One noteworthy observation made on this expedition is that some climbers do not adopt ‘good altitude behaviors’ at altitude and that the reasons for this vary. Some of these reasons, I believe, are rooted in education (or lack thereof) and the availability of consistent information. Inconsistencies arise from what one’s own body seems to demand (or fail to demand) at altitude, what stepping and breathing behaviors are appropriate, what pharmaceutical aids do to help one at altitude, and how to properly train for altitude. In addition, there are inconsistencies in altitude research itself which typically name the altitude itself as the primary independent variable (cause of illness and psychological changes), not the actual blood oxygen levels, and fail to take into account a climber’s individual behavior at altitude.

One of the big messages out there is that “some people get altitude mountain sickness (AMS) and some people don’t and it isn’t clear why”.  I interpret this as “some people get sick when oxygen levels are low (per unit volume) and some people don’t”.  I think we can turn this issue on it’s head and approach the problem in a different way. My own deduction from my experience watching others at altitude and collecting data is that if people keep their oxygen levels high (for example, by using correct pressure breathing and rest stepping procedures), they will most likely avoid AMS, and by doing so, we are no longer playing the lottery of who gets sick when oxygen levels are low and who does not.  This is actually not an original deduction and in fact in 2004 Virues-Ortega et al., published a study with recommendations for biofeedback procedures to help climbers learn protective styles of breathing.  As of the current date, I have not found a statistically derived set of recommendations for what peripherally measured haemoglobin blood oxygen levels (SPO2) (that are attainable via pressure breathing and rest stepping) minimize the risk of AMS and long-lasting neurophysiological impact. (If you know of one, send it to me.)   I would like to work with the public and other investigators to generate some solid statistics for what SPO2 levels and exhaled CO2 levels (if any) can effectively “ward off AMS” and hence increase the number of successful summits while maintaining good health.

When I was preparing for this trip and essentially doing a literature review, I largely found that the scientific literature available refers to high altitude breathing as “hyperventilation”. It is not this exactly– more of a very good use of our breathing apparatus– using our lungs completely and it is difficult to adopt a breathing style that promotes the best possible CO2-O2 exchange in our bodies while maximizing the available oxygen in the atmosphere. We will be posting some video and clear description of this shortly.  While on Kilimanjaro, using an SPO2 meter in hand, (on one’s finger) we found that it is possible to improve and refine one’s breathing and stepping technique however it did require practice and it did require a good set of muscles to continuously move large volumes of air.

Hyperventilation is most commonly known as quick, uncontrolled breathing that results in a net decrease of CO2 in the body leading to constriction of the blood vessels that supply the brain and hence reduced blood flow to the brain. Typically one feels dizzy and out of sorts when this happens.  When we do not have proper levels of CO2 in our bodies, exchange of oxygen molecules from our hemoglobin to our tissues for carbon dioxide from our tissues to our hemoglobin is non-ideal. Pressure breathing on the other hand, when done correctly, seems to increase blood oxygen levels; the rate of pressure breathing (for example, once every step or once every 3 steps), based on my own experience and body awareness, seems to help manage appropriate CO2 levels.  The relationship between the style and rate of pressure breathing with blood O2 and CO2 levels and constriction of the blood vessels need to be investigated further.

We are currently looking for collaborators who are interested in working with us to collect and publish more data in the context of keeping blood oxygen levels high and CO2 at appropriate levels at altitude either purely by behavior (pressure breathing and rest stepping) or by combined behavioural and pharmacological means.  If you would like to hear more about our expedition and see some of the data we collected, we will be posting video, pictures, and plots on my personal blog  (http://philipmichaelzeman.blogspot.com).

According to a description on the YouTube site, the plots given in the figures below show “the ups-and-downs of viewership at each moment in your video, compared to videos of similar length. The higher the graph, the hotter your video: fewer viewers are leaving your video and they may also be rewinding to watch that point in the video again. Audience attention is an overall measure of your video’s ability to retain its audience”.

The data in the first figure corresponds to a “feel good” video created to promote a research project that involves collecting data at high altitude. The data show that we are largely able to retain our audience until we reveal, just before the end of the video, what happens when we open a can of Coke at 14,000 feet. Click on the video below to check it out for yourself.

Comparing a few videos:

(1) A very simple video illustrating a rotating model of brain function related to some spatial navigation research

(2) A television interview video where we are explaining some of our past spatial navigation research

If you have any questions or comments about what we did here or if you have remarks about our high altitude research, feel free to drop me a note or give me a call. My contact information is on our “CONTACT” web page.

