PsychOpenXR - A high level driver for OpenXR supported XR hardware.

Copyright (c) 2022-2023 Mario Kleiner. Licensed to you under the MIT license.
Our underlying PsychOpenXRCore mex driver builds against the Khronos OpenXR SDK public
headers, and links against the OpenXR open-source dynamic loader, to implement the
interface to a system-installed OpenXR runtime. These components are dual-licensed by
Khronos under Apache 2.0 and MIT license: SPDX license identifier “Apache-2.0 OR MIT”

Note: If you want to write code that is portable across XR devices of
different vendors, then use the PsychVRHMD() driver instead of this
driver. The PsychVRHMD driver will use this driver as appropriate when
connecting to a OpenXR supported XR device, but it will also
automatically work with other head mounted displays. This driver does
however expose a few functions specific to OpenXR hardware, so you can
mix calls to this driver with calls to PsychVRHMD to do some mix & match.

For setup instructions for OpenXR, see “help OpenXR”.


oldverbosity = PsychOpenXR(‘Verbosity’ [, newverbosity]);

  • Get/Set level of verbosity for driver status messages, warning messages,
    error messages etc. ‘newverbosity’ is the optional new verbosity level,
    ‘oldverbosity’ is the currently set verbosity level - ie. before changing
    it. Valid settings are: 0 = Silent, 1 = Errors only, 2 = Warnings, 3 = Info,
    4 = Debug.

hmd = PsychOpenXR(‘AutoSetupHMD’ [, basicTask=’Tracked3DVR’][, basicRequirements][, basicQuality=0][, deviceIndex]);

  • Open a OpenXR device, set it up with good default rendering and
    display parameters and generate a PsychImaging(‘AddTask’, …)
    line to setup the Psychtoolbox imaging pipeline for proper display
    on the device. This will also cause the device connection to get
    auto-closed as soon as the onscreen window which displays on
    the device is closed. Returns the ‘hmd’ handle of the device on success.

By default, the first detected devide will be used and if no device
is connected, it will return an empty [] hmd handle. You can override
this default choice of device by specifying the optional ‘deviceIndex’
parameter to choose a specific device. However, only one device per machine is
supported, so the ‘deviceIndex’ will probably be only useful in the future.

More optional parameters: ‘basicTask’ what kind of task should be implemented.
The default is ‘Tracked3DVR’, which means to setup for stereoscopic 3D
rendering, driven by head motion tracking, for a fully immersive experience
in some kind of 3D virtual world. This is the default if omitted. The task
‘Stereoscopic’ sets up for display of stereoscopic stimuli, but without
head tracking. ‘Monoscopic’ sets up for display of monocular stimuli, ie.
the device is just used as a special kind of standard display monitor. In ‘Monoscopic’
and ‘Stereoscopic’ mode, both eyes will be presented with an identical field of view,
to make sure pure 2D drawing works, without the need for setup of special per-eye
projection transformations. In ‘Tracked3DVR’ mode, each eye will have a different
field of view, optimized to maximize the viewable area while still avoiding occlusion
artifacts due to the nose of the wearer of the device.

In monoscopic or stereoscopic mode, you can change the imaging parameters, ie.,
apparent size and location of the 2D views used with the following command to
optimize visual display:

[oldPosition, oldSize, oldOrientation] = PsychOpenXR(‘View2DParameters’, hmd, eye [, position][, size][, orientation]);

‘basicRequirements’ defines basic requirements for the task. Currently
defined are the following strings which can be combined into a single
‘basicRequirements’ string:

‘ForceSize=widthxheight’ = Enforce a specific fixed size of the stimulus
image buffer in pixels, overriding the recommmended value by the runtime,
e.g., ‘ForceSize=2200x1200’ for a 2200 pixels wide and 1200 pixels high
image buffer. By default the driver will choose values that provide good
quality for the given XR display device, which can be scaled up or down
with the optional ‘pixelsPerDisplay’ parameter for a different quality vs.
performance tradeoff in the function PsychOpenXR(‘SetupRenderingParameters’);
The specified values are clamped against the maximum values supported by
the given hardware + driver combination.

‘Float16Display’ = Request rendering, compositing and display in 16 bpc float
format. This will ask Psychtoolbox to render and post-process stimuli in 16 bpc
linear floating point format, and allocate 16 bpc half-float textures as final
renderbuffers to be sent to the VR compositor. If the VR compositor takes advantage
of the high source image precision is at the discretion of the compositor and device.
By default, if this request is omitted, processing and display in sRGB format is
requested from Psychtoolbox and the compositor, ie., a roughly gamma 2.2 8 bpc
format is used.

‘ForbidMultiThreading’ = Forbid any use of multi-threading for visual
presentation by the driver for any means or purposes! This is meant to
get your setup going in case of severe bugs in proprietary OpenXR
runtimes that can cause instability, hangs, crashes or other malfunctions
when multi-threading is used. Or if one wants to squeeze out every last
bit of performance, no matter the consequences (“Fast and furious mode”).
On many proprietary OpenXR runtimes, this will prevent any reliable,
trustworthy, robust or accurate presentation timing or timestamping, and
may cause severe visual glitches under some modes of operation. See the
following keywords below for descriptions of various more nuanced
approaches to multi-threading vs. single-threading to choose fine-tuned
tradeoffs between performance, stability and correctness for your
specific experimental needs.

‘Use2DViewsWhen3DStopped’ = Ask the driver to switch to use of the same 2D views
and geometry during the ‘3DVR’ or ‘Tracked3DVR’ basicTask as would be used
for pure 2D display in basicTask ‘Stereoscopic’ whenever the user script
signals it does not execute a tight tracking and animation loop, ie.
whenever the script calls PsychVRHMD(‘Stop’, hmd). Switch back to regular
3D projected geometry and views after a consecutive PsychVRHMD(‘Start’, hmd).
This is useful if have phases in your experiment session when you want to
display non-tracked content, e.g., instructions or feedback to the
subject between trials, fixation crosses, etc., or pause script execution
for more than a few milliseconds, but still want the visual display to
stay stable. If this keyword is omitted, depending on the specific OpenXR
runtime in use, the driver will stabilize the regular 3D projected
display by use of multi-threaded operation when calling PsychVRHMD(‘Stop’, hmd),
and resume single-threaded operation after PsychVRHMD(‘Start’, hmd). This
higher overhead mode of operation via multi-threading will possibly have
degraded performance, and not only between the ‘Stop’ and ‘Start’ calls,
but throughout the whole session! This is why it can be advisable to
evaulate if use of the ‘Use2DViewsWhen3DStopped’ keyword is a better
solution for your specific experiment paradigm. The switching between 3D
projected view and standard 2D stereoscopic view will change the image
though, which may disorient the subject for a moment while the subjects
eyes need to adapt their accomodation, vergence and focus point. You can
change the imaging parameters, ie., apparent size and location of the 2D
views used in this mode with the following command to minimize visual

