculty Mentor: Todd Freeborn (Electrical and Computer Engineering)
Osteoarthritis is the most common chronic illness and the leading cause of pain and disability among older adults. Sensors to monitor joints and tissues supports tracking disease progression, identifying events that contribute to pain, and evaluating how people respond to therapy.
Teachers will 1) learn about knee tissue physiology, 2) they will measure knee tissue electrical impedance using lab instruments (Keysight E4990A precision impedance analyzer) and wearable sensors; 3) write code to generate visual figures of tissue impedance data, and 4) will analyze and interpret impedance data to answer a research question (e.g. How does knee tissue impedance change during flexion of the knee joint?).
Exploring Physiological Computing Through Modern Web Technologies
Faculty Mentor: Chris Crawford (Computer Science)
Physiological sensing involves the measurement of bio-electrical signals from the body. These signals can measure activity associated with brain (EEG), heart (ECG/EKG), muscles (EMG),
and sweat glands (GSR). Studies on learning featuring physiological sensors have primarily used physiological data to evaluate students’ attention levels, mental effort, anxiety, cognitive load, programming, and learning experience. Other work has aimed to enhance learners’ experiences through closed-loop systems that adapt the learning environment based on learners’ psychophysiological states.
Teachers will 1) learn about physiological sensors and the different aspects of the body they can measure; 2) learn how to use NeuroBlock, a web-based platform for physiological computing education, to collect, filter, and visualize physiological data, 3) measure EEG signals using open-source electronics, and 4) analyze and interpret EEG data to answer a research question (e.g. How does EEG data change during different learning activities?).
Capacitive sensing for breathing assessments with dielectric composites
Faculty Mentor: Amanda Koh (Chemical and Biological Engineering)
Dysfunctional breathing is a challenge that many face due to illness, surgery, or injury. Designing soft, deformable wearable sensors will enable dysfunctional breathing patients and healthcare providers to quantify muscle patterns that demonstrate improved breath control and volume.
Teachers will 1) learn about capacitive sensor materials, 2) measure the electromechanical response of novel dielectric composites using lab instruments (Keysight E4990A precision impedance analyzer and Instron Universal Mechanical Tester), 3) write MATLAB code to organize and visualize capacitive sensor data, and 4) analyze interpret collected data to answer a research question (e.g. How does the capacitive material impedance change when different amounts of pressure are applied?).
Radar measurements to sense changes in body positions and identify falls
Faculty Mentor: Sevgi Gurbuz (Electrical and Computer Engineering)
Fall-related accidents are among the most serious problems facing older adults. Data from quantitative 3D gait analysis in laboratories with motion capture devices can investigate fall risk but limits real-time monitoring in settings where those at risk of falls live. One approach to overcome this is the use of radio frequency (RF) sensors for continuous monitoring in real-life settings. This can support investigation of day-to-day variations in gait, is time efficient, and provides a realistic picture of older adults’ mobility.
Teachers will 1) learn how radar signals can be used to measure objects and people, 2) measure participants using radio-frequency (e.g. radar) sensors during daily living activities (walking, sit-to-stand, stand-to-sit, etc.), 3) write code to organize and visualize radar data, 4) analyze and interpret collected data to answer a research question (e.g. how does the speed of walking change measured radar data?).
Gait and posture measurements using inertial sensors and model-based filtering
Faculty Mentor: Vishesh Vikas (Mechanical Engineering)
Monitoring of human gait and posture is often performed in controlled environments requiring motion capture systems. These provide the user/patient with limited motion capability in a constrained environment. With the increasing availability of low-cost inertial measurement sensors (IMUs) and significant data processing available with low-power, small size hardware; wearable methods for monitoring gait and posture are increasing in interest but require model-based data filtering for accurate estimation and management of sensor inaccuracies.
Teachers will 1) learn how IMUs can be used to measure motion; 2) collect IMU data using simple microcontrollers during different activities (sitting, standing, walking, climbing stairs), 3) write code to organize and visualize IMU data, 4) analyze and interpret data to answer a research question (e.g. how much does IMU data drift over time during extended periods of sitting?).
Electrical sensors to measure bladder sensation and function
Faculty Mentor: Mark Cheng (Electrical and Computer Engineering)
The capability to monitor bladder pressure and urine volume can assist 25 million patients in the US with urinary incontinence. There is hope to restore bladder function when combing sensing capabilities and closed-loop electrical stimulation for treatments. Given the tight range of physiological pressure in bladders (14.7~19.7 psi), it is necessary to design electrical sensors with high sensitivity and robustness for this range.
Teachers will 1) learn bladder physiology with a focus on bladder filling/voiding, 2) measure the electrical properties of bladder tissue phantoms using lab instrumentation (Agilent E5071C network analyzer) and micro electromechanical systems (MEMS), 3) write code to organize and visualize the electrical circuit properties of tissues (Bode plot, Smith chart), 4) analyze and interpret data to answer a research question (e.g. how does the electrical circuit properties change based on the sensor insertion depth?)
Underwater robots for sensing and characterization of ocean environments
Faculty Mentor: Aijun Song (Electrical and Computer Engineering)
The increasing utilization of ocean resources for both commercial and environment activities is increasing the need for under-water sensors, autonomous submerged vehicles, and underwater communications. For underwater communications, robust channel estimation poses a great research challenge in coherent communication, and is critical so that ocean environmental data (e.g. temperature, currents, pollution) can be reliably reported and analyzed.
Teachers will 1) learn about the sensors that underwater robotics use to monitor local water conditions; 2) write code to control SeaMATE ROV underwater robotic hardware (motors for location and depth); 3) measure position, temperature, and depth of robotic hardware in controlled lab conditions, 3) write code to organize and visualize collected underwater data; and 4) analyze and interpret data to answer a research question (e.g. how does the transmission speed of communication impact the reliability and accuracy of transmit data underwater?)
Measuring the Maturity of Concrete
Faculty Mentor: Armen Amirkhanian (Civil, Construction, and Environmental Engineering)
Concrete is the most used material in the world. We build buildings, bridges, and pavements all over the world with this amazingly versatile material. However, time is money and fast construction benefits both the contractor and the general public as projects can open sooner and with less delays. Specifically with concrete pavements, getting onto the pavement as soon as possible is critical for completing projects quickly. It has been a challenge balancing the “early opening” of the pavement against the strength it has and the damage that might occur. However, by measuring the maturity of the pavement with cheap and disposable temperature sensors, we can have real-time data to know the exact minute that we can start driving on a new concrete pavement.
Teachers will 1) learn the basics of concrete materials and how to make small scale mixtures in the classroom; 2) learn how to read, interpret, and teach construction specifications and code; 3) measure the temperature of different concrete materials over time using inexpensive, “off-the-shelf” parts; 4) analyze and interpret the temperature data to make an informed decision of when a vehicle would be allowed onto concrete pavement.