Momona Yamagami

HCI Researcher - PhD Candidate


Headshot of a person with round glasses and short, black hair.

I am a final year PhD student at the University of Washington in Seattle, WA, advised by Profs. Kat Steele and Sam Burden. I am currently on the faculty job market and am looking for positions in the Texas and Lousiana areas. My research focuses on modeling and enhancing human-machine interaction (HMI) to support accessibility and health using biosignals and control theory applied to the field of HCI (human-computer interaction).

My dissertation research leverages control theory methods to model and enhance continuous HMIs and explore biosignals like electromyography (EMG) as accessible machine inputs for people with and without disabilities. My current research interests include how multi-input biosignals can improve HMI accessibility for new and emerging technology like virtual reality and support the health of people with disabilities. with disabilities.

I have received fellowships from the University of Washington Institute for Neuroengineering and the University of Washington College of Engineering. I am a 2021 University of Washington College of Engineering Student Research Award recipient.

Research


Decoding Intent With Control Theory: Comparing Muscle Versus Manual Interface Performance

Manual device interaction requires precise coordination which may be difficult for users with motor impairments. Muscle interfaces provide alternative interaction methods that may enhance performance, but have not yet been evaluated for simple (eg. mouse tracking) and complex (eg. driving) continuous tasks. Control theory enables us to probe continuous task performance by separating user input into intent and error correction to quantify how motor impairments impact device interaction. We compared the effectiveness of a manual versus a muscle interface for eleven users without and three users with motor impairments performing continuous tasks. Both user groups preferred and performed better with the muscle versus the manual interface for the complex continuous task. These results suggest muscle interfaces and algorithms that can detect and augment user intent may be especially useful for future design of interfaces for continuous tasks.

Modeling Intent and Error Correction During Continuous Interactions

Deriving user intent from continuous interactions like mouse navigation or driving a car is a complicated modeling task. I use methods from control theory to model intent (feedforward control) and error correction (feedback control) for a one-dimensional trajectory-tracking task to compare learned controllers between the dominant and non-dominant hands.

Publications


2021

"I'm Just Overwhelmed": Investigating Physical Therapy Access and Technology Design Recommendations for People with Disabilities and/or Chronic Conditions
Momona Yamagami, Kelly Mack, Jennifer Mankoff, Katherine Steele
Under Review in the ACM Transactions on Human Factors in Computing Systems (CHI 2022)

"That's Frustrating": Stakeholder Perceptions of Provision, Use, and AFO Needs for People with Cerebral Palsy
Nicole Zaino, Momona Yamagami, Deborah Gaebler-Spira, Katherine Steele, Kristie Bjornson, Heather Feldner.
Under Review in Prosthetics and Orthotics International

Two-in-One: A Design Space for Mapping Unimanual Input into Bimanual Interactions in VR for Users with Limited Movement
Momona Yamagami, Sasa Junuzovic, Mar Gonzalez Franco, John Porter, Eyal Ofek, Edward Cutrell, Andrew Wilson, Martez Mott.
Under Review in the ACM Transactions on Accessible Computing (TACCESS)

Impact of Virtual Reality Doorway and Hallway Environments on Gait Kinematics in People with Parkinson Disease and Freezing
Amir Besharat, Sheri Imsdahl, Momona Yamagami, Nawat Nhan, Olivia Bellatin, Samuel Burden Kathleen Cummer, Sujata Pradhan, Valerie Kelly.
Under Review in Gait & Posture

Effect of Handedness on Learned Controllers and Sensorimotor Noise During Trajectory-Tracking
Momona Yamagami, Lauren N. Peterson, Darrin Howell, Eatai Roth, Samuel A. Burden.
IEEE Transactions on Cybernetics 2021 | Link

2020

Effects of Virtual Reality Environments on Overground Walking in People with Parkinson Disease and Freezing of Gait
Momona Yamagami, Sheri Imsdahl, Olivia Bellatin, Nawat Nhan, Samuel A Burden, Sujata Pradhan, Valerie E Kelly
Disability and Rehabilitation: Assistive Technology 2020. | Link

Decoding Intent With Control Theory: Comparing Muscle Versus Manual Interface Performance
Momona Yamagami, Katherine M Steele, Samuel A Burden
In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2020), 2020. | Link | Video

2019

Experiments with Sensorimotor Games in Dynamic Human/Machine Interaction
Benjamin Chasnov, Momona Yamagami, Behnoosh Parsa, Lillian J Ratlif, Samuel A Burden
Micro- and Nanotechnology Sensors, Systems, and Applications XI, International Society for Optics and Photonics | Link

2018

Assessment of Dry Epidermal Electrodes for Long-Term Electromyography Measurements
Momona Yamagami, Keshia M Peters, Ivana Milanovic, Irene Kuang, Zeyu Yang, Nanshu Lu, Katherine M Steele
Sensors | Link

Contributions of Feedforward and Feedback Control in a Manual Trajectory-Tracking Task
Momona Yamagami, Darrin Howell, Eatai Roth, Samuel A Burden
2nd IFAC Conference on Cyber-Physical & Human Systems | Link

Teaching


Control System Analysis I

ECE 447, UW

This is a senior-level control system course focusing stability of feedback systems by root locus and frequency-response methods at the University of Washington. I was a teaching assistant for this class in Fall 2019 (in-person), Spring 2020 (remote) and was an instructor during Spring 2021 (remote).