[oldPosition, oldSize, oldOrientation] = PsychOpenXR(‘View2DParameters’, hmd, eye [, position][, size][, orientation]);

For such 2D views you can also specify the distance of the virtual
viewscreen in meters in front of the eyes of the subject. By default the
distance is 1 meter and the size and position is set up to fill out the
field of view in a meaningful way, essentially covering the whole
available field of view. By overriding the distance to a smaller or
bigger distance than 1 meter, you can “zoom in” to the image, or make
sure that also the corners and edges of the image are visible. E.g., the
following keyword would place the virtual screen at 2.1 meters distance:


‘DontCareAboutVisualGlitchesWhenStopped’ = Tell the driver that you don’t
care about potential significant visual presentation glitches happening if
your script does not run a continuous animation with high framerate, e.g.,
after calling PsychVRHMD(‘Stop’, hmd), pausing, etc. This makes sense if
you don’t care, or if your script does not ever pause or slow down during
a session or at least an ongoing trial. This will avoid multi-threading
for glitch prevention in such cases, possibly allowing to side-step
certain bugs in proprietary OpenXR runtimes, or to squeeze out higher
steady-state performance.

‘NoTimingSupport’ = Signal no need at all for high precision and reliability
timing for presentation. If you don’t need any timing precision or
reliability in your script, specifying this keyword may allow the driver
to optimize for higher performance. See ‘TimingSupport’ explanation right

‘TimingSupport’ = Use high precision and reliability timing for presentation.

The current OpenXR specification, as of OpenXR version v1.0.26 from January 2023,
does not provide any means of reliable, trustworthy, accurate timestamping of
presentation, and all so far tested proprietary OpenXR runtime implementations
have severely broken and defective timing support. Only the open-source
Monado OpenXR runtime on Linux provides a reliable and accurate timing
implementation. Therefore this driver has to use a workaround on non-Monado
OpenXR runtimes to achieve at least ok’ish timing if you require it, and
that workaround involves multi-threaded operation. This multi-threading
in turn can severely degrade performance, possibly reducing achievable
presentation framerates to (less than) half of the maximum video refresh
rate of your device! For this reason you should only request ‘TimingSupport’
on non-Monado if you really need it and be willing to pay the performance

If you omit this keyword, the driver will try to guess if you need
precise presentation timing for your session or not. As long as you only
call Screen(‘Flip’, window) or Screen(‘Flip’, window, [], …), ie. don’t
specify a requested stimulus onset time, the driver assumes you don’t
need precise timing, just presenting as soon as possible after a
Screen(‘Flip’), and also that you don’t care about accurate or trustworthy
or correct presentation timestamps to be returned by Screen(‘Flip’). Once
you specify a target onset time tWhen, ie. via calling ‘Flip’ as
Screen(‘Flip’, window, tWhen [, …]), the driver assumes from then on
and for the rest of the session that you want reasonably accurate
presentation timing. It will then switch to multi-threaded operation with
better timing, but potentially drastically reduced performance.

‘TimestampingSupport’ = Use high precision and reliability timestamping for presentation.

‘NoTimestampingSupport’ = Do not need high precision and reliability timestamping for presentation.
Those keywords let you specify if you definitely need or don’t need
trustworthy, reliable, robust, precise presentation timestamps, ie. the
‘timestamp’ return values of timestamp = Screen(‘Flip’) should be high
quality, or if you don’t care. If you omit both keywords, the driver will
try to guess what you wanted. On most current OpenXR runtimes, use of
timestamping will imply multi-threaded operation with the performance
impacts and problems mentioned above in the section about ‘TimingSupport’,
that is why it is advisable to explicitely state your needs, to allow the
driver to optimize for the best precision/reliability/performance
tradeoff on all the runtimes where such a tradeoff is required.

As mentioned here, in “help PsychVRHMD” and our “help OpenXR” overview
and setup instructions, currently no standard OpenXR implementation with
reliable and trustworthy timestamping exists. Proper enhancements to
OpenXR will need to be done in the future. Right now, as of Psychtoolbox, we have a hacky solution for a subset of Linux users, called
“Monado metrics timestamping hack”. It goes as follows:

If you need reliable timestamping, the only solution right now is to use
Linux + the latest Monado upstream version + a modified version of Mesa + an
AMD or Intel gpu of sufficient performance + a VR HMD supported by Monado
on Linux. Contact our paid support “help PsychPaidSupportAndServices” for
help in setting up this feature and getting suitable modified Monado and
Mesa drivers. Once everything is installed on the hardware and software
side, the following steps need to be taken at the start of each
experiment session to enable the special Monado metrics timestamping hack
for trustworthy timestamping at the price of lowered performance:

1. Create a Linux fifo pipe file, e.g., in a terminal type  
   "sudo mkfifo /usr/local/framequeue.protobuf"  
   You can choose any file path and name instead of  
   /usr/local/framequeue.protobuf but it makes sense to choose a  
   directory which is under your users control, not a temporary  
   directory, unless you want to repeat step 1 after each system  
   reboot. In steps 2 and 3 you must path the same path/filename to  
   both monado-service and Octave/Matlab via the XRT\_METRICS\_FILE  
   environment variable.  
2. Start monado-service and use the created fifo file as output file  
   for the metrics log, e.g., in a terminal window via  
   "XRT\_METRICS\_FILE=/usr/local/framequeue.protobuf XRT\_METRICS\_EARLY\_FLUSH=true monado-service"  
   This will launch the monado-service [OpenXR](OpenXR) compositor, enable its  
   metrics logging with low latency into the fifo, and block its  
   startup until the Psychtoolbox XR work session is started.  
3. Start a PTB session, also with XRT\_METRICS\_FILE environment variable  
   specified to the same fifo file location during launch of Octave or  
   Matlab, e.g., in a terminal start Octave or Matlab via:  
   "XRT\_METRICS\_FILE=/usr/local/framequeue.protobuf octave --gui" or  
   "XRT\_METRICS\_FILE=/usr/local/framequeue.protobuf matlab"  
   Once the [PsychOpenXR](PsychOpenXR) driver has detected that a Monado XR server is  
   running, and that the fifo file exists and is accessible, it opens  
   that fifo for read access, which will let monado-service fully start  
   up and get ready to serve [OpenXR](OpenXR) clients. Your Psychtoolbox session  
   should then work with trustworthy timestamps, but at potentially  
   significantly reduced performance, e.g., a framerate of only half  
   or a third of the refresh rate of your VR HMD display.  

