Vibrotactile actuators in prototype smart glasses (credit: Joseph Szczerba et al./Proceedings of the Human Factors and Ergonomics Society)

Human factors/ergonomics researchers at General Motors and an affiliate have performed a study using a new turn-by-turn automotive navigation system that uses haptic cues (vibrations) to the temples to communicate information to drivers on coming turns (which direction and when to turn), instead of distracting voice prompts or video displays.

They modified a prototype smart-glasses device with motors in two actuators (on the right and left side of the head) that buzz to indicate a right or left turn and how far it is, indicated by the number of buzzes (1 at 800 feet away, 2 at 400 feet, and 3 at 100 feet).

National Advanced Driving Simulator (NADS) MiniSim software (credit: NADS)

Using a driving simulator, each participant drove three city routes using a visual-only, visual-plus-voice, and visual-plus-haptic navigation system. For all three system modalities, the participants were also presented with graphical icons for turn-by-turn directions and distance.

Sample turn-by-turn direction icon (credit: Joseph Szczerba et al./Proceedings of the Human Factors and Ergonomics Society)

The researchers found that effort, mental workload, and overall workload were lowest with the prototype haptic system. Drivers didn’t have to listen for voice instructions or take their eyes off the road to look at a visual display. Drivers also preferred the haptic system because it didn’t distract from conversation or audio entertainment.

The results indicate that haptic smart-glasses paired with a simplified icon-based visual display may give drivers accurate directional assistance with less effort.

Mazda 2015 with GPS audio and video display (credit: Landmark MAZDA)

As noted in “Up to 27 seconds of inattention after talking to your car or smartphone,” two studies by University of Utah researchers for the AAA Foundation for Traffic Safety found that a driver traveling only 25 mph continues to be distracted for up to 27 seconds after disconnecting from highly distracting phone and car voice-command systems. The 27 seconds means a driver traveling 25 mph would cover the length of three football fields before regaining full attention.

According to the Multiple Resource Theory developed by Christopher D. Wickens in Theoretical Issues in Ergonomics Science (open access), multiple tasks (such as use of navigation systems while driving) performed via the same channel can result in excessive demand that may increase cognitive workload (and risks of an accident).

The new human factors/ergonomics haptics research was conducted by Joseph Szczerba and Roy Mathieu from General Motors Global R&D and Roger Hersberger from RLH Systems LLC. It was described in a paper in Proceedings of the Human Factors and Ergonomics Society September 2015.

Abstract of A Wearable Vibrotactile Display for Automotive Route Guidance: Evaluating Usability, Workload, Performance and Preference

Automotive navigation systems typically provide distance and directional information of an ensuing maneuver by means of visual indicators and audible instructions. These systems, however, use the same human perception channels that are required to perform the primary task of driving, and may consequently increase cognitive workload. A vibrotactile display was designed as an alternative to voice instruction and implemented in a consumer wearable device (smart-glasses). Using a driving simulator, the prototype system was compared to conventional navigation systems by assessing usability, workload, performance and preference. Results indicated that the use of haptic feedback in smart-glasses can improve secondary task performance over the conventional visual/auditory navigation system. Additionally, users preferred the haptic system over the other conventional systems. This study indicates that existing technologies found in consumer wearable devices may be leveraged to enhance the user-interface of vehicle navigation systems.

Elite X-Plane General Aviation Dream Package flight simulator system (credit: Xforce PC)

You can learn how to improve your novice pilot skills by having your brain zapped with recorded brain patterns of experienced pilots via transcranial direct current stimulation (tDCS), according to researchers at HRL Laboratories.

“We measured the brain activity patterns of six commercial and military pilots, and then transmitted these patterns into novice subjects as they learned to pilot an airplane in a realistic flight simulator,” says Matthew Phillips, PhD.

The study, published in an open-access paper in the February 2016 issue of the journal Frontiers in Human Neuroscience, found that novice pilots who received brain stimulation via electrode-embedded head caps improved their piloting abilities, with a 33 percent increase in skill consistency, compared to those who received sham stimulation. “We measured the average g-force of the plane during the simulated landing and compared it to control subjects who received a mock brain stimulation,” says Phillips.

“Pilot skill development requires a synthesis of multiple cognitive faculties, many of which are enhanced by tDCS and include dexterity, mental arithmetic, cognitive flexibility, visuo-spatial reasoning, and working memory,” the authors note.

Measuring brain activity to infer learning

Neuroimaging and tDCS experimental setup for stimulation. EEG locations are denoted in blue, fNIRS sources (red), and detectors (green). tDCS electrodes are denoted in purple (cathodes) and yellow (anodes). C and D: Predicted electric field intensities. (credit: Jaehoon Choe et al./Front. Hum. Neurosci.)

The study focused on a working-memory area — the right dorsolateral prefrontal cortex (DLPFC) — and the left motor cortex (M1), using continuous electroencephalography (EEG) to monitor midline frontal theta-band oscillatory brain activity and functional near infrared spectroscopy (fNIRS) to monitor blood oxygenation to infer neuronal activity.

The researchers used the XForce Dream Simulator package from X-Force PC and the X-plane 10 flight simulator software from Laminar Research for flight simulation training.

Previous research has demonstrated that tDCS can both help patients more quickly recover from a stroke and boost a healthy person’s creativity; HRL’s new study is one of the first to show that tDCS is effective in accelerating practical learning.

Phillips speculates that the potential to increase learning with brain stimulation may make this form of accelerated learning commonplace. “As we discover more about optimizing, personalizing, and adapting brain stimulation protocols, we’ll likely see these technologies become routine in training and classroom environments,” he says. “It’s possible that brain stimulation could be implemented for classes like drivers’ training, SAT prep, and language learning.”

