Microelectromechanical Systems Research Articles

Self-adjusting voxelated electrochemical three-dimensional printing of metallic microstructures

Abstract Microscale metallic structures enhanced by additive manufacturing technology have attracted extensive attention especially in microelectronics and electromechanical devices. Meniscus-confined electrodeposition (MCED) advances microscale 3D metal printing, enabling simpler fabrication of superior metallic microstructures in air without complex equipment or post-processing. However, accurately predicting growth rates with current MCED techniques remain challenging, which is essential for precise structure fabrication and preventing nozzle clogging. In this work, we present a novel approach to electrochemical 3D printing that utilizes a self-adjusting, voxelated method for fabricating metallic microstructures. Diverging from conventional voxelated printing which focuses on monitoring voxel thickness for structure control, this technique adopts a holistic strategy. It ensures each voxel’s position is in alignment with the final structure by synchronizing the micropipette’s trajectory during deposition with the intended design, thus facilitating self-regulation of voxel position and reducing errors associated with environmental fluctuations in deposition parameters. The method’s ability to print micropillars with various tilt angles, high density, and helical arrays demonstrates its refined control over the deposition process. Transmission electron microscopy analysis reveals that the deposited structures, which are fabricated through layer-by-layer (voxel) printing, contain nanotwins that are widely known to enhance the material’s mechanical and electrical properties. Correspondingly, in situ scanning electron microscopy (SEM) microcompression tests confirm this enhancement, showing these structures exhibit a compressive yield strength exceeding 1 GPa. The indentation tests provided an average hardness of 3.71 GPa, which is the highest value reported in previous work using MCED. The resistivity measured by the four-point probe method was (1.95 ± 0.01) × 10−7 Ω·m, nearly 11 times that of bulk copper. These findings demonstrate the considerable advantage of this technique in fabricating complex metallic microstructures with enhanced mechanical properties, making it suitable for advanced applications in microsensors, microelectronics, and micro-electromechanical systems.

Research on Adhesion Pull-Off Behavior of Rigid Flat Punch and Viscoelastic Substrate

Interfacial adhesion is one of the key factors affecting the reliability of micro–nano systems. The adhesion contact mechanism is still unclear as the time-dependent viscoelasticity of soft materials. To clarify the adhesion interaction, the pull-off detachment between the rigid flat punch and viscoelastic substrate is explored considering the viscoelasticity of soft materials and rate-dependent adhesion. Taking the Lennard-Jones (L-J) potential characterizing interfacial adhesion and the Prony series defining the viscoelasticity of materials as references, the bilinear cohesion zone model (CZM) and standard Maxwell model are employed, and an adhesion analysis framework is established by combining finite element technology. The influence laws of the loading and unloading rates, material relaxation coefficients and size effect on adhesion pull-off behavior are revealed. The results show that the pull-off force is independent of the material relaxation effect and related to the unloading rate. When v^ ≥ 50 or v^ < 0.01, the pull-off force has nothing to do with the unloading rate, but when 0.01 < v^ < 50, the pull-off force increases with the increasing unloading rate. Also, it is controlled by the size effect, and the changing trend conforms to the MD-n model proposed by Jiang. The energy required for interfacial separation (i.e., effective adhesion work) is a result of the comprehensive influence of unloading rates, material properties and the relaxation effect, which is consistent with Papangelo1’s research results. In addition, we derive the critical contact radius of the transition from the Kendall solution to the strength control solution. This work not only provides a detailed solution for the interfacial adhesion behavior but also provides guidance for the application of adhesion in Micro-Electro-Mechanical Systems (MEMSs).

Research on hydroacoustic signal processing algorithm based on B-spline and Hilbert transform