‘Eyetracking’ = Request eye gaze tracking via a supported HMD builtin eye tracker.
This keyword asks the driver to enable eye gaze tracking. A given combo
of VR/AR/MR device (and its builtin eye tracker), operating system, OpenXR
runtime and additional optionally installed eye tracking software, may
support multiple different gaze tracking api’s and runtimes. By default,
the driver will try to use the most capable gaze tracking api, ie. the
one which provides the most detailed and exhaustive information about the
users gaze, at the highest sampling rate, with the most flexibility. It
will fall back to less capable or efficient tracking api’s if more
capable ones are not supported or available. For this reason, the amount
of information can differ widely between the most capable api’s and the
most basic api’s. User scripts which strive to be usable on different
operating systems, software setups or eyetracking hardware and HMDs must
therefore be written in a defensive and adaptive way to be able to work
with only the minimal subset of information guaranteed to be available on
all implementations. The info struct returned by info = PsychVRHMD(‘GetInfo’);
contains info about basic gaze tracking capabilities as a bitmask in
info.eyeTrackingSupported: A value of +1 means at least one gaze vector
is reported. A value of +2 means reporting of binocular eye tracking data
is supported. A value of +1024 means that HTC’s proprietary SRAnipal
eyetracking is used for more extensive gaze data reporting.

If eye tracking is requested via the keyword and supported, then the user
script can request return of the most recent eye gaze tracking sample
data by calling the state = PsychVRHMD(‘PrepareRender’, …, reqmask, …)
function with reqmask flag +4. This will cause the returned ‘state’ struct
to contain additional fields with information about the most recent gaze.
See help text for the ‘PrepareRender’ function for more detailed info.

The current driver supports the following gazetracking implementations:

  • With HTC VR HMDs with eyetracking support, under Microsoft Windows, in
    combination with the optional HTC SRAnipal runtime DLL’s installed, and
    using Matlab, an optional SRAnipal mex driver can be used to provide both
    binocular per-eye gaze tracking data, separate for the subjects left and
    right eye, and a virtual 3rd “cyclops eye” which is synthesized info from
    both hardware eye trackers, sometimes of higher quality due to sensor
    fusion of the two gaze tracker data streams. For each of both eyes, in
    addition to eye gaze position and direction, estimated pupil size in
    millimeters and a measure of eye openess is reported, e.g., for eye
    blink detection or estimation of gaze data reliability. Reported times
    are hardware timestamps of when a gaze sample was measured. On the tested
    “HTC Vive Pro Eye” HMD sampling rates of up to 120 Hz were possible.

  • On other device + operating system + OpenXR runtime combos with OpenXR
    gazetracking support, information from the XR_EXT_eye_gaze_interaction
    gaze tracking extension is returned. This extension is supported on a wider
    range of XR devices, but the returned information is more limited: A
    single eye gaze vector and position, but without any information about the
    subjects eye openess, pupil size or of the systems confidence in the quality
    of the measured gaze. The gaze vector is of unspecified origin. It could
    be measured gaze from a monocular eye tracker, ie. either left or right eye
    gaze, or it could be a “cyclops eye” synthesized gaze computed via sensor
    fusion of gaze data from a binocular gaze tracker. The gaze data may be
    measured data from a time in the past, or interpolated or extrapolated
    gaze data from one or more past measured eye gaze samples. The returned
    gaze sample timestamp may be a hardware timestamp of when the gaze sample
    was measured, but could also be the time for which gaze was predicted via
    interpolation or extrapolation of past hardware measured gaze samples.
    Temporal resolution of the gaze data is also unspecified. On the tested
    HTC Vive Pro Eye, the reported gaze seems to correspond to the sensor
    fusion of gaze samples from the binocular eye tracker, and the temporal
    resolution is reduced to at best 16.6 msecs for at most 60 gaze samples
    per second.

‘basicQuality’ defines the basic tradeoff between quality and required
computational power. A setting of 0 gives lowest quality, but with the
lowest performance requirements. A setting of 1 gives maximum quality at
maximum computational load. Values between 0 and 1 change the quality to
performance tradeoff.

hmd = PsychOpenXR(‘Open’ [, deviceIndex], …);

  • Open device with index ‘deviceIndex’. See PsychOpenXRCore Open?
    for help on additional parameters.

PsychOpenXR(‘SetAutoClose’, hmd, mode);

  • Set autoclose mode for device with handle ‘hmd’. ‘mode’ can be
    0 (this is the default) to not do anything special. 1 will close
    the device ‘hmd’ when the onscreen window is closed which displays
    on the device. 2 will do the same as 1, but close all open HMDs and
    shutdown the complete driver and OpenXR runtime - a full cleanup.

isOpen = PsychOpenXR(‘IsOpen’, hmd);

  • Returns 1 if ‘hmd’ corresponds to an open device, 0 otherwise.

PsychOpenXR(‘Close’ [, hmd]);

  • Close provided device ‘hmd’. If no ‘hmd’ handle is provided,
    all HMDs will be closed and the driver will be shutdown.

