Millions of mobile applications (apps) are being developed in domains such as energy, health, security, and entertainment. The US FDA expects that there will be 500 million smart phone users downloading healthcare related apps by the end of 2015. Many of these apps will perform interventions to control human physiological parameters such as blood pressure and heart rate. The intervention aspects of the apps can cause dependency problems, e.g., multiple interventions of multiple apps can increase or decrease each other’s effects, some of which can be harmful to the user.

Security and privacy concerns in the increasingly interconnected world are receiving much attention from the research community, policymakers, and general public.  However, much of the recent and on-going efforts concentrate on privacy in communication and social interactions.  The advent of cyber-physical systems, which aim at tight integration between distributed computational intelligence, communication networks, physical world, and human actors, opens new possibilities for developing intelligent systems with new capabilities.

Episodic brain disorders such as epilepsy have a considerable impact on a patient’s productivity and quality of life and may be life-threatening when seizures cannot be controlled with medications. We will create a second generation brain-implantable sensing and stimulating device (BISSD) based on CPS principles and practice. The BISSD will be composed of modules placed intracranially to continuously monitor brain state and vulnerability to seizure and intervene with electrical stimulation to block the development of seizure.

The broad goal of this project is to advance both the foundations and the enabling technologies in the field of human-machine systems, with a focus on exercise and rehabilitation machines. One of the motivations of our project is the observation that advances in exercise devices are mostly seen in their haptic interfaces rather than their intrinsic capabalities. Also, our collaboration with NASA on exercise machines for astronauts has motivaed us to investigate this aspect of human-machine interaction.

We present a bifurcation analysis of electrical alternans in the two-current Mitchell-Schaeffer (MS) cardiac-cell model using the theory of -decidability over the reals. Electrical alternans is a phenomenon characterized by a variation in the successive Action Potential Durations (APDs) generated by a single cardiac cell or tissue.

This project is a modular multi-robot cyber-physical system (CPS) for assisting young developmentally-delayed children learn to walk. The challenges of assisting young developmentally-delayed children learn to walk are 1) stabilizing medio-lateral body movement; and 2) developing gait that exploits potential and kinetic energy exchange. Typically, adults help children learn to walk by providing support that enables them to safely explore the environment.

Optimization algorithms used in a real-time and safety-critical context offer the potential for considerably advancing robotic and autonomous systems by improving their ability to execute complex missions. However, this promise cannot happen without proper attention to the considerably stronger operational constraints that real time, safety-critical applications must meet, unlike their non-real-time, desktop counterparts.

This exhibition presents two projects. The first project is a framework and associated tooling for the extraction of system specifications from test data that has been automatically generated from automated executions of the system. The test data in our framework consists of sequences of inputs to and the corresponding outputs from the system. From an initial collection of test data, data-mining techniques are used to infer the invariants; then the system is instrumented with the invariants and new test data is generated to try to invalidate the mined invariants.

Part 1: Upper-limb motor impairments arise from a wide range of clinical conditions including amputations, spinal cord injury, or stroke. Addressing lost hand function, therefore, is a major focus of rehabilitation interventions; and research in robotic hands and hand exoskeletons aimed at restoring fine motor control functions gained significant speed recently. Integration of these robots with neural control mechanisms is also an ongoing research direction.