Purpose This paper aims to solve the problems of baseline drift, susceptibility to abnormal data interference during baseline drift processing, and phase inconsistency in underwater acoustic target detection and signal processing of single microelectromechanical systems (MEMS) vector hydrophone. To this end, this paper proposes a baseline drift removal algorithm based on Huber regression model with B-spline interpolation (H-BS) and a phase compensation algorithm based on the Hilbert transform. Design/methodology/approach First, the Huber regression model is innovatively introduced into the conventional B-spline interpolation (B-spline) to solve the control point vectors more accurately and to improve the anti-interference ability of the abnormal data when the B-spline interpolation fitting removes baseline drift and the baseline drift components in the signals are fitted accurately and removed by the above method. Next, the Hilbert transform is applied to the three-channel output signals of the MEMS vector hydrophone to calculate the instantaneous phase and the phase compensation is performed on the vector X/Y signals with the scalar P signal as the reference. Findings Through simulation experiments, it is found that H-BS proposed in this paper has smaller processing error and better robustness than variational modal decomposition and B-spline, but the H-BS algorithm takes slightly longer than the B-spline. In the actual lake test experiments, the H-BS algorithm can effectively remove the baseline drift component in the original signal and restore the signal waveform, and after the Hilbert transform phase compensation, the direction of arrival estimation accuracy of the signal is improved by 1°∼2°, which realizes high-precision orientation to the acoustic source target. Originality/value In this paper, the Huber regression model is introduced into B-spline interpolation fitting for the first time and applied in the specialized field of hydroacoustic signal baseline drift removal. Meanwhile, the Hilbert transform is applied to phase compensation of hydroacoustic signals. After simulation and practical experiments, these two methods are verified to be effective in processing hydroacoustic signals and perform better than similar methods. This study provides a new research direction for the signal processing of MEMS vector hydrophone, which has important practical engineering application value.

Machine Learning-Enhanced Fabrication of Three-Dimensional Co-Pt Microstructures via Localized Electrochemical Deposition

This paper presents a novel method for fabricating three-dimensional (3D) microstructures of cobalt–platinum (Co-Pt) permanent magnets using a localized electrochemical deposition (LECD) technique. The method involves the use of an electrolyte and a micro-nozzle to control the deposition process. However, traditional methods face significant challenges in controlling the thickness and uniformity of deposition layers, particularly in the manufacturing of magnetic materials. To address these challenges, this paper proposes a method that integrates machine learning algorithms to optimize the electrochemical deposition parameters, achieving a Co:Pt atomic ratio of 50:50. This optimized ratio is crucial for enhancing the material’s magnetic properties. The Co-Pt microstructures fabricated exhibit high coercivity and remanence magnetization comparable to those of bulk Co-Pt magnets. Our machine learning framework provides a robust approach for optimizing complex material synthesis processes, enhancing control over deposition conditions, and achieving superior material properties. This method opens up new possibilities for the fabrication of 3D microstructures with complex shapes and structures, which could be useful in a variety of applications, including micro-electromechanical systems (MEMSs), micro-robots, and data storage devices.

Evaluation of a novel forward-looking optical coherence tomography probe for endoscopic applications: an ex vivo feasibility study.

As a result of recent advances in the development of small microelectromechanical system mirrors, a novel forward-looking optical coherence tomography (OCT) probe with a uniquely large field of view is being commercially developed. The aim of this study is to prospectively assess the feasibility of this advanced OCT probe in interpreting ex vivo images of colorectal polyp tissue and to identify necessary steps for further development. A total of 13 colorectal lesions from 9 patients, removed during endoscopic resection, were imaged ex vivo with the OCT device and compared with histopathological images that served as the gold standard for diagnostics. Normal tissue from one patient, removed during the endoscopic procedure, was imaged as a negative control. We assessed the presence of features indicative for polyp type and degree of dysplasia, by comparing OCT images to histopathological images and by evaluating the presence of OCT-specific features identified by previous studies, such as effacement (loss of layered tissue structure), a hyperreflective epithelial layer, and irregularity of the surface. As verified by corresponding histological images, tissue structures such as blood vessels and tissue layers could be distinguished in OCT images of the normal tissue sample. Detailed structures on histological images such as crypts and cell nuclei could not be identified in the OCT images. However, we did identify OCT features specific for colorectal lesions, such as effacement and a hyperreflective epithelial layer. In general, the imaging depth was about 1mm. Some relevant tissue structures could be observed in OCT images of the novel device. However, some adaptations, such as increasing imaging depth using a laser with a longer central wavelength, are required to improve its clinical value for the imaging of colorectal lesions.

A Review on Resonant MEMS Electric Field Sensors

Electric field sensors (EFSs) are widely used in various fields, particularly in accurately assessing atmospheric electric fields and high-voltage power lines. Precisely detecting electric fields enhances the accuracy of weather forecasting and contributes to the safe operation of power grids. This paper comprehensively reviews the development of micro-electromechanical system (MEMS) resonant EFSs, including theoretical analysis, working principles, and applications. MEMS resonant EFSs have developed into various structures over the past decades. They have been reported to measure electric field strength by detecting changes in the induced charge on the electrodes. Significant advancements include diverse driving and sensing structures, along with improved dynamic range, sensitivity, and resolution. Recently, mode localization has gained attention and has been applied to electric field sensing. This paper reviews the performances and structures of MEMS resonant EFSs over recent decades and highlights recent advances in weakly coupled resonant EFSs, offering comprehensive guidance for researchers.

