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An accelerometer is a device that measures force due to gravity or a change in speed or direction of travel. This paper describes accelerometers and their application in other disciplines and, by way of an example, explores the utility of accelerometers for studying aggression. We end with a discussion of additional ways accelerometers might be used in group processes research.

We first review the use of accelerometers in other disciplines. We then present the results of four studies that demonstrate the use of accelerometers to measure aggression. Study 1 establishes the measure’s concurrent validity. Study 2 concerns its stability and representative reliability. Study 3 seeks to establish the measure’s predictive validity by associating it with an existing measure. Study 4 demonstrates the ability of accelerometers to address a sociological research question.

In Studies 1 and 2, we find that accelerometers can be used to differentiate between distinct levels of aggression. In Study 3, we find that men’s average peak acceleration correlates with a previously validated measure of aggression. Study 4 uses accelerometers to reproduce a well-established finding in the aggression literature.

We conclude that accelerometers are a flexible tool for group processes’ researchers and social scientists more broadly. Our findings should prove useful to social scientists interested in measuring aggression or in employing accelerometers in their work.

Laboratory calibration methods are time-consuming and require accurate devices to find the error coefficients of the low-cost microelectromechanical system (MEMS) accelerometer. Besides, low-cost MEMS sensors highly depend on temperature because of their silicon property and the effect of temperature on error coefficients should also be considered for compensation. This paper aims to present a field calibration method in which the accelerometer is placed in different positions without any accurate equipment in a few minutes and its temperature is changed by a simple device like a hairdryer.

In this paper, a non-linear cost function is defined based on this rule that the magnitude of the acceleration measured by the accelerometer in static mode is equal to the gravity plus error factors. Also, the dependency of error coefficients of the accelerometer is presented as a second-order polynomial in this cost function. By minimizing the cost function, the accelerometer error coefficients include bias, scale factor and non-orthogonality and their temperature dependency are obtained simultaneously.

Simulation results in MATLAB and empirical results of a MPU6050 accelerometer verify the good performance of the proposed calibration method.

Finding a fast and simple field calibration method to calibrate a low-cost MEMS accelerometer and compensate for the temperature dependency without using accurate laboratory equipment can help a wide range of industries that use advanced and expensive sensors or use expensive laboratory equipment to calibrate their sensors, to decrease their costs.

Worker activity identification and classification is the most crucial and difficult stage in work sampling studies. Manual methods of recording are tedious and prone to error and, hence automating the task of observing and classifying worker activities is an important step towards improving the current practice. Very recently, accelerometer-based systems have been explored to automate activity recognition in construction, but it had been carried out in controlled environment. The purpose of this paper is to cover the evaluation of the system in field situations.

Experimental investigation was carried out on crews of iron workers and carpenters with accelerometer data loggers worn at selected locations on the human body. The accelerometer data collection was spread over a time period of two weeks, and video recording of the worker activities was concurrently carried out to serve as ground truth, the reference used for comparison. The activity recognition analysis was carried out on accelerometer data features using a decision tree algorithm.

It was found that the classification using the individual training scheme performed better when compared with the collective training scheme for both the trades. The field studies results showed that the classification accuracies for iron work and carpentry are 90.07 and 77.74 per cent, respectively, using decision tree classifier. It was found that similarities of movements were a major cause for lower accuracy of recognition.

The work being preliminary in nature has used the basic classifier and pre-processing methods and, standard settings of algorithms.

The paper has investigated accelerometer-based method for construction labour activity classification in field situations.

This paper aims to present an efficient design approach for the micro electromechanical systems (MEMS) accelerometers considering design parameters affecting the long-term reliability of these inertial sensors in comparison to traditional iterative microfabrication and experimental characterization approach.

A dual-axis capacitive MEMS accelerometer design is presented considering the microfabrication process constraints of the foundry process. The performance of the MEMS accelerometer is analyzed through finite element method– based simulations considering main design parameters affecting the long-term reliability. The effect of microfabrication process induced residual stress, operating pressure variations in the range of 10 mTorr to atmospheric pressure, thermal variations in the operating temperature range of −40°C to 100°C and impulsive input acceleration at different input frequency values is presented in detail.

The effect of residual stress is negligible on performance of the MEMS accelerometer due to efficient design of mechanical suspension beams. The effect of operating temperature and pressure variations is negligible on energy loss factor. The thermal strain at high temperature causes the sensing plates to deform out of plane. The input dynamic acceleration range is 34 g at room temperature, which decreases with operating temperature variations. At low frequency input acceleration, the input acts as a quasi-static load, whereas at high frequency, it acts as a dynamic load for the MEMS accelerometer.

In comparison with the traditional MEMS accelerometer design approaches, the proposed design approach focuses on the analysis of critical design parameters that affect the long-term reliability of MEMS accelerometer.

Three-axis accelerometers play a vital role in monitoring the vibrations in aircraft machinery, especially in variable flight temperature environments. The sensitivity of a three-axis accelerometer under different temperature conditions needs to be calibrated before the flight test. Hence, the authors investigated the efficiency and sensitivity calibration of three-axis accelerometers under different conditions. This paper aims to propose the novel calibration algorithm for the three-axis accelerometers or the similar accelerometers.

The authors propose a hybrid genetic algorithm–particle swarm optimisation–back-propagation neural network (GA–PSO–BPNN) algorithm. This method has high global search ability, fast convergence speed and strong non-linear fitting capability; it follows the rules of natural selection and survival of the fittest. The authors describe the experimental setup for the calibration of the three-axis accelerometer using a three-comprehensive electrodynamic vibration test box, which provides different temperatures. Furthermore, to evaluate the performance of the hybrid GA–PSO–BPNN algorithm for sensitivity calibration, the authors performed a detailed comparative experimental analysis of the BPNN, GA–BPNN, PSO–BPNN and GA–PSO–BPNN algorithms under different temperatures (−55, 0 , 25 and 70 °C).

