The objective of this research is to develop methods and tools for a multimodal and multi-sensor assessment and rehabilitation game system called CPLAY for children with Cerebral Palsy (CP). CPLAY collects and processes multiple types of stimulation and performance data while a child is playing. Its core has a touch-screen programmable game that has various metrics to measure delay of response, score, stamina/duration, accuracy of motor/hand motion. Optional devices attached to extend CPLAY versions provide additional parallel measurements of level of concentration/participation/engagement that quantify rehabilitation activity. The approach is to model the process as a cyber-physical system (CPS) feedback loop whereby data collected from various physical 3D devices (including fNIR brain imaging) are processed into hierarchical events of low-to-high semantic meaning that impact/ adjust treatment decisions. Intellectual Merit: The project will produce groundbreaking algorithms for event identification with a multi-level data to knowledge feedback loop approach. New machine learning, computer vision, data mining, multimodal data fusion, device integration and event-driven algorithms will lead towards a new type of cyber- physical rehabilitation science for neurological disorders. It will deliver fundamental advancements to engineering by showing how to integrate physical devices with a computationally quantitative platform for motor and cognitive skills assessment. Broader Impacts: The project delivers a modular & expandable game system that has huge implications on the future of US healthcare and rehabilitation of chronic neurological disabilities. It brings hope to children with Cerebral Palsy via lower cost and remote rehabilitation alternatives. It brings new directions to human centered computing for intelligent decision-making that supplements evidence-based practices and addresses social and psychological isolation problems.

The objective of this research is to understand the loosely coupled networked control systems and to address the scientific and technological challenges that arise in their development and operation. The approach is to (1) develop a mathematical abstraction of the CPS, and an online actuation decision model that takes into account temporal and spatial dependencies among actions; (2) develop algorithms and policies to effectively manage the system and optimize its performance with respect to applications' QoS requirements; and (3) develop an agent-based event-driven framework to facilitate engineers easily monitor, (re)configure and control the system to achieve optimized results. The developed methodologies, algorithms, protocols and frameworks will be evaluated on testbeds and by our collaborating institution. The project provides fundamental understanding of loosely coupled networked control systems and a set of strategies in managing such systems. The components developed under this project enables the use of wireless-sensor-actuator networks for control systems found in a variety of disciplines and benefits waterway systems, air/ground transportation systems, power grid transmission systems, and the sort. The impact of this project is broadened through collaborations with our collaborating institution. This project provides a set of strategies and tools to help them meet the new standards. The inter-disciplinary labs and curriculum development at both undergraduate and graduate level with an emphasis on CPS interdisciplinary applications, theoretical foundations, and CPS implementations prepare our students as future workforce in the area of CPS applications.

The objective of this research is the creation of a coastal observing system that enables dense, in situ, 4D sensing through networked, sensor-equipped underwater drifters. The approach is to develop the technologies required to deploy a swarm of autonomous buoyancy controlled drifters, which are vehicles that can control their depth, but are otherwise carried entirely by the ocean currents. Such Lagrangian sampling promises to deliver a wealth of new data, ranging from applications in physical oceanography (mapping 3D currents), biology (observing the dispersion of larvae and nutrients), environmental science (tracking coastal pollutants and effluents from storm drains), and security (monitoring harbors and ports). This observing system fundamentally requires accurate positions of the drifters (to interpret the spatial correlations of data samples), swarm control algorithms (to achieve desired sampling topologies), and wireless communication (to coordinate between the individual drifters). This research will create distributed techniques to self-localize the drifter swarm, novel swarm control algorithms that enable topology manipulation while purely leveraging the stratified flow environment, and efficient wireless underwater communication for information sharing. This project has significant societal impact and educational elements. Underwater drifter swarms will enable novel insights into a wide array of scientific questions, including understanding plankton transport, accumulation and dispersion as well as monitoring harmful algal blooms. Undergraduates will play an active role in many aspects of this project, thereby offering them a uniquely interdisciplinary experience. Finally, outreach to high school students will occur through the UCSD COSMOS summer program.