Oculus Input Test sample overview

Updated: May 11, 2026

Overview

This sample provides 17 diagnostic UI panels and 67 Enhanced Input Actions that demonstrate the full range of Meta Quest input capabilities. It covers controller inputs, hand tracking, capacitive touch, microgestures, force-sensing triggers, and system-level interaction profiles. The 3D Widget Panel architecture makes it easy to explore each input category interactively.

View the sample source code on GitHub⁠.

What you will learn

Configure 67 Enhanced Input Actions for controller and hand tracking inputs

Use ControllersAndHands mode for simultaneous controller and hand input

Build 3D Widget Panel UI architecture with paired Actor BP and Widget BP components

Detect controller types using OpenXR interaction profiles

Access advanced inputs including capacitive touch, microgestures, and force-sensing triggers

Visualize input state across 17 diagnostic panels

Requirements

Meta Quest 2, Quest 3, or Quest 3S

Unreal Engine 5.5 with the MetaXR plugin

For build setup and configuration, see the sample README⁠.

Get started

Clone or download the sample from the GitHub repository. Open the project in Unreal Engine 5.5 with the MetaXR plugin installed. Build and deploy to your Meta Quest device. The sample presents a menu of diagnostic panels organized by input category. Point and select panels to explore each input type. Use both controllers and hands simultaneously in ControllersAndHands mode to test dual-input scenarios.

Explore the sample

File / Scene	What it demonstrates	Key concepts
Controller: Gamepad panel	Traditional gamepad-style inputs	Button presses, thumbstick axes
Controller: MotionController panel	6DoF controller tracking and buttons	Position, rotation, trigger, grip
Hand Tracking: Pinch panel	Pinch detection per finger	Pinch state, pinch strength
Hand Tracking: Strength panel	Grip and pinch force values	Analog hand tracking values
Advanced: CapTouch panel	Capacitive touch sensing on buttons	Near-touch and touch states
Advanced: Microgesture panel	Fine-grained finger gestures	Microgesture detection API
Advanced: Touchpad panel	Touchpad input on supported controllers	2D axis, touch state
System: InteractionProfile panel	OpenXR controller type detection	Interaction profile strings
System: HMD panel	Headset tracking and mounted state	HMD pose, proximity sensor
System: Performance panel	Frame timing and GPU/CPU metrics	Performance monitoring
3D Widget Panel (architecture)	Actor BP + Widget BP paired panels	Reusable 3D UI pattern

Runtime behavior

The sample displays a circular arrangement of 17 diagnostic panels in a passthrough environment. Each panel updates in real time as the user interacts with controllers or hands. The ControllersAndHands mode enables simultaneous tracking of both input modalities, showing how controllers and hands can coexist.

Input categories are organized as:

Controller: Gamepad and MotionController panels showing button, trigger, grip, and thumbstick state

Hand Tracking: Pinch and Strength panels showing per-finger pinch state and analog force values

Advanced: CapTouch, Microgesture, and Touchpad panels for specialized input hardware

System: InteractionProfile, HMD, and Performance panels for device-level information

Key concepts

Each diagnostic panel consists of a paired Actor Blueprint and Widget Blueprint:

`BP_Panel_`[Category] (Actor BP)
├── Contains 3D widget component
├── Handles placement and interaction
└── References WBP_Panel_[Category] (Widget BP)
    ├── Displays real-time input values
    └── Updates per-frame from Enhanced Input Actions

Enhanced Input Actions

The sample defines 67 Enhanced Input Actions across all input categories. Each action maps to a specific input signal:

// Example: Controller trigger with analog value
IA_Trigger_Left   // Float axis: 0.0 to 1.0
IA_Trigger_Right  // Float axis: 0.0 to 1.0

// Example: Hand tracking pinch
IA_Pinch_Index_Left   // Bool: pinch state
IA_PinchStrength_Index_Left  // Float: pinch force

OpenXR interaction profiles

The sample uses OpenXR interaction profiles to detect which controller type is connected at runtime, enabling controller-specific UI and input mapping without hardcoding device types.