Alper Bozkurt

A portable near infrared spectroscopy system for bedside monitoring of newborn brain

BackgroundNewborns with critical health conditions are monitored in neonatal intensive care units (NICU). In NICU, one of the most important problems that they face is the risk of brain injury. There is a need for continuous monitoring of newborns brain function to prevent any potential brain injury. This type of monitoring should not interfere with intensive care of the newborn. Therefore, it should be non-invasive and portable.MethodsIn this paper, a low-cost, battery operated, dual wavelength, continuous wave near infrared spectroscopy system for continuous bedside hemodynamic monitoring of neonatal brain is presented. The system has been designed to optimize SNR by optimizing the wavelength-multiplexing parameters with special emphasis on safety issues concerning burn injuries. SNR improvement by utilizing the entire dynamic range has been satisfied with modifications in analog circuitry.Results and ConclusionAs a result, a shot-limited SNR of 67 dB has been achieved for 10 Hz temporal resolution. The system can operate more than 30 hours without recharging when an off-the-shelf 1850 mAh-7.2 V battery is used. Laboratory tests with optical phantoms and preliminary data recorded in NICU demonstrate the potential of the system as a reliable clinical tool to be employed in the bedside regional monitoring of newborn brain metabolism under intensive care.

Balloon-Assisted Flight of Radio-Controlled Insect Biobots

We report on radio-controlled insect biobots by directing the flight of Manduca sexta through neuromuscular activation. Early metamorphosis insertion technology was used to implant metal wire probes into the insect brain and thorax tissue. Inserted probes were adopted by the developing tissue as a result of the metamorphic growth. A mechanically and electrically reliable interface with the insect tissue was realized with respect to the insects behavioral and anatomical adoption. Helium balloons were used to increase the payload capacity and flight duration of the insect biobots enabling a large number of applications. A super-regenerative receiver with a weight of 650 mg and 750 muW of power consumption was built to control the insect flight path through remotely transmitted electrical stimulation pulses. Initiation and cessation of flight, as well as yaw actuation, were obtained on freely flying balloon-assisted moths through joystick manipulation on a conventional model airplane remote controller.

Safety assessment of near infrared light emitting diodes for diffuse optical measurements

BackgroundNear infrared (NIR) light has been used widely to monitor important hemodynamic parameters in tissue non-invasively. Pulse oximetry, near infrared spectroscopy, and diffuse optical tomography are examples of such NIR light-based applications. These and other similar applications employ either lasers or light emitting diodes (LED) as the source of the NIR light. Although the hazards of laser sources have been addressed in regulations, the risk of LED sources in such applications is still unknown.MethodsTemperature increase of the human skin caused by near infrared LED has been measured by means of in-vivo and in-vitro experiments. Effects of the conducted and radiated heat in the temperature increase have been analyzed separately.ResultsElevations in skin temperature up to 10°C have been observed. The effect of radiated heat due to NIR absorption is low – less than 0.5°C – since emitted light power is comparable to the NIR part of sunlight. The conducted heat due to semiconductor junction of the LED can cause temperature increases up to 9°C. It has been shown that adjusting operational parameters by amplitude modulating or time multiplexing the LED decreases the temperature increase of the skin significantly.ConclusionIn this study, we demonstrate that the major risk source of the LED in direct contact with skin is the conducted heat of the LED semiconductor junction, which may cause serious skin burns. Adjusting operational parameters by amplitude modulating or time multiplexing the LED can keep the LED within safe temperature ranges.

Flexible Technologies for Self-Powered Wearable Health and Environmental Sensing

This article provides the latest advances from the NSF Advanced Self-powered Systems of Integrated sensors and Technologies (ASSIST) center. The work in the center addresses the key challenges in wearable health and environmental systems by exploring technologies that enable ultra-long battery lifetime, user comfort and wearability, robust medically validated sensor data with value added from multimodal sensing, and access to open architecture data streams. The vison of the ASSIST center is to use nanotechnology to build miniature, self-powered, wearable, and wireless sensing devices that can enable monitoring of personal health and personal environmental exposure and enable correlation of multimodal sensors. These devices can empower patients and doctors to transition from managing illness to managing wellness and create a paradigm shift in improving healthcare outcomes. This article presents the latest advances in high-efficiency nanostructured energy harvesters and storage capacitors, new sensing modalities that consume less power, low power computation, and communication strategies, and novel flexible materials that provide form, function, and comfort. These technologies span a spatial scale ranging from underlying materials at the nanoscale to body worn structures, and the challenge is to integrate them into a unified device designed to revolutionize wearable health applications.

Insect–Machine Interface Based Neurocybernetics

We present details of a novel bioelectric interface formed by placing microfabricated probes into insect during metamorphic growth cycles. The inserted microprobes emerge with the insect where the development of tissue around the electronics during the pupal development allows mechanically stable and electrically reliable structures coupled to the insect. Remarkably, the insects do not react adversely or otherwise to the inserted electronics in the pupae stage, as is true when the electrodes are inserted in adult stages. We report on the electrical and mechanical characteristics of this novel bioelectronic interface, which we believe would be adopted by many investigators trying to investigate biological behavior in insects with negligible or minimal traumatic effect encountered when probes are inserted in adult stages. This novel insect-machine interface also allows for hybrid insect-machine platforms for further studies. As an application, we demonstrate our first results toward navigation of flight in moths. When instrumented with equipment to gather information for environmental sensing, such insects potentially can assist man to monitor the ecosystems that we share with them for sustainability. The simplicity of the optimized surgical procedure we invented allows for batch insertions to the insect for automatic and mass production of such hybrid insect-machine platforms. Therefore, our bioelectronic interface and hybrid insect-machine platform enables multidisciplinary scientific and engineering studies not only to investigate the details of insect behavioral physiology but also to control it.