Regards,
Philip Michael Zeman

It is possible to design a video game with particular cognitive strategies in mind.  Equipment such as eye-trackers or even EEG machines can help a game designer and behavioural scientist with a design methodology to optimize games for specific cognitive strategies.  At Dr. Ron Skelton’s lab at the University of Victoria, just such activities are taking place.  However, rather than having video game sales on his mind, his team has been investigating different ways to design game-based tasks to elicit function of particular systems of the brain important in navigating 1st-person perspective video game environments.  This is actually the context from which Applied Brain and Vision Sciences’ game design consulting practice originated.  Under Skelton’s supervision, we realized that we could combine behavioral, eye-tracking, and EEG data acquisition and analysis methods to help us understand the strategies people were using to solve video game tasks and what brain systems they might be using to employ these strategies.

In our recent publication,

“We present a novel method of combining eye tracking with specially designed virtual environments to provide objective evidence of navigational strategy selection. A simple, inexpensive video camera with an easily built infrared LED array is used to capture eye movements at 60 Hz. Simple algorithms analyze gaze position at the start of each virtual maze trial to identify stimuli used for navigational orientation. To validate the methodology, human participants were tested in two virtual environments which differed with respect to features usable for navigation and which forced participants to use one or another of two well-known navigational strategies. Because the environmental features for the two kinds of navigation were clustered in different regions of the environment (and the video display), a simple analysis of gaze position during the first (i.e., orienting) second of each trial revealed which features were being attended to, and therefore, which navigational strategy was about to be employed on the upcoming trial.”

Livingstone-Lee, S.A., Murchison, S.C., Zeman, P.M., Gandhi, M.M., van Gerven, D.J., Stewart, L., Livingston, N.J., & Skelton, R.W. (2011) Simple Gaze Analysis and Special Design of a Virtual Morris Water Maze Provides a New Method for Differentiating Egocentric and Allocentric Navigational Strategy Choice. Behavioural Brain Research, 225, 117-125.

The video below provides a simple example of one of the 1st-person perspective virtual environments the Skelton lab has been using to investigate spatial navigation cognition.  The person playing the game of course does not have the view with the location of eye-gaze and millisecond logger displayed on their screen.  The depiction in the video is a portion of the data we store to help us in our analysis.

More information about the equipment we used is available on Dr. Skelton’s site: http://web.uvic.ca/psyc/skelton/Arena/EyeTracker.htm

Feel free to contact me (Dr. Zeman) if you have any questions about this article, the work we do, or if you’re interested in my experience working with this type of eye tracking equipment.

Palomar College: Adapting to High Altitude
http://anthro.palomar.edu/adapt/adapt_3.htm

Altitude.ORG
http://www.altitude.org/high_altitude.php

Finding Altitude: Google Map Tool
http://www.altitude.org/find_altitude.php

International HAPE database: Register as research participant
http://www.altitude.org/hape.php

Princeton University: Outdoor Action Home Page
http://www.princeton.edu/~oa/index.shtml

Princeton University: Altitude Safety
http://www.princeton.edu/~oa/safety/altitude.html

TheSportJournal.Org: Monthly Refereed Sports Journal, Published By The United Stages Sports Academy
http://www.thesportsjournal.org

Acclimatization in High-Altitude Sport: Predictive Modeling of Oxygen Saturation as an Expedition Managements Tool
http://www.thesportjournal.org/article/acclimatization-high-altitude-sport-predictive-modeling-oxygen-saturation-expedition-managem

International Society for Mountain Medicine
http://www.ismmed.org/

An Altitude Tutorial
http://www.ismmed.org/np_altitude_tutorial.htm

Excerpt from the original article: “A brain implant developed at the University of Michigan uses the body’s skin like a conductor to wirelessly transmit the brain’s neural signals to control a computer, and may eventually be used to reactivate paralyzed limbs.

The implant is called the BioBolt, and unlike other neural interface technologies that establish a connection from the brain to an external device such as a computer, it’s minimally invasive and low power, said principal investigator Euisik Yoon, a professor in the U-M College of Engineering, Department of Electrical Engineering and Computer Science.