It has been showed that the prediction error of three-axis accelerometer under the hybrid GA–PSO–BPNN algorithm is the least (approximately ±0.1), which proved that the proposed GA–PSO–BPNN algorithm performed well on the sensitivity calibration of the three-axis accelerometer under different temperatures conditions.

The designed GA–PSO–BPNN algorithm with high global search ability, fast convergence speed and strong non-linear fitting capability has been proposed to decrease the sensitivity calibration error of three-axis accelerometer, and the hybrid algorithm could reach the global optimal solution rapidly and accurately.

This paper aims to describe a novel hybrid inertial measurement unit (IMU) for motion capturing via a new configuration of strategically distributed inertial sensors, and a calibration approach for the accelerometer and gyroscope sensors mounted in a flight vehicle motion tracker built on the inertial navigation system.

The hybrid-IMU is designed with five accelerometers and one auxiliary gyroscope instead of the accelerometer and gyroscope triads in the conventional IMU.

Simulation studies for tracking with both attitude angles and translational movement of a flight vehicle are conducted to illustrate the effectiveness of the proposed method.

The cross-quadratic terms of angular velocity are selected to process the direct measurements of angular velocities of body frame and to avoid the integration of angular acceleration vector compared with gyro-free configuration based on only accelerometers. The inertial sensors are selected from the commercial microelectromechanical system devices to realize its low-cost applications.

This paper aims to develop a resonant accelerometer for structure optimization. The dynamic analysis of the resonator for resonant accelerometer are investigated.

First, the working principle and mechanical model of the resonator are introduced. Moreover, dynamic analysis of the resonator is used for the purpose of investigating the dynamic characteristics of the resonant accelerometer. Finally, to verify the feasibility of the proposed dynamic analysis method, resonant accelerometer 1g static tumbling experiments of resonant accelerometer are built.

It can be seen from the natural frequency and the resonator mode that only when the resonator root stiffness is much greater than the resonant beam stiffness, there will be appear corresponding interference mode, therefore,the resonator root stiffness is avoid too large in design. The stability analysis result of resonant beam under axial force show that the resonant beam parameters should be maintained a constant. At the same time, it is concluded from the vibration mode analysis for resonant beam that the influence of the beam thickness and beam errors on the first and second order modes is great. On the other hand, it is concluded from the test result that the designed resonant accelerometer sensitivity is 98 Hz/g, which shows that the dynamic analysis method is feasible.

The research may be significant in the field of resonant sensors, supporting a variety of practical applications such as phone and game.

This paper seeks to establish a foundation for designing and optimizing resonant accelerometer structure. To this end, the dynamic analytical method of the resonator for resonant accelerometer was discussed. The results of this research have proved that the dynamic analysis based on a resonator is an effective approach and instructional in practical resonant sensor design.

This paper aims to focus on the numerical modelling of 3D structure of surface micromachined (MEMS) accelerometers.

The paper focuses on the methods of mechanical design and analysis of electrostatic accelerometers (comb drive structure) and uses computer simulation procedure leading to final structure design, then to be defined as a basic structure for stress analysis.

The strategy in computer modeling of accelerometer MEMS is satisfactory in order to simulate the electromechanical characteristics of different accelerometer structures (IMEMS).

A novel complex strategy in computer modeling of accelerometer MEMS, based on solid modeling is proposed.

This paper aims to provide detailed information on the dynamic model and closed‐loop control theory for a resonant accelerometer based on electrostatic stiffness, which is important for the design of this type of resonant accelerometer.

After analysing the principles of the resonant accelerometer based on electrostatic stiffness, a dynamic model was built. According to the requirements of the closed‐loop control, the control equations based on phase‐locked technology were also built for the system. With the help of the averaging method, the system behaviour was analysed, and the equilibrium for the vibration amplitude was achieved.

The theoretical analysis and simulation show that integral gain is critical to system stability. When it is larger than the critical point, the system stable time is shorter, but the frequency‐tracking process fluctuates; if it is smaller than the critical point, the system stable time is longer, and the frequency‐tracking process stabilizes a resonant accelerometer was fabricated with a bulk‐silicon‐dissolved process. With the above conclusions, the accelerometer was driven and tested with a sensitivity of 47 Hz/g for a single vibration beam.

The dynamic model and the control theory for the resonant accelerometer based on electrostatic stiffness were presented in this paper. The simulation and experiment results agree well with the theoretical analysis.

The purpose of this paper is to provide an improved structural design for accelerometers based on cantilever beam‐mass structure and offer the descriptions of sensor fabrication, packaging and experiments.

The cantilever beam‐membrane (CB‐membrane) structure is designed as the sensing element for piezoresistive accelerometers. In the CB‐membrane structure, a cantilever beam and two identical membranes as a whole part supports the proof mass. Four piezoresistors are distributed on the surface of the cantilever beam to form a Wheatstone bridge. Finite element method is used to carry out the structural analysis and determine the sensor dimensions. The sensor chip is fabricated by bulk micro‐machining technique, packaged in dual‐in‐line (DIP) way and tested.

Compared with the conventional cantilever beam‐mass (CB‐mass) structure, the CB‐membrane structure can improve the sensor's performances, including response frequency, output linearity and cross‐axis sensitivity. The results of simulation and experiments prove that the CB‐membrane accelerometer has good performances.

The accelerometer is simply packaged and the zero offset voltage has not been compensated. Moreover, the measured response frequency is lower than the simulated value. Further work and study are needed to solve these problems.

The accelerometer with CB‐membrane structure has good performances as the static and dynamic experiments show and is suitable to detect the spindle vibration of the machine tools.