Abstract of Transcranial Direct Current Stimulation Modulates Neuronal Activity and Learning in Pilot Training

Skill acquisition requires distributed learning both within (online) and across (offline) days to consolidate experiences into newly learned abilities. In particular, piloting an aircraft requires skills developed from extensive training and practice. Here, we tested the hypothesis that transcranial direct current stimulation (tDCS) can modulate neuronal function to improve skill learning and performance during flight simulator training of aircraft landing procedures. Thirty-two right-handed participants consented to participate in four consecutive daily sessions of flight simulation training and received sham or anodal high-definition-tDCS to the right dorsolateral prefrontal cortex (DLPFC) or left motor cortex (M1) in a randomized, double-blind experiment. Continuous electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) were collected during flight simulation, n-back working memory, and resting-state assessments. tDCS of the right DLPFC increased midline-frontal theta-band activity in flight and n-back working memory training, confirming tDCS-related modulation of brain processes involved in executive function. This modulation corresponded to a significantly different online and offline learning rates for working memory accuracy and decreased inter-subject behavioral variability in flight and n-back tasks in the DLPFC stimulation group. Additionally, tDCS of left M1 increased parietal alpha power during flight tasks and tDCS to the right DLPFC increased midline frontal theta-band power during n-back and flight tasks. These results demonstrate a modulation of group variance in skill acquisition through an increasing in learned skill consistency in cognitive and real-world tasks with tDCS. Further, tDCS performance improvements corresponded to changes in electrophysiological and blood-oxygenation activity of the DLPFC and motor cortices, providing a stronger link between modulated neuronal function and behavior.

In a new paper published in Science, researchers at the Harvard and Raytheon BBN Technology have observed, for the first time, electrons in a metal behaving like a fluid (credit: Peter Allen/Harvard SEAS)

A radical discovery by researchers at Harvard and Raytheon BBN Technology about graphene’s hidden properties could lead to a model system to explore exotic phenomena like black holes and high-energy plasmas, as well as novel thermoelectric devices.

In a paper published Feb. 11 in Science, the researchers document their discovery of electrons in graphene behaving like a fluid. To make this observation, the team improved methods to create ultra-clean graphene* and developed a new way to measure its thermal conductivity.

A black hole on a chip

In ordinary 3D metals, electrons hardly interact with each other. But graphene’s two-dimensional, honeycomb structure acts like an electron superhighway in which all the particles have to travel in the same lane. The electrons in this ultra-clean graphene act like massless relativistic objects, some with positive charge and some with negative charge.

They move at incredible speed — 1/300 of the speed of light — and have been predicted to collide with each other ten trillion times a second at room temperature.  These intense interactions between charge particles have never been observed in an ordinary metal before.

Most of our world is described by classical physics. But very small things, like electrons, are described by quantum mechanics while very large and very fast things, like galaxies, are described by relativistic physics, pioneered by Albert Einstein.

Combining these different sets of laws of physics is notoriously difficult, but there are extreme examples where they overlap. High-energy systems like supernovas and black holes can be described by linking classical theories of hydrodynamics with Einstein’s theories of relativity.

A quantum ‘Dirac’ fluid metal

But since we can’t run an experiment on a black hole (yet), enter graphene.

When the strongly interacting particles in graphene were driven by an electric field, they behaved not like individual particles but like a fluid that could be described by hydrodynamics.

“Physics we discovered by studying black holes and string theory, we’re seeing in graphene,” said Andrew Lucas, co-author and graduate student with Subir Sachdev, the Herchel Smith Professor of Physics at Harvard. “This is the first model system of relativistic hydrodynamics in a metal.”

Industrial implications

A small chip of graphene could also be used to model the fluid-like behavior of other high-energy systems.

To observe the hydrodynamic system, the team turned to noise. At finite temperature, the electrons move about randomly:  the higher the temperature, the noisier the electrons. By measuring the temperature of the electrons to three decimal points, the team was able to precisely measure the thermal conductivity of the electrons.

“This work provides a new way to control the rate of heat transduction in graphene’s electron system, and as such will be key for energy and sensing-related applications,” said Leonid Levitov, professor of physics at MIT.

“Converting thermal energy into electric currents and vice versa is notoriously hard with ordinary materials,” said Lucas. “But in principle, with a clean sample of graphene there may be no limit to how good a device you could make.”

The research was led by Philip Kim, professor of physics and applied physics at The Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS).

* The team created an ultra-clean sample by sandwiching the one-atom thick graphene sheet between tens of layers of an electrically insulating perfect transparent crystal with a similar atomic structure of graphene.

“If you have a material that’s one atom thick, it’s going to be really affected by its environment,” said Jesse Crossno, a graduate student in the Kim Lab and first author of the paper. “If the graphene is on top of something that’s rough and disordered, it’s going to interfere with how the electrons move. It’s really important to create graphene with no interference from its environment.”

Next, the team set up a kind of thermal soup of positively charged and negatively charged particles on the surface of the graphene, and observed how those particles flowed as thermal and electric currents.

Abstract of Observation of the Dirac fluid and the breakdown of the Wiedemann-Franz law in graphene

Interactions between particles in quantum many-body systems can lead to collective behavior described by hydrodynamics. One such system is the electron-hole plasma in graphene near the charge neutrality point, which can form a strongly coupled Dirac fluid. This charge neutral plasma of quasi-relativistic fermions is expected to exhibit a substantial enhancement of the thermal conductivity, thanks to decoupling of charge and heat currents within hydrodynamics. Employing high sensitivity Johnson noise thermometry, we report an order of magnitude increase in the thermal conductivity and the breakdown of the Wiedemann-Franz law in the thermally populated charge neutral plasma in graphene. This result is a signature of the Dirac fluid, and constitutes direct evidence of collective motion in a quantum electronic fluid.