PsychOpenXR(‘Controllers’, hmd);

  • Return a bitmask of all connected controllers: Can be the bitand
    of the OVR.ControllerType_XXX flags described in ‘GetInputState’.

info = PsychOpenXR(‘GetInfo’, hmd);

  • Retrieve a struct ‘info’ with information about the device ‘hmd’.
    The returned info struct contains at least the following standardized
    fields with information:

handle = Driver internal handle for the specific device.
driver = Function handle to the actual driver for the device, e.g., @PsychOpenXR.
type = Defines the type/vendor of the device, e.g., ‘OpenXR’.
modelName = Name string with the name of the model of the device, e.g., ‘Rift DK2’.
separateEyePosesSupported = 1 if use of PsychOpenXR(‘GetEyePose’) will improve
the quality of the VR experience, 0 if no improvement
is to be expected, so ‘GetEyePose’ can be avoided
to save processing time without a loss of quality.
This *always* returns 0 on this PsychOpenXR driver.

eyeTrackingSupported = Info about eye gaze tracking capabilities. A value
of +1 means at least one gaze vector is reported. A value of +2 means
reporting of binocular per-eye tracking data is supported. A value of
+1024 means that HTC’s proprietary SRAnipal eyetracking is available for
more extensive gaze data reporting.

The returned struct may contain more information, but the fields mentioned
above are the only ones guaranteed to be available over the long run. Other
fields may disappear or change their format and meaning anytime without
warning. See ‘help PsychVRHMD’ for more detailed info about available fields.

isSupported = PsychOpenXR(‘Supported’);

  • Returns 1 if the OpenXR driver is functional, 0 otherwise. The
    driver is functional if the VR runtime library was successfully
    initialized and a connection to the VR server process has been
    established. It would return 0 if the server process would not be
    running, or if the required runtime library would not be correctly

[isVisible, playAreaBounds, OuterAreaBounds] = PsychOpenXR(‘VRAreaBoundary’, hmd [, requestVisible]);

  • Request visualization of the VR play area boundary for ‘hmd’ and returns its
    current extents.

‘requestVisible’ 1 = Request showing the boundary area markers, 0 = Don’t
request showing the markers. This parameter is accepted, but ignored for OpenXR.

Returns in ‘isVisible’ the current visibility status of the VR area boundaries.
This driver always returns 0 for false / invisible.

‘playAreaBounds’ is a 3-by-n matrix defining the play area boundaries. Each
column represents the [x;y;z] coordinates of one 3D definition point. Connecting
successive points by line segments defines the boundary, as projected onto the
floor. Points are listed in clock-wise direction. An empty return argument means
that the play area is so far undefined. This driver returns empty if the boundaries
are unknown. Otherwise it returns the bounding rectangle of the area, as current
unextended OpenXR runtimes can only return a rectangle, not more complex boundaries.

‘OuterAreaBounds’ defines the outer area boundaries in the same way as
‘playAreaBounds’. This driver currently returns the same as ‘playAreaBounds’, as
current unextended OpenXR only supports that information.

input = PsychOpenXR(‘GetInputState’, hmd, controllerType);

  • Get input state of controller ‘controllerType’ associated with device ‘hmd’.

‘controllerType’ can be one of OVR.ControllerType_LTouch, OVR.ControllerType_RTouch,
OVR.ControllerType_Touch, OVR.ControllerType_Remote, OVR.ControllerType_XBox, or
OVR.ControllerType_Active for selecting whatever controller is currently active.

Return argument ‘input’ is a struct with fields describing the state of buttons and
other input elements of the specified ‘controllerType’. It has the following fields:

‘Valid’ = 1 if ‘input’ contains valid results, 0 if input status is invalid/unavailable.
‘Time’ Time of last input state change of controller.
‘ActiveInputs’ = Bitmask defining which of the following struct elements do contain
meaningful input from actual physical input source devices. This is a more fine-grained
reporting of what ‘Valid’ conveys, split up into categories. The following flags will be
logical or’ed together if the corresponding input category is valid, ie. provided with
actual input data from some physical input source element, controller etc.:

+1 = ‘Buttons’ gets input from some real buttons or switches.
+2 = ‘Touches’ gets input from some real touch/proximity sensors or gesture recognizers.
+4 = ‘Trigger’ gets input from some real analog trigger sensor or gesture recognizer.
+8 = ‘Grip’ gets input from some real analog grip sensor or gesture recognizer.
+16 = ‘Thumbstick’ gets input from some real thumbstick, joystick or trackpad or similar 2D sensor.
+32 = ‘Thumbstick2’ gets input from some real secondary thumbstick, joystick or trackpad or similar 2D sensor.

‘Buttons’ Vector with button state on the controller, similar to the ‘keyCode’
vector returned by KbCheck() for regular keyboards. Each position in the vector
reports pressed (1) or released (0) state of a specific button. Use the OVR.Button_XXX
constants to map buttons to positions.

‘Touches’ Like ‘Buttons’ but for touch buttons. Use the OVR.Touch_XXX constants to map
touch points to positions.

‘Trigger’(1/2) = Left (1) and Right (2) trigger: Value range 0.0 - 1.0, filtered and with dead-zone.
‘TriggerNoDeadzone’(1/2) = Left (1) and Right (2) trigger: Value range 0.0 - 1.0, filtered.
‘TriggerRaw’(1/2) = Left (1) and Right (2) trigger: Value range 0.0 - 1.0, raw values unfiltered.
‘Grip’(1/2) = Left (1) and Right (2) grip button: Value range 0.0 - 1.0, filtered and with dead-zone.
‘GripNoDeadzone’(1/2) = Left (1) and Right (2) grip button: Value range 0.0 - 1.0, filtered.
‘GripRaw’(1/2) = Left (1) and Right (2) grip button: Value range 0.0 - 1.0, raw values unfiltered.

‘Thumbstick’ = 2x2 matrix: Column 1 contains left thumbsticks [x;y] axis values, column 2 contains
right sticks [x;y] axis values. Values are in range -1 to +1, filtered and with deadzone applied.
‘ThumbstickNoDeadzone’ = Like ‘Thumbstick’, filtered, but without a deadzone applied.
‘ThumbstickRaw’ = ‘Thumbstick’ raw date without deadzone or filtering applied.

‘Thumbstick2’ = Like ‘Thumbstick’, but for devices with a 2nd 2D input device for each hand, e.g.,
a 2nd thumbstick or a trackpad.

pulseEndTime = PsychOpenXR(‘HapticPulse’, hmd, controllerType [, duration=2.5][, freq=1.0][, amplitude=1.0]);

  • Trigger a haptic feedback pulse, some controller vibration, on the
    specified ‘controllerType’ associated with the specified ‘hmd’.

