October 27, 2025
MEMS inertial sensors have transformed the way electronic devices interact with the physical world. From stabilizing drones to measuring human motion in a smartwatch, these sensors enable precise detection of acceleration and rotation in space.
Accelerometer and Gyroscope — they can be considered the primary inertial sensors. Their combination forms the foundation of all autonomous navigation, stabilization, and motion-tracking systems.
A MEMS accelerometer measures acceleration, i.e., the change in velocity experienced by a body over a given time interval. This type of sensor relies on a suspended mass within the chip: when the device undergoes acceleration, the mass tends to remain stationary due to inertia, while the frame moves relative to it. This relative displacement is converted into an electrical signal, typically via a capacitance change between movable and fixed electrodes.
The underlying principle is analogous to a spring-mass system, where the force generated by acceleration produces a measurable deformation. At the MEMS scale, this deformation is on the order of a few micrometers, sufficient to generate electrically detectable capacitance variations.
A modern accelerometer consists of one or more flexible mechanical structures, often fabricated on silicon wafers using micromachining techniques. The movable masses are suspended on compliant springs and connected to a series of electrodes that act both as sensing elements and, in feedback systems, as actuators.
To achieve three-axis measurement (X, Y, Z), the chip integrates three orthogonally oriented structures. The collected signals are amplified, digitized, and transmitted to the control system. The design must also account for critical factors such as mechanical resonance, thermal compatibility with electronics, and isolation from external vibrations.
MEMS accelerometer performance is characterized by sensitivity, long-term stability, linearity, and frequency response. The dynamic range depends on the application: consumer devices typically operate within ±2g or ±4g, while automotive or industrial systems can reach ±200g.
A key limitation is mechanical noise and thermal drift, which can introduce errors, particularly at low signal levels. To mitigate these issues, automatic calibration, on-chip thermal compensation, and digital filtering are often employed to remove spurious components.
MEMS accelerometers are widely deployed across numerous products. Beyond measuring tilt and gravity in mobile devices, they are used for predictive maintenance in industrial applications, detecting shocks and vibrations, and in the biomedical sector for monitoring physical activity. In automotive systems, they are critical for airbag deployment and emergency braking systems, while in robotics they provide essential information for balance control and locomotion.
A MEMS gyroscope measures angular velocity, i.e., the rate at which an object rotates around an axis. Its operation is also inertial and relies on the Coriolis effect. Inside the sensor is a vibrating mass, maintained in oscillation by a mechanical actuation system. When the device rotates, the mass oscillates not only along the actuation axis but also along an orthogonal axis due to the Coriolis force acting on moving objects subjected to rotation.
This deflection is detected by sense electrodes that measure the mass’s displacement in the transverse direction. The magnitude of the deflection is proportional to the angular velocity, and the measurement can be obtained using either open-loop or closed-loop techniques, depending on the required precision.
The internal structure of a MEMS gyroscope is more complex than that of an accelerometer due to the need to maintain constant mass vibration. This requires integrating feedback control circuits, often implemented directly on the chip or in a coupled die.
Geometries vary: common designs include tuning forks, which use two masses vibrating in opposite phase to improve external noise rejection, and ring resonators, which provide structural symmetry and enhanced stability.
MEMS gyroscopes are highly sensitive sensors but are also susceptible to drift over time. Bias instability, i.e., the random variation of the zero point, is one of the most challenging errors, especially for long-term navigation applications. Additionally, intrinsic noise from small vibration detection and thermal variations can affect the resonance frequency of the vibrating masses.
To improve performance, advanced filtering, nonlinear compensation models, and, in critical applications, sensor redundancy are employed. Accuracy specifications vary by use: consumer systems typically tolerate drift on the order of 5–10 °/h, whereas aerospace systems require errors below 0.01 °/h.
Gyroscopes are essential wherever real-time orientation changes need to be estimated. They are used in autonomous navigation systems to compensate for temporary GPS loss, in drones for attitude stabilization, and in virtual reality for head motion tracking. Automotive applications include vehicle stabilization, traction control, and rollover prevention. In the medical field, gyroscopes are used for monitoring movement disorders and assisted rehabilitation.
MEMS accelerometers and gyroscopes are the cornerstones of three-dimensional motion measurement. Both rely on solid physical principles and exploit microscopic mechanics to achieve dynamic measurements with levels of precision previously unimaginable in portable devices.
Their true strength lies in complementarity: the accelerometer provides reliable information on linear accelerations and orientation relative to gravity, while the gyroscope measures angular rotations with high responsiveness. However, both have limitations that can lead to cumulative errors or unstable estimates. For this reason, they are often integrated into multi-sensor units, where algorithms optimally fuse the data.
In the future, MEMS inertial sensor development will progress in two main directions: improving absolute performance (noise reduction, long-term stability) and integrating with smart circuits capable of performing complex processing directly on-chip.
