This work used a low-cost wireless electroencephalography (EEG) headset to quantify the human response to different cognitive stress states on a single-trial basis. We used a Stroop-type color–word interference test to elicit mild stress responses in 18 subjects while recording scalp EEG. Signals recorded from thirteen scalp locations were analyzed using an algorithm that computes the root mean square voltages in the theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands immediately following the initiation of Stroop stimuli; the mean of the Teager energy in each of these three bands; and the wideband EEG signal line-length and number of peaks. These computational features were extracted from the EEG signals on thirteen electrodes during each stimulus presentation and used as inputs to logistic regression, quadratic discriminant analysis, and k-nearest neighbor classifiers. Two complementary analysis methodologies indicated classification accuracies over subjects of around 80% on a balanced dataset for the logistic regression classifier when information from all electrodes was taken into account simultaneously. Additionally, we found evidence that stress responses were preferentially time-locked to stimulus presentation, and that certain electrode–feature combinations worked broadly well across subjects to distinguish stress states.

Microrobots have a number of potential applications for micromanipulation and assembly, but also offer challenges in power and control. This paper describes an uncalibrated vision-based control system for magnetically actuated microrobots operating untethered at the interface between two immiscible fluids. The microrobots are 20 μm thick and approximately 100–200 μm in lateral dimension. Several different robot shapes are investigated. The robots and fluid are in a 20 × 20 × 15 mm vial placed at the center of four electromagnets. Pulse width modulation of the electromagnet currents is used to control robot speed and direction. Given a desired position, a controller based on recursive least square estimation drives the microrobot to the goal without a priori knowledge of system parameters such as drag coefficients or intrinsic and extrinsic camera parameters. Results are verified experimentally using a variety of microrobot shapes and system configurations.

This describes the application of a visual servo control method to the microrobotic manipulation of polymer beads on a two-dimensional fluid interface. A microrobot, actuated through magnetic fields, is utilized to manipulate a non-magnetic polymer bead into a desired position. The controller utilizes multiple modes of robot actuation to address the different stages of the task. A filtering strategy employed in separation mode allows the robot to spiral from the manipuland in a fashion that promotes the manipulation positioning objective. Experiments demonstrate that our multiphase controller can be used to direct a microrobot to position a manipuland to within an average positional error of approximately 8 pixels (64 µm) over numerous trials.

Microrobotics is a rapidly growing field with promising applications in microsurgery and microassembly. A challenge in these systems is providing power and control signals to the robot. This project explores crawling robots that are powered and controlled through a global mechanical vibration field. Structures within the robot will cause it to respond to particular frequencies with different motion modalities. A prototype, dubbed the “jitterbot”, was cut out of a 0.75 mm sheet of steel using electric discharge machining (EDM), and has a total footprint of approximately 30 mm × 20 mm in the xy-plane. The “robot” has a tripod body (8 mm × 16 mm) with three small legs, and two suspended masses that are designed for specific resonance frequencies. The robot was tested on a plate that was vibrated vertically at frequencies ranging from 20 to 2,000 Hz. For particular resonant frequencies, the robot moves forward and turns in either a clockwise or counterclockwise direction. Finite element modeling confirms that the mechanism for motion is a rocking mode that is influenced by two arms that are suspended mass springs tuned to different frequencies. This lays the groundwork for further miniaturization.

(1) The advent of micro/nanorobotics promises to transform the physical, chemical, and biological domains by harnessing opportunities otherwise limited by size. Most notable is the biomedical field, in which the ability to manipulate micro/nanoparticles has numerous applications in biophysics, drug delivery, tissue engineering, and microsurgery. (2) Acoustics, the physics of vibrational waves through matter, offers a precise, accurate, and minimally invasive technique to manipulate microrobots or microparticles (stand-ins for microrobots). One example is through the use of flexural vibrations induced in resonant structures such as Chladni plates. (3) In this research, we developed a platform for precise two-dimensional microparticle manipulation via acoustic forces arising from Chladni figures and resonating microscale membranes. The project included two distinct phases: (i) macroscale manipulation with a Chladni plate in air; and (ii) microscale manipulation using microscale membranes in liquid. In the first phase (macroscale in air), we reproduced previous studies in order to gain a better understanding of the underlying physics and to develop control algorithms based on statistical modeling techniques. In the second phase (microscale in liquid), we developed and tested a new setup using custom microfabricated structures. The macroscale statistical modeling techniques were integrated with microscale autonomous control systems. It is shown that control methods developed on the macroscale can be implemented and used on the microscale with good precision and accuracy.

Pulse power systems generate heat in the presence of a large time varying magnetic field. In order to quantify the local heat generation, these systems need temperature sensing equipment. The magnetic field can induce signals in temperature sensors with electrical connections such as thermocouples and thermistors. Also, the power systems are often at a high electric potential when energized requiring robust electrical isolation schemes to prevent the system from discharging through the sensing equipment. As such, a sensing system has been developed that can remotely capture information to determine the temperature of a surface. This sensor is based on an interferometer using a thin sapphire die coated with nickel oxide as the sensing element. A model was developed to predict the behavior of the sensor in order to determine the ideal layer thickness. With this system temperature measurement has been demonstrated at a sampling rate of 30 Hz over a range of 20degC to 300degC with 20% precision. Because the technique explored in this research does not require physical connections to the sensor, the dilemma of the magnetic field and electrical isolation are bypassed.