Alper Bozkurt

The ultimate vision of our research is to establish a new architecture and design toolbox for Reconfigurable Metal-Free Microsystems with Alternative Power Sources (RMF-MAPS), amenable to modular assembly, green material technologies, hybrid production processes, and next-generation energy technologies. The outcomes will inform the engineering community of new research directions and technologies to disrupt conventional microelectronic technology into the next century. Specifically, we propose to demonstrate a 100% metal-free sensing-communications node, which operates from a renewable energy source and is completely degradable or recyclable after a designed operational lifetime.

In this proposal, we aim to study and develop a transformative plant wearable sensor that can be deployed on-plant for continuous monitoring of biotic and abiotic stresses of plants and their microenvironment to inform plant health status and early detection of plant diseases. This multifunctional plant wearable sensor will include an array of ligand-functionalzied chemiresistive sensors to profile plant leaf VOCs and nanowire-based flexible sensors to monitor microclimate in parallel. The sensors will be prepared on a light-transparent, gas-permeable, and stretach substrate for long-term wearibility on live plants. In addition, a signal transmitter will be developed for wireless data acquistion and transmission. The system will be thourughly tested on tomato plants in the greenhouse for stress monitoring and disease detection.

We propose a novel sensor system with accompanying data analytics to explore the capability of wearable multimodal sensors to address the short-comings of the traditional polysomnography systems. If successful, this project will lead to improved capacity to carry out sleep research and to detect and treat sleep disorders. The miniaturization and low power consumption will pave the way for rapid adoption and deployment of these systems for home-use in real-world settings.

Stroke is a leading cause of motor disability. A majority of stroke survivors exhibit upper and lower limb motor impairments, ranging from incapability of reaching and grasping objects to limited ambulation. The objective of this project is to develop a personalized, community-based rehabilitation system to improve daily functions of stroke survivors. The system will include three essential components ������������������ a nanomaterial-enabled multifunctional wearable sensor network to monitor arm and leg functional activities; a low-power data acquisition, processing, and transmission protocol; and a user interface (i.e., smart phone APP) to communicate training outcomes to the users and clinicians and receive feedback from the users and clinicians. The proposed community-based rehabilitation system will enable personalized, continuous rehabilitation during daily activities.

Accurate monitoring for changes in pest susceptibility to insecticidal toxins expressed in genetically engineered agronomic crops is currently an ineffective process limited by both scale and scope of deployment. Although long-term scientific and social change will be necessary to minimize pest resistance evolution, understanding near-term shifts in susceptibility through novel monitoring will also be essential to enable more effective resistance management strategies. To address this limitation on resistance monitoring, we propose to develop and deploy real-time pheromone-based sensor platforms to indicate patterns of lepidopteran pest activity in landscapes. We will use cotton bollworm (Helicoverpa zea Boddie) as a case study to develop and refine automated monitoring tools designed to detect shifts in pest susceptibility.

Monitoring of animal health is crucial for various applications from agriculture to working animal applications, from pharmaceutical industries to sports. In this project, our major aim is the development of ultra-miniature physiological sensors systems for measuring heart rate, respiratory rate, and core body temperature in small and caged experimental animals.

Our main goals are to: (1) develop a statistically-sound data-driven framework for signal quality characterization of wearable devices in the real-world; and (2) use this framework for enhancing algorithmic developments and hardware design. Current approaches depend on rules or indicators derived from expert knowledge in controlled environments, so they do not generalize well to the use at-home. Our main application will be the early asthma exacerbation detection. We aim to employ the prototypes designed by the NSF-ERC ASSIST center, which aims to develop nano-enabled energy harvesting, energy storage, nanodevices and sensors to create innovative battery-free, body-powered, and wearable health monitoring systems.

The focus of this project is to facilitate the means to lead the Health and Environmental Tracker (HET) Testbed. This particular project focuses on the ����������������making��������������� of the HET where we develop prototypes to be used in clinical experiments and provide technical support to Thrust 3 researches with sensor interfacing. This year������������������s efforts will include the integration of biochemical sensors into the HET testbed as well as populating enough number of devices/prototypes for data collection to establish the ASSIST HET database.

Advanced Self-powered Systems of Integrated Sensor Technologies (ASSIST) vision is to be a dynamic leader in development of wearable, self-powered integrated sensor technologies for continuous health and environmental monitoring. These technologies will directly respond to NAE?s Grand Challenge to advance health informatics to improve acquisition, management and use of health information to enhance medical care, correlate disease and environment and revolutionize response to public health emergencies, disasters, pandemics and/or chem-bio attacks. ASSIST?s mission is to transform US and global health informatics, electronics and biomedical engineering industries through development and demonstration of fundamental and enabling nanotechnologies for energy harvesting, battery-free energy storage and ultra-low power computation and communication, integrated with physiological and environmental nanosensors and biocompatible materials, to empower personal environmental health monitoring and emergency response. Goals: 1. Advance discovery in energy harvesting and storage, multifunctional sensors and materials, and low-power systems design; 2. Develop enabling technologies for energy conversion, device reliability and ultra-low power computation and communications, with integration to achieve two 1st-generation test-beds: self-sustaining wireless nodes and conformal multifunctional applications; 3. Develop systems integration requirements and demonstrate ?Exposure Track? and ?Emergency Track? testbeds; 4. Develop efficient and secure methods to handle large quantities of data and retrieve patterns of environmental and health correlations; 5. Create a culture of team-based research, education and innovation, cultivating a diverse group of talented, well prepared graduates excited about research, design and production of health informatics and biomedical engineering solutions to improve global health and safety; 6. Form partnerships with precollege institutions to strengthen the STEM pipeline by helping middle and high school students and teachers develop technical literacy and motivation to contribute to solving NAE Grand Challenges; 7. Stimulate entrepreneurship and form sustainable partnerships with small and large firms, health practitioners and emergency responders to link ASSIST discoveries to innovation, accelerated commercialization and job creation. ASSIST integrated sensor technologies will result in a wearable health patch that incorporates energy harvesting and storage, computation and communication, along with low-power integrated sensors for health and environmental exposures. This will be the platform technology that will drive two systems applications related to global health. The first, the Exposure Track, will enable longitudinal, simultaneous monitoring of environmental factors and human health parameters to create an unprecedented set of data to lead to direct understanding of how environment impacts health. This information, of great interest to EPA and CDC, will revolutionize our understanding of environmental health and may impact future regulatory policies. The patch?s self-powered nature will enable critical longitudinal monitoring. This system will involve epidemiologists, social scientists, data mining, pattern recognition professionals and EPA scientists to further understanding of environmental health. The patch will also drive a second system, the Wellness Track, which will aim to empower patients to take charge of their own health by having readily accessible information about their health status. According to the Milken Inst., lifestyle diseases consume 70% of the US?s health care resources and face an unsustainable future in light of rising health care costs. It has been shown that humans are more likely to change lifestyle habits if they witness real-time, positive changes in their health as a result of those changes. The Wellness Track will provide an unobtrusive, battery-free interface for sensing of multiple vital signs, along with advanced and secure communication strateg

This research project aims to test a class of minimally invasive biosensing microsystems that extract, process, and analyze sweat and interstitial fluid (ISF) monitor metabolic profiles in a more continuous and longitudinal method.