MEMS based bioelectronic neuromuscular interfaces for insect cyborg flight control

This paper reports the first direct control of insect flight by manipulating the wing motion via microprobes and electronics introduced through the Early Metamorphosis Insertion Technology (EMIT). EMIT is a novel hybrid biology pathway for autonomous centimeter-scale robots that forms intimate electronic-tissue interfaces by placing electronics in the pupal stage of insect metamorphosis. Our new technology may enable insect cyborgs by realizing a reliable control interface between inserted microsystems and insect physiology. The design rules on the flexibility of the inserted microsystem and the investigation towards tissue- microprobe biological and electrical compatibility are also presented.

Line following terrestrial insect biobots

The present day technology falls short in offering centimeter scale mobile robots that can function effectively under unknown and dynamic environmental conditions. Insects, on the other hand, exhibit an unmatched ability to navigate through a wide variety of environments and overcome perturbations by successfully maintaining control and stability. In this study, we use neural stimulation systems to wirelessly navigate cockroaches to follow lines to enable terrestrial insect biobots. We also propose a system-on-chip based ZigBee enabled wireless neurostimulation backpack system with on-board tissue-electrode bioelectrical coupling verification. Such a capability ensures an electrochemically safe stimulation and avoids irreversible damage to the interface which is often misinterpreted as habituation of the insect to the applied stimulation.

Low-Power Wearable Systems for Continuous Monitoring of Environment and Health for Chronic Respiratory Disease.

We present our efforts toward enabling a wearable sensor system that allows for the correlation of individual environmental exposures with physiologic and subsequent adverse health responses. This system will permit a better understanding of the impact of increased ozone levels and other pollutants on chronic asthma conditions. We discuss the inefficiency of existing commercial off-the-shelf components to achieve continuous monitoring and our system-level and nano-enabled efforts toward improving the wearability and power consumption. Our system consists of a wristband, a chest patch, and a handheld spirometer. We describe our preliminary efforts to achieve a submilliwatt system ultimately powered by the energy harvested from thermal radiation and motion of the body with the primary contributions being an ultralow-power ozone sensor, an volatile organic compounds sensor, spirometer, and the integration of these and other sensors in a multimodal sensing platform. The measured environmental parameters include ambient ozone concentration, temperature, and relative humidity. Our array of sensors also assesses heart rate via photoplethysmography and electrocardiography, respiratory rate via photoplethysmography, skin impedance, three-axis acceleration, wheezing via a microphone, and expiratory airflow. The sensors on the wristband, chest patch, and spirometer consume 0.83, 0.96, and 0.01 mW, respectively. The data from each sensor are continually streamed to a peripheral data aggregation device and are subsequently transferred to a dedicated server for cloud storage. Future work includes reducing the power consumption of the system-on-chip including radio to reduce the entirety of each described system in the submilliwatt range.

Sound Localization Sensors for Search and Rescue Biobots

Recent advances in neural engineering have enabled direct control of insect locomotion through neural and muscular stimulation. The resulting insect biobots, with a natural ability to crawl through small spaces, offer unique advantages over traditional synthetic robots. A cyberphysical network of such biobots could prove useful for search and rescue applications in uncertain disaster environments. We present a vision-based automated system for an objective assessment of biobotic navigation capability on Madagascar hissing cockroaches. We report the most precise control results obtained with insect biobots so far both manually and autonomously. We also demonstrate autonomous control capability where a low-power insect-mounted array of microphones was used to localize a sound source and guide the biobot toward it. Forming a wireless mobile sensor network with directional and omnidirectional microphones distributed within the structure of a rubble pile could be useful for both environmental mapping and localization of trapped survivors under the rubble.

Behavior recognition based on machine learning algorithms for a wireless canine machine interface

Training and handling working dogs is a costly process and requires specialized skills and techniques. Less subjective and lower-cost training techniques would not only improve our partnership with these dogs but also enable us to benefit from their skills more efficiently. To facilitate this, we are developing a canine body-area-network (cBAN) to combine sensing technologies and computational modeling to provide handlers with a more accurate interpretation for dog training. As the first step of this, we used inertial measurement units (IMU) to remotely detect the behavioral activity of canines. Decision tree classifiers and Hidden Markov Models were used to detect static postures (sitting, standing, lying down, standing on two legs and eating off the ground) and dynamic activities (walking, climbing stairs and walking down a ramp) based on the heuristic features of the accelerometer and gyroscope data provided by the wireless sensing system deployed on a canine vest. Data was collected from 6 Labrador Retrievers and a Kai Ken. The analysis of IMU location and orientation helped to achieve high classification accuracies for static and dynamic activity recognition.