Tensile Strength Property with PdCo-Cu Multi-Layer Lamination and Heat Treatment of MEMS Probe for Probe Card

Cantilever wire probe card has limited to transport high-speed signal because of long wire but it is suitable for inspecting high-current and high voltage semiconductor such as wide band gap (WBG) power semiconductors.Superior mechanical property of a probe card wire is in demand because it is respectively used wafer inspection with in and out pad on the top surface of the power semiconductor wafer. Therefore, in this study, tensile specimens of micro electro-mechanical systems (MEMS) probe alternatively layered and electroplated with palladium (Pd)-cobalt (Co) alloy layers and copper (Cu) layers. MEMS probe was also measured tensile strength and elongation with multi-lamination and heat treatment conditions. Additionally, fractography of fracture surface after tensile test were analyzed using a scanning electron microscope (SEM). As the number of PdCo-Cu multi-layer increased, 11, 15 and 21 layered specimens showed higher tensile strength and longer elongation than 5 layered specimens because of the increase of laminated interface of PdCo and Cu. 7 layered specimen after isothermal aging had higher tensile strength and longer elongation than before isothermal aging. In 5, 11, 15 and 21 layered specimens, the fracture surfaces of tensile test specimens without aging treatment showed a ductile-brittle mixed fracture mode. Fracture surfaces of 7-layered specimen before and after isothermal aging showed a ductile-brittle mixed fracture mode.

MEMS and ECM Sensor Technologies for Cardiorespiratory Sound Monitoring—A Comprehensive Review

This paper presents a comprehensive review of cardiorespiratory auscultation sensing devices (i.e., stethoscopes), which is useful for understanding the theoretical aspects and practical design notes. In this paper, we first introduce the acoustic properties of the heart and lungs, as well as a brief history of stethoscope evolution. Then, we discuss the basic concept of electret condenser microphones (ECMs) and a stethoscope based on them. Then, we discuss the microelectromechanical systems (MEMSs) technology, particularly focusing on piezoelectric transducer sensors. This paper comprehensively reviews sensing technologies for cardiorespiratory auscultation, emphasizing MEMS-based wearable designs in the past decade. To our knowledge, this is the first paper to summarize ECM and MEMS applications for heart and lung sound analysis.

Application of active piezoresistive cantilevers in high-eigenmode surface imaging

Abstract One of the most important limitations of the atomic force microscopy (AFM) is scanning speed, whose high values are required for contemporary high-resolution, long-range diagnostic applications. The measurement bandwidth of an AFM depends on several factors, but usually results from the time constant of the oscillating cantilever, which is correlated with its resonance frequency and quality factor. We propose a method to overcome this problem by performing the surface measurements when the cantilever is vibrating in higher eigenmodes. In this paper we demonstrate the application of active piezoresistive cantilevers operating in this mode. The active piezoresistive cantilever comprises a piezoresistive deflection sensor, a deflection actuator and a nanotip. It is a complete micro-electro-mechanical system (MEMS), ensuring the highest reliability of cantilever vibration control and detection. Higher eigenmode operations are usually difficult to implement as they usually result in lower deflection and lower sensitivity of the probe vibration deflection. Here we present an experimental modification of the structure of an active piezoresistive cantilever using focused ion beam (FIB) machining that mitigates both weaknesses. This has enabled the cantilever to scan the surface at a scanning rate of 10 lines/s with a maximum speed of 500 μm/s and a data acquisition rate of 10 kS/s, when the probe is vibrating at 380 kHz in the second eigenmode. We also describe a traceable calibration routine (based on analysis of the response of the piezoresistive detector, the output of the HeNe interferometer and precise control of the deflection actuator), together with the cantilever modification process and the development of the measurement setup. We show measurement results of dedicated calibration samples and silicon carbide crystal lattice references.