Currently, the skull must remain open…..” (go to the University of Michigan site for the rest of the article)

While the algorithms appears to have cleaned the data by doing a fairly good job of removing these nasty eye-movement and eye-blink artefacts, one must acknowledge that there are limits to what the algorithm can do.  Namely, for any instant that the raw EEG data are clipped (the signal saturates the EEG amplifier/digitizer) the ‘artefact’ can not be cleaned from the data to reveal uncontaminated brain activity-related EEG for the duration the EEG is clipped.  I have not provided a sample of clipped data in this example.

I welcome all comments and critiques sent to my email address listed on this site.

Regards,

~Philip Zeman

Figure 1. Eye Blinks and Movement: Raw EEG is given in red; Cleaned EEG is given in Blue.

Figure 2. Eye Blinks and Movement (Zoomed-In): Raw EEG is given in red; Cleaned EEG is given in Blue.

Background:

This was a difficult decision to make because the Emotiv headset presents us with a few challenges.  Our first challenge relates to the unique noise characteristics of the Emotive headset. Since the Emotive headset uses a ‘gel-free’ contact system, the noise characteristics differ from standard equipment and will thus have to be treated accordingly. The second challenge is that the Emotive systems has fewer electrodes as compared to standard EEG systems.  Standard systems typically employ 32 or more channels; this provides for up to 32 degrees of freedom for multivariate noise removal algorithms.  Since fewer channels are available on the Emotive headset, there are fewer degrees of freedom available for our multivariate noise removal methods.  We are creating new methods of noise removal to meet this challenge.

The New Software Release:

In providing support for the Emotiv system, our next software release will have two additional input parameters.  First, the user will be required to specify the type of hardware used to acquire the data.  Second, for cases of especially noisy data, the user has an option to stabilize statistics of new data to be cleaned with those of data previously recorded using the same hardware.

Heartbeat Removal Algorithm Background:

Our existing heartbeat removal algorithm was created out of necessity to remove heartbeat contamination from a client dataset.  As a result of our efforts, we now have an algorithm that not only removes the heartbeat contamination from the EEG, but also effectively isolates the heartbeat from the EEG so that it can be analyzed as a separate biometric signal.  The heartbeat rate can be obtained along with detail measures of the P-Q-R-S-T heartbeat constellation depending on data quality characteristics. (There are of course always limits; for example, the heartbeat must be present in the EEG in the first place so that it can be extracted from the EEG.)

We will be posting pictures, videos, and stories to entertain the avid armchair adventurer.

The biggest news is that we now have a new URDA client available for download.  We have made the decision that we can let prospective users download the client application at their leisure and afterwards sign-up for a user account.  This provides the opportunity to take a look at the interface prior to filling out our website form and minimizes some of our work on this end.

URDA Client Improvements

Display of Characteristics of Multiple Datasets- The client application now displays the technical characteristics of the data from multiple datasets.  This was a requirement for the system to concurrently process multiple participant datasets.

Client opens browser window when an error is encountered- We have added the functionality that the URDA client will open a web browser window when and error is encountered to display the reason and possible solution to the client/server error.  It is yet to be seen if this new functionality becomes a hindrance.  Presumably, experienced users will encounter fewer errors and have fewer ‘pop-ups’ of the web browser window.

A “credit” ticker system was added- This’ ticker’/credit system displays how much data you have processed. (It will be enabled on the server shortly.)

URDA Server Improvements

New Algorithm: Aggressive Wavelet-based EEG de-noising algorithm- We have just added this second algorithm to our system. It uses statistical process in multiple mathematical spaces to separate noise from brain-related activities.

Support for multiple participant and condition data files- The software now allows for batch cleaning of data collected for multiple participants and conditions.

*.edf file read bug fixed- There was an issue reading NeuroGuide generated *.edf files that was fixed. The system can now process both AppliedNeurosciences NeuroGuide *.edf and standard *.edf files.

Tip For Getting Better Cleaning Results

Use a high sampling rate rather than a low sampling rate.  It is advantageous to use higher than typical sampling rates because this helps the data cleaning algorithms identify artifacts in the EEG data.  I highly recommend using a sampling rate of 256 samples per second or higher. A sampling rate of 512 samples per second will yield wonderful results.  If data are sampled at a rate of 1024 samples per second, I can do some signal processing tricks that are not available for lower sampling rates.  Using very high sampling rates of 2048 samples per second creates a lot of data and this can become a problem.  Very high sampling rates do provide for incrementally improved artifact detection above a sampling rate of 1024 samples per second however it has a clear trade-off: the dataset becomes less manageable.

As always, if you have any questions or concerns, drop me an email and I will respond as promptly.

Regards,

Phil Zeman