Currently supported values for ‘controllerType’ are:

OVR.ControllerType_XBox - The Microsoft XBox controller or compatible gamepad.
OVR.ControllerType_Remote - Connected remote control or similar, e.g., control buttons on device.
OVR.ControllerType_LTouch - Haptic enabled left hand controller.
OVR.ControllerType_RTouch - Haptic enabled right hand controller.
OVR.ControllerType_Touch - All haptics enabled hand controllers.
OVR.ControllerType_Active - All active haptics enabled controllers.

‘duration’ is requested pulse duration in seconds. By default a pulse of
2.5 seconds duration is executed, as this is the maximum pulse duration
supported by Oculus Rift CV1 touch controllers. Other controllers or
OpenXR runtimes may have different limits on pulse duration, or no limit
at all. A duration of 0 maps to the minimum duration supported by the
active OpenXR runtime and device. ‘freq’ may be a normalized frequency in
range 0.0 - 1.0, or a higher frequency in Hz. A value of 0 will disable
an ongoing pulse. The range up to 1.0 gets mapped to the interval 0 - 320
Hz for backwards compatibility with older Oculus VR drivers. Values
greater than 1 are interpreted as desired frequency in Hz. OpenXR
runtimes and hardware may clamp the requested frequency to implementation
dependent minimum or maximum values, or quantize to only a few discrete
frequencies. E.g., Oculus touch controllers only support 160 Hz and 320
Hz, no other frequencies. ‘amplitude’ is the amplitude of the vibration
in normalized 0.0 - 1.0 range.

‘pulseEndTime’ returns the expected stop time of vibration in seconds,
given the parameters. This may be inaccurate, depending on OpenXR runtime
and hardware.

In general, unfortunately, testing so far shows that OpenXR runtimes vary
considerably in how well they follow the requested haptic pulse duration,
frequency, and timing, so some caution is advised wrt. haptic pulse
feedback. Never trust a given software + hardware combo blindly, always
verify your specific setup!

state = PsychOpenXR(‘PrepareRender’, hmd [, userTransformMatrix][, reqmask=1][, targetTime]);

  • Mark the start of the rendering cycle for a new 3D rendered stereoframe.
    Return a struct ‘state’ which contains various useful bits of information
    for 3D stereoscopic rendering of a scene, based on head tracking data.

‘hmd’ is the handle of the device which delivers tracking data and receives the
rendered content for display.

‘reqmask’ defines what kind of information is requested to be returned in
struct ‘state’. Only query information you actually need, as computing some
of this info is expensive! See below for supported values for ‘reqmask’.

‘targetTime’ is the expected time at which the rendered frame will display.
This could potentially be used by the driver to make better predictions of
camera/eye/head pose for the image. Omitting the value will use a target time
that is implementation specific, but known to give generally good results,
e.g., the midpoint of scanout of the next video frame.

‘userTransformMatrix’ is an optional 4x4 right hand side (RHS) transformation
matrix. It gets applied to the tracked head pose as a global transformation
before computing results based on head pose like, e.g., camera transformations.
You can use this to translate the “virtual head” and thereby the virtual eyes/
cameras in the 3D scene, so observer motion is not restricted to the real world
tracking volume of your headset. A typical ‘userTransformMatrix’ would be a
combined translation and rotation matrix to position the observer at some
3D location in space, then define his/her global looking direction, aka as
heading angle, yaw orientation, or rotation around the y-axis in 3D space.
Head pose tracking results would then operate relative to this global transform.
If ‘userTransformMatrix’ is left out, it will default to an identity transform,
in other words, it will do nothing.

state always contains a field state.tracked, whose bits signal the status
of head tracking for this frame. A +1 flag means that head orientation is
tracked. A +2 flag means that head position is tracked via some absolute
position tracker like, e.g., the Oculus Rift DK2 or Rift CV1 camera. A +128
flag means the device is actually strapped onto the subjects head and displaying
our visual content. Lack of this flag means the device is off and thereby blanked
and dark, or we lost access to it to another application.

state also always contains a field state.SessionState, whose bits signal general
VR session status:
+1 = Our rendering goes to the device, ie. we have control over it. Lack of this could
mean the Health and Safety warning is displaying at the moment and waiting for
acknowledgement, or the OpenXR GUI application is in control.
+2 = Device is present and active.
+4 = Device is strapped onto users head. A Rift CV1 would switch off/blank if not on the head.
+8 = DisplayLost condition! Some hardware/software malfunction, need to completely quit this
Psychtoolbox session to recover from this.
+16 = ShouldQuit The user interface / user asks us to voluntarily terminate this session.
+32 = ShouldRecenter = The user interface asks us to recenter/recalibrate our tracking origin.

‘reqmask’ defaults to 1 and can have the following values added together:

+1 = Return matrices for left and right “eye cameras” which can be directly
used as OpenGL GL_MODELVIEW matrices for rendering the scene. 4x4 matrices
for left- and right eye are contained in state.modelView{1} and {2}.

 Return position and orientation 4x4 camera view matrices which describe  
 position and orientation of the "eye cameras" relative to the world  
 reference frame. They are the inverses of state.modelView{}. These  
 matrices can be directly used to define cameras for rendering of complex  
 3D scenes with the [Horde3D](Horde3D) 3D engine. Left- and right eye matrices are  
 contained in state.cameraView{1} and state.cameraView{2}.  
 Additionally tracked/predicted head pose is returned in state.localHeadPoseMatrix  
 and the global head pose after application of the 'userTransformMatrix' is  
 returned in state.globalHeadPoseMatrix - this is the basis for computing  
 the camera transformation matrices.  

