Embedded & Pervasive Systems Lab

We research design, development, and validation of algorithms, tools, and technologies that enhance utilization and large-scale adoption of pervasive systems.

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Embedded & Pervasive Systems Lab

Research Lab

Washington State University

About EPSL

Medical embedded systems seamlessly connect human users to the physical world that is richly and invisibly interwoven with sensors, actuators, displays, and networks embedded in the everyday objects. The pervasive nature of such systems will transform the way people interact with each other and their environment and will revolutionize the way next generation medical services are provided. When realized properly, the resulting unparalleled information extracted from these systems enables emerging applications in mobile and remote healthcare, wellness, emergency response, fitness monitoring, elderly care support, long-term preventive chronic care, smart environments, gaming and sports.

The current focus of our research in the Embedded and Pervasive Systems Lab (EPSL) is on design, development, and validation of algorithms, tools, and technologies that enhance utilization and large-scale adoption of medical embedded systems. To validate and refine the new technology, we conduct clinical studies involving patients with heart failure, diabetes, cancer, visual impairment, and gait difficulties. Clinical studies are conducted in collaboration with partners from Elson S. Floyd College of Medicine, College of Nursing, College of Pharmacy, College of Education, and College of Agricultural, Human, and Natural Resource Science at WSU as well as our collaborators at Pullman Regional Hospital, UCLA School of Medicine, UCLA Stein Eye Institute, UC-Irvine Nursing Science, and Memorial Sloan Kettering Cancer Center (MSKCC). This end-to-end approach results in innovative, evidence-based and cost-conscious solutions for patients, doctors and medical centers.

Research Projects

Edema Monitoring

Monitoring Edema helps caregivers and patients to understand the state of the disease as well as the effectiveness of treatments. SmartSock is a wearable and context-aware prototype for intelligent in-home monitoring of edema. SmartSock is powered by advanced machine learning, …

Gait Monitoring

We develop novel approaches for reliable gait monitoring and investigate applications of wearable-base monitoring in various populations. The utility of wearable sensors for continuous gait monitoring has grown substantially, enabling novel applications on mobility assessment in …

Power-Aware System Design

The stringent constrained resources available on tiny sensor nodes introduce a number of challenges regarding accuracy, power-efficiency, user-comfort, and security. These design considerations, however, often impose conflicting requirements. Thus, a comprehensive research …

Computational Autonomy

Computational algorithms need to be reconfigured (i.e., retrained) upon any changes in configuration of wearable technologies, such as addition/removal of a sensor to/from the network, displacement/misplacement/mis-orientation of the sensors, etc. Re-training of these algorithms …

Recent Publications

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Dropout as an Implicit Gating Mechanism For Continual Learning

*Selected for oral presentation and received runner-up award in CVPR 2020 continual learning workshop

Optimal Policy for Deployment of Machine Learning Modelson Energy-Bounded Systems

With the recent advances in both machine learning and embedded systems research, the demand to deploy computational models for …

Recent & Upcoming Talks

Neural Tangent Kernel

Introduction to neural tangent kernel

Paper Review: Multi-modal Self-Supervised Learning for Human Activity Recognition

Review of self-supervised learning for human activity recognition

Paper Review: Lottery Ticket Hypothesis

Review of The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Members

Director

PhD Students

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Iman Mirzadeh

Research Assistant

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Ramesh Kumar Sah

Research Assistant

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Parastoo Alinia

Research Assistant

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Mahdi Pedram

Research Assistant

Alumni

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Marjan Nourollahi

Graduate Alumni

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Niloofar Hezarjaribi

Graduate Alumni

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Ramin Fallahzadeh

Graduate Alumni

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Ali Rokni

Graduate Alumni

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Yuchao Ma

Graduate Alumni

Contact

  • epsl@wsu.edu
  • 355 Spokane Street, Dana 114, Pullman, WA 99164