DEVELOPMENT OF RS-WZ3 SENSOR IN IOT BASED VIBRATION MONITORING SYSTEM

This article develops a vibration monitoring system on the machine using the RS-WZ3 sensor, which is based on MEMS (Micro-Electro-Mechanical Systems) technology. The RS-WZ3 sensor can measure vibrations on three axes (X, Y, and Z), as well as the surface temperature of the motor. The MAX485 module and the ESP32 microcontroller transform the vibration data from the sensor into a digital signal, subsequently displaying it on a web interface accessible remotely in real time. Sensor calibration is carried out by comparing the measurement results of the RS-WZ3 sensor with those of the GM63A vibration meter, which shows good accuracy with an average error of 2.01%. Testing of this system shows that the RS-WZ3 sensor is effective in measuring and monitoring machine vibrations in real time, enabling more efficient predictive maintenance and reducing maintenance costs.

Machine learning-driven discovery of high-performance MEMS disk resonator gyroscope structural topologies

The design of the microelectromechanical system (MEMS) disc resonator gyroscope (DRG) structural topology is crucial for its physical properties and performance. However, creating novel high-performance MEMS DRGs has long been viewed as a formidable challenge owing to their enormous design space, the complexity of microscale physical effects, and time-consuming finite element analysis (FEA). Here, we introduce a new machine learning-driven approach to discover high-performance DRG topologies. We represent the DRG topology as pixelated binary matrices and formulate the design task as a path-planning problem. This path-planning problem is solved via deep reinforcement learning (DRL). In addition, we develop a convolutional neural network-based surrogate model to replace the expensive FEA to provide reward signals for DRL training. Benefiting from the computational efficiency of neural networks, our approach achieves a significant acceleration ratio of 4.03 × 105 compared with FEA, reducing each DRL training run to only 426.5 s. Through 8000 training runs, we discovered 7120 novel structural topologies that achieve navigation-grade precision. Many of these surpass traditional designs in performance by several orders of magnitude, revealing innovative solutions previously unconceived by humans.

MEMS capacitive pressure sensor: analysis, theoretical modeling, simulation and performance comparison of the effect of a conical notch

Abstract Micro-Electro-Mechanical Systems (MEMS) pressure sensors are widely used in various applications due to their high sensitivity, low power consumption, and compactness. This work involves the design and simulation of a MEMS-based Touch Mode Capacitive Pressure Sensor (TMCPS). The proposed sensor is based on a substrate with an integrated conical notch featuring a circular diaphragm, aiming to enhance the key performance parameters of the sensor. The integration of a conical notch in the substrate increases the touch area between the diaphragm and substrate compared to the literature, ensuring increased capacitance and capacitive sensitivity. In this work the mathematical analysis of deflection of a circular diaphragm employing thin plate theory, capacitance, and capacitive sensitivity, along with step-by-step explanations, is provided. The results are obtained from MATLAB simulations. The deflection of the diaphragm is validated through Finite Element Analysis (FEA) using COMSOL Multiphysics. The proposed work demonstrates a significant improvement in sensor sensitivity compared to the existing literature.

Aspect Ratio-Dependent Etching in Silicon using XeF2: Experimental Investigation and Comparative Analysis with Dry Etching Methods

Abstract Silicon machining plays a crucial role in shaping three-dimensional structures for Micro-Electro-Mechanical Systems (MEMS) applications. This study investigates Aspect Ratio Dependent Etching (ARDE) across various silicon etching processes, with a particular focus on Xenon Difluoride (XeF2) etching, in comparison to Reactive Ion Etching (RIE) and Deep Reactive Ion Etching (DRIE).By exploring different etching parameters, the study highlights the presence of ARDE in both plasma and non-plasma etching processes. Additionally, it is demonstrated that ARDE can be modeled by a saturating exponential function through experimental adjustment of parameters, enabling the prediction of etching profiles.

A Drosophila-inspired intelligent olfactory biomimetic sensing system for gas recognition in complex environments

The olfactory sensory system of Drosophila has several advantages, including low power consumption, high rapidity and high accuracy. Here, we present a biomimetic intelligent olfactory sensing system based on the integration of an 18-channel microelectromechanical system (MEMS) sensor array (16 gas sensors, 1 humidity sensor and 1 temperature sensor), a complementary metal‒oxide‒semiconductor (CMOS) circuit and an olfactory lightweight machine-learning algorithm inspired by Drosophila. This system is an artificial version of the biological olfactory perception system with the capabilities of environmental sensing, multi-signal processing, and odor recognition. The olfactory data are processed and reconstructed by the combination of a shallow neural network and a residual neural network, with the aim to determine the noxious gas information in challenging environments such as high humidity scenarios and partially damaged sensor units. As a result, our electronic olfactory sensing system is capable of achieving comprehensive gas recognition by qualitatively identifying 7 types of gases with an accuracy of 98.5%, reducing the number of parameters and the difficulty of calculation, and quantitatively predicting each gas of 3–5 concentration gradients with an accuracy of 93.2%; thus, these results show superiority of our system in supporting alarm systems in emergency rescue scenarios.