+2 = Return matrices for tracked left and right hands of user, ie. of tracked positions
and orientations of left and right XR input controllers, if any.

 state.handStatus(1) = Tracking status of left hand: 0 = Untracked, 1 = Orientation  
                       tracked, 2 = Position tracked, 3 = Orientation and position  
                       tracked. If handStatus is == 0 then all the following information  
                       is invalid and can not be used in any meaningful way.  
 state.handStatus(2) = Tracking status of right hand.  
 state.localHandPoseMatrix{1} = 4x4 [OpenGL](OpenGL) right handed reference frame matrix with  
                                hand position and orientation encoded to define a  
                                proper GL\_MODELVIEW transform for rendering stuff  
                                "into"/"relative to" the oriented left hand.  
 state.localHandPoseMatrix{2} = Ditto for the right hand.  
 state.globalHandPoseMatrix{1} = userTransformMatrix \* state.localHandPoseMatrix{1};  
                                 Left hand pose transformed by passed in userTransformMatrix.  
 state.globalHandPoseMatrix{2} = Ditto for the right hand.  
 state.globalHandPoseInverseMatrix{1} = Inverse of globalHandPoseMatrix{1} for collision  
                                        testing/grasping of virtual objects relative to  
                                        hand pose of left hand.  
 state.globalHandPoseInverseMatrix{2} = Ditto for right hand.  

+4 = Return the most recent eye gaze information on devices with built-in eye tracking hardware.
Returned information may represent the latest available measured eye
gaze data, or it may be predicted eye gaze information for the
specified ‘targetTime’, computed via interpolation or extrapolation
from actual previously measured eye gaze. This is dependent on the
specific gaze tracker implementation of your system. If the reported
gaze sample timestamps are identical to the provided ‘targetTime’
then that is one possible indication that reported gaze may be
predicted gaze instead of a direct hardware measured gaze sample.

 The following fields are mandatory as part of the state struct, if gaze  
 tracking is supported and enabled and requested:  
 state.gazeRaw = If no new gaze tracking data is available, returns an  
 empty [] variable. Otherwise a variable in a format that is  
 dependent on the actually used gaze tracking api and implementation.  
 It could be a vector, a struct, an array of structs... The format  
 may change without prior notice, without any regard for backward  
 compatibility, so it is mostly useful for debugging by the PTB  
 developers or other Psychtoolbox internal special use cases, not to  
 be relied on by regular user experiment scripts!  
 The following variables are arrays, whose length depends on the  
 used gaze tracking method. Each array element represents properties  
 of one tracked eye gaze. At a minimum, the arrays have one element  
 for the most basic gaze tracking, e.g., if the [OpenXR](OpenXR) extension  
 XR\_EXT\_eye\_gaze\_interaction is used for gaze tracking, it will only  
 report one gaze vector in index 1: A monocular gaze sample from either  
 the left or right eye, or a synthetic "cyclops eye" gaze sample, computed  
 via sensor fusion of data from a binocular gazetracker. The arrays could  
 also have 2 elements for a purely binocular eye tracker, with index 1 for  
 the left eye, and index 2 for the right eye data. On a binocular tracker,  
 it is also possible for a three element array to be returned, in  
 which case index 1 is left eye date, 2 is right eye date, and 3 is  
 synthesized "cyclops eye" data.  
 Please write your scripts so they can handle any number of 1, 2 or  
 three array elements meaningfully:  
 state.gazeStatus(i) = A flag telling if i'th gaze is unavailable  
                       (=0), available (+1) or available and somewhat  
                       trustworthy (+2). Values other than 3 (=1+2)  
                       should not really be trusted. A value of only  
                       1 could, e.g., mean that data was reported,  
                       but it is not based on an actual measured eye  
                       gaze sample, but purely extrapolated or  
                       predicted from past valid data. A value of 3  
                       is not a guarantee of high quality data, just  
                       that the data is actually measured eye gaze  
                       data and passed the minimum quality treshold.  
 state.gazeTime(i) = A timestamp of the time for which the given  
 gaze information is valid, or the value [NaN](NaN) if no valid timestamp is  
 available from the gaze tracker. Depending on gaze tracking method in  
 use, this could be a time in the past, referring to the hardware  
 timestamp of when the gaze tracker hardware acquired that sample, or  
 it could be the time in the past or near future for which the gaze  
 data was computed via prediction / extrapolation of gaze movement or  
 interpolation from past gaze tracking data history. [OpenXR](OpenXR) built in  
 gaze tracking extensions often may not report the most recent  
 measured eye gaze sample from a past tracking cycle. Instead they  
 take the user provided 'targetTime' (or predicted stimulus onset  
 time for the next to-be-presented VR/AR/MR/XR stimulus image, if  
 'targetTime' was omitted) and try to predict where the subject will  
 be looking (for a 'targetTime' in the near future) or has looked  
 (for a 'targetTime' in the near past). In case of such prediction,  
 the reported state.gazeTime(i) corresponds to the time for which  
 gaze was actually predicted. It is a bit of a hazard for scientific  
 research purposes that there is some uncertainty if timestamps refer  
 to time of real measured gaze, or to some predicted time, or that  
 prediction / interpolation / extrapolation may be used instead of  
 reporting measured data, or that the prediction method - if any - is  
 not specified or standardized across different devices, gaze  
 trackers and gaze tracking runtimes and api's. This is unfortunately  
 unavoidable, as most commercial off the shelf gaze trackers for XR  
 applications are not targeted at scientific research use cases, but  
 as human computer interaction method for operating and navigating in  
 VR and AR, e.g., for gaming and entertainment purposes. Not much we  
 could do about this, so you will have to deal with this in your  
 research paradigm or carefully select hardware with known suitable  
 properties for your specific use case.  
 Actual gaze information is provided in two formats, a 2D format, in  
 onscreen window pixel coordinates, ie. where in the image has the  
 subject looked, and a 3D format, as 3D gaze rays, ie. where in a  
 rendered 3D scene has the subject looked:  

2D - Onscreen window referenced:

 state.gazePos{i} = A two-element [x,y] vector of the estimated 2D user  
 gaze position in Psychtoolbox onscreen window coordinates. Iow. the  
 x,y coordinates of where the user looked. In mono display mode this  
 is done by mapping the users gaze vector to the 2D space of the  
 common image that is displayed in the left and right eye display of  
 a VR/AR/MR HMD. In stereoscopic 2D display mode or full 3D perspective  
 correct rendering mode with potential head tracking, where a different  
 image is rendered and displayed to the subjects left and right eye, the  
 mapping of indices is as follows: state.gazePos{1} is expressed wrt.  
 to the left eye image buffer, ie. the one selected via  
 [Screen](Screen)('SelectStereoDrawBuffer', win, 0);. state.gazePos{2} refers  
 to the right eye image buffer ([Screen](Screen)('SelectStereoDrawBuffer', win, 0);).  
 state.gazePos{3} for a potential synthetic "cyclops eye" gaze will  
 reference the left eye image buffer again.  

