A linear acceleration sensor measures the acceleration of a device along three perpendicular axes (X, Y, Z) excluding gravity. Unlike the standard accelerometer which includes gravitational pull (~9.8 m/s² downward), the linear acceleration sensor isolates pure motion acceleration. This allows apps to detect actual device movement—shaking, tilting, translation—without gravity's constant offset. The data is typically reported in meters per second squared (m/s²). Modern smartphones use sensor fusion algorithms combining accelerometer, gyroscope, and magnetometer data to separate gravity from motion acceleration.

The trajectory is computed through double integration of the linear acceleration data. First, acceleration is integrated over time to calculate velocity (v = ∫a·dt). Then velocity is integrated to calculate position (x = ∫v·dt). A small damping factor is applied to reduce drift caused by sensor noise. The resulting X-Y positions are plotted on the canvas, creating a visual trail of the device's movement path. The brighter part of the trail represents the most recent positions, while older points gradually fade. The red arrow at the trail's head indicates the current acceleration direction and magnitude.

Starting with iOS 13, Apple requires websites to explicitly request user permission before accessing motion sensors via the DeviceMotionEvent API. This is a privacy measure, as motion data can potentially be used for fingerprinting or inferring user activity. When using Safari on iOS, you'll see an "Allow Sensor" button—tap it and confirm the system dialog to enable real sensor data. On Android devices and desktop browsers, this permission is typically not required, and sensors work immediately if available. The tool falls back to simulation mode if permission is denied or sensors are unavailable.

Most modern smartphones and tablets support the DeviceMotion API with linear acceleration data. This includes iPhone 6 and newer (iOS 10+), most Android phones running Android 4.4+, and some iPad models. Desktop and laptop computers generally do not have built-in accelerometers, so they rely on the simulation mode. Some high-end laptops with SSDs may include shock sensors, but these are rarely exposed through browser APIs. For the best experience, visit this tool on a mobile device with a recent browser (Safari 13+, Chrome 80+, Firefox 70+, or Edge 80+). HTTPS is required for sensor access.

Trajectory drift occurs because sensor noise and tiny errors accumulate during the double integration process. Even a constant offset of 0.01 m/s² in acceleration can cause the calculated position to drift by several meters over 30 seconds. To mitigate this, the tool applies a damping factor (~0.94 per frame) that gradually reduces velocity, mimicking friction. Additionally, acceleration values below a small threshold (~0.05 m/s²) are zeroed out to filter sensor noise. While these techniques reduce drift, they also mean the trajectory is best suited for visualizing short-term, dynamic movements rather than precise long-term position tracking.

In simulation mode, the tool generates synthetic acceleration data using overlapping sine waves at different frequencies (0.5–3 Hz) with added random noise. This mimics the natural micro-movements of a handheld device. You can also click or tap on the canvas to apply impulse forces—the acceleration vector points toward your click location with a magnitude proportional to the distance from the current position. Simulation mode runs at approximately 60 frames per second using requestAnimationFrame, matching the smoothness of real sensor data. It's ideal for desktop users or for testing the visualization without a physical device.

All acceleration values are displayed in meters per second squared (m/s²), the SI unit for acceleration. For reference, Earth's gravity is approximately 9.81 m/s². The horizontal bar charts use a scale of ±3 m/s² (typical handheld motion range), which represents about 30% of gravity. The trajectory canvas uses a spatial scale where 1 meter ≈ 180 pixels, allowing visualization of movements up to about ±1.2 meters from the origin. The magnitude stat shows the Euclidean norm √(x²+y²+z²) of the current acceleration vector, giving you a single number representing total acceleration intensity.

A standard accelerometer measures total acceleration including gravity—when your phone sits flat on a table, it reads ~9.8 m/s² downward. A gyroscope measures rotational velocity (degrees per second) around each axis. The linear acceleration sensor used here specifically isolates translational motion by removing gravity. This makes it ideal for detecting shakes, pushes, and directional movements. Many fitness trackers and motion analysis apps use linear acceleration for step counting, gesture recognition, and activity classification. The three sensors often work together in sensor fusion systems for more accurate motion tracking.

Yes. All motion data processing happens entirely within your browser using client-side JavaScript. No sensor data is ever sent to any server, recorded, or shared. The trajectory visualization is computed and rendered locally on your device. Once you close the page or click Reset, all stored trajectory points are cleared from memory. Modern browsers enforce HTTPS requirements for sensor APIs, adding a layer of transport security. However, if you're concerned about privacy, you can always use the simulation mode, which generates synthetic data without accessing any physical sensors.

Linear acceleration sensors power many real-world applications: Fitness tracking (step counting, cadence measurement), Gesture recognition (shake-to-undo, flip-to-silence), Gaming (motion-controlled gameplay), Vehicle telematics (hard braking detection, crash sensing), Seismic monitoring (using smartphone networks for earthquake early warning), Rehabilitation (tracking patient movement exercises), and Augmented Reality (stabilizing virtual objects relative to device movement). Understanding linear acceleration is fundamental to building responsive, context-aware mobile applications.