Cantilever configurations in vibration-based piezoelectric energy harvesting: A comprehensive review on beam shapes and multi-beam formations.

Abstract Vibration-based energy harvesting technology is a well-established research area that has attracted tremendous interest over the last decade. This interest is primarily owing to its extension into a wide range of engineering domains, particularly in Microelectromechanical Systems (MEMS). The cantilever beam is the most common and widely used model for vibration-based energy harvester, driven by two key factors: a) simplicity in design, and b) high output power density. Numerous studies over the years have focused on optimizing the cantilever beam design to increase output power capacity and/or widen the frequency bandwidth of the harvester. While researchers have proposed a plethora of cantilever beam configurations for specific purposes (e.g., low-frequency harvesting, multi-directional frequency harvesting, etc.), there is a notable lack of detailed literature on the types and configurations of cantilever beams. This gap hinders researchers from gaining a comprehensive understanding of the cantilever beams already introduced. Following the need, in this article a comprehensive review is made to list the types of cantilever beams proposed by the researchers over the years. This review covers the working principles of piezoelectric energy harvesting, analyses existing solutions geared towards increasing power output and widening working frequency, and discusses diverse configurations including single and multiple beam setups. The listed beams are categorized based on their structural shape and organization such that it can be helpful for a reader to anticipate which cantilever beam design can be suitable for a specific need. Power output capacity and operating frequency for every beam design are also presented in a tabular form, under each beam category. This would enable the researchers to tailor their designs for specific applications, enhance material efficiency, drive innovation, and open new application possibilities.

Theoretical insights into the ultrahigh piezoelectric performance of (BiFeO3)n/(BaTiO3)n (n = 1–5) superlattices

Perovskite structures have attracted extensive attention in microelectromechanical systems and nanoelectromechanical systems devices due to the high piezoelectric response and the low dielectric constant. The piezoelectric and dielectric properties of the tetragonal BiFeO3/BaTiO3 superlattices grown along the c-axis direction are investigated using density functional theory (DFT) and density functional perturbation theory. The calculated results demonstrate that the (BiFeO3)n/(BaTiO3)n (n = 1–5) superlattices exhibit a profoundly increased piezoelectric response compared to their bulk structures. The (BiFeO3)2/(BaTiO3)2 possesses the highest piezoelectric d33 of 697 pC/N among known lead-free perovskite systems. Furthermore, the (BiFeO3)2/(BaTiO3)2 superlattice possesses a low dielectric ɛ33, and its d33 at 2% tensile strain is 16 times larger than that of an unstrained equilibrium structure. This demonstrates that biaxial tensile strain significantly enhances the piezoelectric response. Combining the special quasirandom structure method with DFT, the structures of a 0.5BiFeO3–0.5BaTiO3 solid solution are predicted, and its calculated d33 is 58 pC/N, which is much smaller than that of a (BiFeO3)2/(BaTiO3)2 superlattice. The results suggest that the (BiFeO3)2/(BaTiO3)2 superlattice might be a potential candidate for nonvolatile random access memory, transducers and actuators, and nanoscale electronic devices.

New design of operational MEMS bridges for measurements of properties of FEBID-based nanostructures.

Focused electron beam-induced deposition (FEBID) is a novel technique for the development of multimaterial nanostructures. More importantly, it is applicable to the fabrication of free-standing nanostructures. Experimenting at the nanoscale requires instruments with sufficient resolution and sensitivity to measure various properties of nanostructures. Such measurements (regardless of the nature of the quantities being measured) are particularly problematic in the case of free-standing nanostructures, whose properties must be separated from the measurement system to avoid possible interference. In this paper, we propose novel devices, namely operational micro-electromechanical system (opMEMS) bridges. These are 3D substrates with nanometer-scale actuation capability and equipped with electrical contacts characterised by leakage resistances above 100 GΩ, which provide a platform for comprehensive measurements of properties (i.e., resistance) of free-standing FEBID structures. We also present a use case scenario in which an opMEMS bridge is used to measure the resistance of a free-standing FEBID nanostructure.