3D - 3D scene geometry referenced:

 state.gazeRayLocal{i} = encodes the subjects gaze direction / line  
 of sight within a HMD fixed reference frame:  
 state.gazeRayLocal{i}.gazeC = a [x,y,z] 3D vector denoting the  
 estimated position of the optical center of the subjects eye balls,  
 relative to the origin of the head-fixed reference frame.  
 state.gazeRayLocal{i}.gazeD = a [dx,dy,dz] 3D vector denoting the  
 gaze direction in the head-fixed x, y and z axis.  
 The values in gazeRayLocal therefore define a 3D line equation  
 denoting the users line of sight, a "gaze ray" so to speak:  
 For all scalar values t from zero to infinity, p(t) with  
 p(t) = state.gazeRayLocal{i}.gazeC + t \* state.gazeRayLocal{i}.gazeD  
 defines 3D points along the looking direction / gaze vector / gaze  
 ray of the subject, in a head-fixed reference frame.  
 Mathematical intersection of such a defined line equation p(t) with 3D  
 scene geometry in 3D rendering mode that is fixed wrt. to the users head  
 allows you to figure out where the user is looking in 3D space.  
 For a typical 3D head tracked VR / AR / MR rendering scenario, where  
 you would also set the the 'reqmask' flag +1 to retrieve head  
 tracking information and state.modelView matrices for 3D rendering,  
 the function also provides state.gazeRayGlobal{i} of the same  
 format. In this case the HMD head tracking information is used to  
 locate the subjects head position and orientation in a 3D rendered  
 scene and the gaze ray is transformed accordingly, so mathematical  
 intersection of rendered 3D geometry with the 3D line equation ...  
 p(t) = state.gazeRayGlobal{i}.gazeC + t \* state.gazeRayGlobal{i}.gazeD  
 ... allows to find the point of fixation in a 3D world even if the  
 subject is moving their head or walking around.  
 Some of the supported eye tracking implementations may provide the  
 following additional optional information for each gaze index i. If  
 the information is not available for a given implementation, either  
 an empty vector [] or the scalar value [NaN](NaN) is returned:  
 state.gazeConfidence(i) = A scalar value of confidence, ie. how  
 certain is the gaze tracker that reported data is trustworthy and  
 accurate. Currently unsupported on all trackers, returns [NaN](NaN).  
 state.gazeEyeOpening(i) = A scalar value of how far the subjects  
 eyes are open, in a normalized range 0 for closed to 1 for fully  
 open. This can be used, e.g., as another confidence measure, or for  
 eye blink detection. Supported for i=1,2 with HTC [SRAnipal](SRAnipal) gaze  
 tracking on suitable HTC [HMDs](HMDs) like the HTC Vive Pro Eye.  
 state.gazeEyePupilDiameter(i) = The estimated diameter of the  
 subjects pupil, presumably in millimeters. Supported for i=1,2 with  
 HTC [SRAnipal](SRAnipal) gaze tracking on suitable HTC [HMDs](HMDs) like the HTC Vive Pro Eye.  
 state.gazeEyeConvergenceDistance = For binocular gaze tracking, this  
 may be a scalar estimate of eye convergence distance, ie. the  
 distance of the fixation point from the eyes. May be supported on  
 some HTC [HMDs](HMDs) under [SRAnipal](SRAnipal), but has not been confirmed to work in  
 practice on the tested HTC Vive Pro Eye.  

More flags to follow…

eyePose = PsychOpenXR(‘GetEyePose’, hmd, renderPass [, userTransformMatrix][, targetTime]);

  • Return a struct ‘eyePose’ which contains various useful bits of information
    for 3D stereoscopic rendering of the stereo view of one eye, based on head or
    eye tracking data. This function provides essentially the same information as
    the ‘PrepareRender’ function, but only for one eye. Therefore you will need
    to call this function twice, once for each of the two renderpasses, at the
    beginning of each renderpass. NOTE: The function only exists for backwards
    compatibility with existing older VR/AR/XR scripts. It does *not* provide any
    benefit on OpenXR VR/AR/XR devices, but instead may cause a performance decrease
    when used! It is recommended to not use it in new scripts.

‘hmd’ is the handle of the device which delivers tracking data and receives the
rendered content for display.

‘renderPass’ defines if information should be returned for the 1st renderpass
(renderPass == 0) or for the 2nd renderpass (renderPass == 1). The driver will
decide for you if the 1st renderpass should render the left eye and the 2nd
pass the right eye, or if the 1st renderpass should render the right eye and
then the 2nd renderpass the left eye. The ordering depends on the properties
of the video display of your device, specifically on the video scanout order:
Is it right to left, left to right, or top to bottom? For each scanout order
there is an optimal order for the renderpasses to minimize perceived lag.

‘targetTime’ is the expected time at which the rendered frame will display.
This could potentially be used by the driver to make better predictions of
camera/eye/head pose for the image. Omitting the value will use a target time
that is implementation specific, but known to give generally good results.

‘userTransformMatrix’ is an optional 4x4 right hand side (RHS) transformation
matrix. It gets applied to the tracked head pose as a global transformation
before computing results based on head pose like, e.g., camera transformations.
You can use this to translate the “virtual head” and thereby the virtual eyes/
cameras in the 3D scene, so observer motion is not restricted to the real world
tracking volume of your headset. A typical ‘userTransformMatrix’ would be a
combined translation and rotation matrix to position the observer at some
3D location in space, then define his/her global looking direction, aka as
heading angle, yaw orientation, or rotation around the y-axis in 3D space.
Head pose tracking results would then operate relative to this global transform.
If ‘userTransformMatrix’ is left out, it will default to an identity transform,
in other words, it will do nothing.

Return values in struct ‘eyePose’:

‘eyeIndex’ The eye for which this information applies. 0 = Left eye, 1 = Right eye.
You can pass ‘eyeIndex’ into Screen(‘SelectStereoDrawBuffer’, win, eyeIndex)
to select the proper eye target render buffer.

‘modelView’ is a 4x4 RHS OpenGL matrix which can be directly used as OpenGL
GL_MODELVIEW matrix for rendering the scene.

