Dr. Alper Bozkurt performs research on how microsystems based tissue interfaces and physiological monitoring systems can be used to wirelessly interact with animals and crops that is raised in agricultural fields to enable new phenotypical data for smarter farming. This is one of the on-going efforts under Integrated Bionic MicroSystems Laboratory (iBionicS Lab) which has a vision to introduce conceptually novel animal-plant-machine interfaces to bridge artificial systems with biological organisms towards the next generation bionic cyber-physical systems. Such cyber-physical systems would be the building blocks of a new era where everything is connected to each other through the Internet of Things.
Biography: Alper Bozkurt is a professor of Electrical and Computer Engineering and University Faculty Scholar at NC State University. He received a Ph.D. degree from Cornell University in 2010 working with Prof. Amit Lal on DARPA’s Hybrid Insect Micro-Electro-Mechanical-Systems program. His research team at NC State performs research on connecting biological organisms to the cloud to solve real life engineering problems in innovative ways. The ongoing funded projects include “insect-machine-interfaces” with remotely controlled biobotic insects for exploration and mapping after natural disasters, “canine-machine interfaces” to enable a computer assisted canine training system and remotely interact with canines and “plant-machine interfaces” to record biopotentials and impedances on crops and trees to monitor their stress response. His recent achievements were covered by media including BBC, CNN, National Geographic, Discovery Channel and Reuters. Bozkurt is a recipient of Calhoun Fellowship from Drexel University, Donald Kerr Award from Cornell University, Chancellor’s Innovation Award and William F. Lane Outstanding Teacher Award at NC State, the CAREER Award from National Science Foundation, IBM Faculty Award, IEEE Sensors Council Young Professional Award and was included in Popular Science Magazine’s Brilliant 10 list. His research team received best paper awards from The US Government Microcircuit Applications & Critical Technology Conference, IEEE Body Sensor Network Conference and IEEE Sensors Conference.
SHORT DESCRIPTION OF INTERESTS:
Dr. Bozkurt joined NCSU in August 2010. His research interests include development of microscale sensors, actuators and methodologies to unlock the mysteries of biological systems with an aim of engineering these systems directly or developing new engineering approaches by learning from these systems. His work related to Coastal Resilience Initiative includes behavioral monitors for mussels, physiological sensors for fishes, stress detection in plants and smart trapping of insects. His team develops novel sensors and provides wireless electronics prototyping support.
- A Wearable Patch for Prolonged Sweat Lactate Harvesting and Sensing , 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC) (2021)
- Evaluation of Environmental Enclosures for Effective Ambient Ozone Sensing in Wrist-worn Health and Exposure Trackers , 2021 IEEE SENSORS (2021)
- Investigating the Relationship between Cough Detection and Sampling Frequency for Wearable Devices , 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC) (2021)
- Melt-Extruded Sensory Fibers for Electronic Textiles , MACROMOLECULAR MATERIALS AND ENGINEERING (2021)
- Noncontact Electrophysiology Monitoring Systems for Assessment of Canine-Human Interactions , 2021 IEEE SENSORS (2021)
- Novel 3D-printed Electrodes for Implantable Biopotential Monitoring , 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC) (2021)
- Preliminary Evaluation of a Solar-Powered Wristband for Continuous Multi-Modal Electrochemical Monitoring , 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC) (2021)
- Simultaneous Localization of Biobotic Insects using Inertial Data and Encounter Information , 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC) (2021)
- Textile-Based Pressure Sensors for Monitoring Prosthetic-Socket Interfaces , IEEE SENSORS JOURNAL (2021)
- Towards Continuous Plant Bioimpedance Fitting and Parameter Estimation , 2021 IEEE SENSORS (2021)
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.
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.
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.
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.
Corn earworm (Helicoverpa zea Boddie) has been the target of black light and pheromone trapping networks across North Carolina for decades. Analysis of this historical data has shown that high numbers of corn earworm are positively related to the abundance of soybean in the surrounding landscape (Dorman and Huseth in prep). However, we do not know how to leverage this new knowledge into accurate risk predictions for soybean growers. In 2019, the NCSPA funded the development of a real-time pheromone trap targeting corn earworm. Following a period of development and small scale testing, we deployed 20 traps in soybean fields across 5 NC counties. First, we tested the trap durability and identified several improvements that will be needed to move this trap toward commercialization (power usage, weatherizing). Second, we documented a remarkable amount of corn earworm abundance variation in space and time. Here, we propose to refine our trap design and develop predictive data analytics using the near real-time data. Results of this work will provide the foundation for grower accessible corn earworm risk prediction tools.
The major aim of this project is to investigate the technology challenges, business case, and market & regulatory environment related to the deployment of new Murata technologies, new Murata products, and Murata-based engineering techniques for the development of ultra-miniature, injectable and subcutaneous physiology capsules. These capsule devices are for physiological measurements from animals.
This proposal targets a somatic and cerebral oximetry devices using functional near-infrared spectroscopy. The proposed project directly supports research on this platform to ideate on a deployable prototype for use toward injury monitoring of traumatic brain injury (TBI) patients, both from primary injury and secondary injury.
This proposal aims at solving a long-standing problem in the field of prosthetics ÃƒÂ¢Ã¢â€šÂ¬Ã¢â‚¬Å“lack of inner-socket sensor technology. Due to this limitation, monitoring the inner socket environment (such as socket pressure, moisture, and temperature) is impossible. The proposed textile based multimodal sensor interface will be evaluated in real-time inner socket environment monitoring to enable self-management.
Recent developments in miniature, low-power wireless sensors has provided systems capable of long-term deployment and continuous operation. Plant sciences will be benefited by the application of such a tailored suite of sensors, in which the output data will inform real-time changes to growth conditions in order to minimize cost and maximize yield. This proposal develops a physical and computational framework that will determine the necessary suite of plant physiology sensors and uses the collected data to model the complex interactions between phenotypical response and growth conditions. The contributions of this award will facilitate the broad adoption of new plant physiology sensors and analytic platforms for plant/crop management.
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 ÃƒÂ¢Ã¢â€šÂ¬Ã…â€œmakingÃƒÂ¢Ã¢â€šÂ¬Ã‚Â 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 yearÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢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.