Simulation and Investigation of Si-Based Piezoelectric Micromachined Ultrasonic Transducer (PMUT) Performances

Micro-electromechanical system (MEMS) based piezoelectric ultrasonic transducers for acoustic imaging of the surroundings are known as piezoelectric micromachined ultrasonic transducers (PMUTs). This research proposes a structural design of the PMUT with four fixed-guided beams. The beam is subjected to lateral loads, with vectors that are perpendicular to the longitudinal axis. This project simulated Piezoelectric Micromachined Ultrasonic Transducer (PMUT) with three different material properties i.e. Aluminium Nitride (AlN), Lead zirconate titanate (PZT) and Zinc Oxide (ZnO). Based on the study, it was found that reducing the beam dimensions and increasing the plate size will result in the first mode frequency reduction from 1.33x107 Hz to 3.74x106 Hz. Other than that, it was found that AlN PMUT experienced the maximum deflection of 6.3413 to 6.3478 μm when the loads applied in the range of 50 to 200 μN/m2. When the piezoelectric material changed to PZT, we obtained the maximum deflections of 0.3771 to 0.3786 μm when the same loads range applied to the PMUT. As for the ZnO PMUT, the maximum deflections obtained were in between 0.1702 μm to 0.1772 μm with the loads are maintained as in the loads applied to the AlN and PZT. This study proved the significant impact of altering the structural dimensions and material properties of PMUTs on their operational characteristics, specifically the first mode frequency and deflection behavior.

Review on Next-Gen Healthcare: The Role of MEMS and Nanomaterials in Enhancing Diagnostic and Therapeutic Outcomes

The convergence of microelectromechanical systems (MEMS) and nanomaterials is transforming healthcare by enabling breakthroughs in diagnostics, drug delivery, and biosensing. This synergistic integration offers unprecedented precision, miniaturization, and biocompatibility, overcoming critical challenges in detecting disease markers and delivering therapies. MEMS-based devices, when combined with nanomaterials, achieve heightened sensitivity and specificity, allowing for early diagnosis and targeted treatments across various medical applications. From cancer detection to neurotransmitter monitoring for mental health management, this fusion holds immense potential in advancing personalized medicine. As research in this domain continues to evolve, MEMS-nanomaterial technologies are poised to significantly enhance healthcare outcomes by improving diagnostic accuracy, treatment efficacy, and patient well-being. This review discusses recent advances, key challenges, and future perspectives on the role of MEMS and nanotechnology in shaping the future of healthcare innovation.

Use of a Microelectromechanical Systems Sensor for Objective Measurements of Abnormal Head Posture in Congenital Superior Oblique Palsy Patients.

The purpose of this study was to design an objective method for measurement of head positions as achieved with use of a microelectromechanical systems (MEMS) sensor. In addition, to use this system to observe the abnormal head position (AHP) in patients with congenital superior oblique palsy (SOP) before and after their surgery. An MEMS sensor was designed for recording of the pitch, roll, and yaw values of the head position in real time. The MEMS sensor was then fixed on the synoptophore from -30 degrees to +30 degrees positions horizontally and vertically to test the accuracy of these measurements. Then, we tested 13 participants with AHP using the MEMS method and the photographic method and compared their correlations. Finally, the pitch, roll, and yaw values of head positions were measured using this MEMS sensor in 31 patients with congenital SOP as performed before and after their surgery. The MEMS sensor (LPMS-B2; Alubi, Guangzhou, China; 400 hertz [Hz]), as based on the theory of a gyroscope, was designed and connected to a smartphone via Bluetooth. It was able to conveniently record the patient's pitch, roll, and yaw head positions in real time, recordings which were consistent with the scales of the synoptophore (P > 0.05) and good correlations with the photographic method (P < 0.001). The main preoperative AHP in patients with SOP was roll (22/31, 71%). Pre- and postoperative vertical deviations were 16.4 ± 7.3 prism diopters (PD) and 4.1 ± 4.2 PD, respectively (P = 0.001). The AHP in patients with SOP was positively correlated with the angle of extorsion in the dominant eye (P = 0.01), rather than that of the vertical deviation. The MEMS sensor described in this report is a simple, practical, and accurate objective device for use in head position measurements. In patients with SOP, the AHP is related to the angle of extorsion in the dominant eye. The MEMS sensor was designed as a micro-wireless dynamic high-precision device for AHP measurement, which has the potential for use in a clinic.