‘cameraView’ contains a 4x4 RHS camera matrix which describes position and
orientation of the “eye camera” relative to the world reference
frame. It is the inverse of eyePose.modelView. This matrix can
be directly used to define the camera for rendering of complex
3D scenes with the Horde3D 3D engine or other engines which want
absolute camera pose instead of the inverse matrix.

oldType = PsychOpenXR(‘TrackingOriginType’, hmd [, newType]);

  • Specify the type of tracking origin for OpenXR device ‘hmd’.
    This returns the current type of tracking origin in ‘oldType’.
    Optionally you can specify a new tracking origin type as ‘newType’.
    Type must be either:
    0 = Origin is at eye height (device height).
    1 = Origin is at floor height.
    The eye height or floor height gets defined by the system during
    sensor calibration, possibly guided by some OpenXR GUI control application.

PsychOpenXR(‘SetupRenderingParameters’, hmd [, basicTask=’Tracked3DVR’][, basicRequirements][, basicQuality=0][, fov=[HMDRecommended]][, pixelsPerDisplay=1])

  • Query the device ‘hmd’ for its properties and setup internal rendering
    parameters in preparation for opening an onscreen window with PsychImaging
    to display properly on the device. See section about ‘AutoSetupHMD’ above for
    the meaning of the optional parameters ‘basicTask’, ‘basicRequirements’
    and ‘basicQuality’.

‘fov’ Optional field of view in degrees, from line of sight: [leftdeg, rightdeg,
updeg, downdeg]. If ‘fov’ is omitted, the device runtime will be asked for a
good default field of view and that will be used. The field of view may be
dependent on the settings in the device user profile of the currently selected
user. Note: This parameter is ignored with the current driver in 3D mode, ie.
basicTask ‘3DVR’ or ‘Tracked3DVR’ on any standard OpenXR 1.0 backend, as the
driver auto-selects optimal field of view for 3D perspective correct rendering.
In the 2D modes ‘Monoscopic’ or ‘Stereoscopic’, or in 3D mode with stopped loop,
the specified field of view will be used for calculating position and size of the
2D views in use. If omitted the driver will try to auto-detect a meaningful field
of view. If that is impossible, it will use the hard-coded values of an Oculus
Rift CV-1 HMD as fallback. In all these cases, the ‘PerEyeFOV’ keyword will alter
the method of default view setup from one that only takes the minimal vertical
field of view min(updeg, downdeg) into account and calculates horizontal size to
preserve stimulus image aspect ratio, to one that takes all field of view parameters
into account, even if it causes distortions of shapes.

‘pixelsPerDisplay’ Ratio of the number of render target pixels to display pixels
at the center of distortion. Defaults to 1.0 if omitted. Lower values can
improve performance, at lower quality.

PsychOpenXR(‘SetBasicQuality’, hmd, basicQuality);

  • Set basic level of quality vs. required GPU performance.

oldSetting = PsychOpenXR(‘SetFastResponse’, hmd [, enable]);

  • Return old setting for ‘FastResponse’ mode in ‘oldSetting’,
    optionally disable or enable the mode via specifying the ‘enable’
    parameter as 0 or greater than zero.

Deprecated: This function does nothing. It just exists for (backwards)
compatibility with PsychVRHMD.

oldSetting = PsychOpenXR(‘SetTimeWarp’, hmd [, enable]);

  • Return old setting for ‘TimeWarp’ mode in ‘oldSetting’,
    optionally enable or disable the mode via specifying the ‘enable’
    parameter as 1 or 0.

Deprecated: This function does nothing. It just exists for (backwards)
compatibility with PsychVRHMD.

oldSetting = PsychOpenXR(‘SetLowPersistence’, hmd [, enable]);

  • Return old setting for ‘LowPersistence’ mode in ‘oldSetting’,
    optionally enable or disable the mode via specifying the ‘enable’
    parameter as 1 or 0.

Deprecated: This function does nothing. It just exists for (backwards)
compatibility with PsychVRHMD.

oldSettings = PsychOpenXR(‘PanelOverdriveParameters’, hmd [, newparams]);
Deprecated: This function does nothing. It just exists for (backwards)
compatibility with PsychVRHMD.

PsychOpenXR(‘SetHSWDisplayDismiss’, hmd [, dismissTypes=1+2+4]);

  • Set how the user can dismiss the “Health and safety warning display”.
    Deprecated: This function does nothing. It just exists for (backwards)
    compatibility with PsychVRHMD.

[bufferSize, imagingFlags, stereoMode] = PsychOpenXR(‘GetClientRenderingParameters’, hmd);

  • Retrieve recommended size in pixels ‘bufferSize’ = [width, height] of the client
    renderbuffer for each eye for rendering to the device. Returns parameters
    previously computed by PsychOpenXR(‘SetupRenderingParameters’, hmd).

Also returns ‘imagingFlags’, the required imaging mode flags for setup of
the Screen imaging pipeline. Also returns the needed ‘stereoMode’ for the

needPanelFitter = PsychOpenXR(‘GetPanelFitterParameters’, hmd);

  • ‘needPanelFitter’ is 1 if a custom panel fitter task is needed, and the ‘bufferSize’
    from the PsychVRHMD(‘GetClientRenderingParameters’, hmd); defines the size of the
    clientRect for the onscreen window. ‘needPanelFitter’ is 0 if no panel fitter is

[winRect, ovrfbOverrideRect, ovrSpecialFlags, ovrMultiSample, screenid] = PsychOpenXR(‘OpenWindowSetup’, hmd, screenid, winRect, ovrfbOverrideRect, ovrSpecialFlags, ovrMultiSample);

  • Compute special override parameters for given input/output arguments, as needed
    for a specific device. Take other preparatory steps as needed, immediately before the
    Screen(‘OpenWindow’) command executes. This is called as part of PsychImaging(‘OpenWindow’),
    with the user provided hmd, screenid, winRect etc.

isOutput = PsychOpenXR(‘IsHMDOutput’, hmd, scanout);

  • Returns 1 (true) if ‘scanout’ describes the video output to which the
    device ‘hmd’ is connected. ‘scanout’ is a struct returned by the Screen
    function Screen(‘ConfigureDisplay’, ‘Scanout’, screenid, outputid);
    This allows probing video outputs to find the one which feeds the device.
    Deprecated: This function does nothing. It just exists for (backwards)
    compatibility with PsychVRHMD.
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