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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.

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.

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 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.

The paper aims to present numerical modeling and technology of a very first three axial low temperature cofired ceramics (LTCC) accelerometer.

Low temperature cofired ceramics technology was applied in the fabrication process of the novel device. The numerical modeling was used to predict the properties of the accelerometer, moreover, design of the experiment methodology was used to reduce time of simulation and to get as much as information from the experiment as possible.

The low temperature cofired ceramics make it possible to fabricate three axial accelerometer.

The presented device is just a first prototype. Therefore, further research work will be needed to improve structural drawbacks and to analyze precisely the device reliability and parameters repeatability.

The device presented in the paper can be applied in systems working in a harsh environment (high temperature and humidity). Ceramic sensors can withstand temperatures up to 600°C.

This paper presents novel three axial LTCC accelerometer.

Technological capabilities of manufacturing microelectromechanical system (MEMS) gyroscopes are still insufficient if compared to manufacturing high-efficient gyroscopes and accelerometers. This creates weaknesses in their mechanical structure and restrictions in the measurement accuracy, stability and reliability of MEMS gyroscopes and accelerometers. This paper aims to develop a new architectural solutions for optimization of MEMS gyroscopes and accelerometers and propose a multi-axis MEMS inertial module combining the functions of gyroscope and accelerometer.

The finite element modeling (FEM) and the modal analysis in FEM are used for sensing, drive and control electrode capacitances of the multi-axis MEMS inertial module with the proposed new architecture. The description is given to its step-by-step process of manufacturing. Algorithms are developed to detect its angular rates and linear acceleration along three Cartesian axes.

Experimental results are obtained for eigenfrequencies and capacitances of sensing, drive and control electrodes for 50 manufactured prototypes of the silicon electromechanical sensor (SES). For 42 SES prototypes, a good match is observed between the calculated and simulated capacitance values of comb electrodes. Thus, the mean-square deviation is not over 20 per cent. The maximum difference between the calculated and simulated eigenfrequencies in the drive channel of 11 SES prototypes is not over 3 per cent. The same difference is detected for eigenfrequencies in the first sensing channel of 17 SES prototypes.

This study shows a way to design and optimize the structure and theoretical background for the development of the MEMS inertial module combining the functions of gyroscope and accelerometer. The obtained results will improve and expand the manufacturing technology of MEMS gyroscopes and accelerometers.

This paper aims to propose a gesture recognition method at an early stage. An accelerometer is installed in most current mobile phones, such as iPhones, Android-powered devices and video game controllers for the Wii or PS3, which enables easy and intuitive operations. Therefore, many gesture-based user interfaces that use accelerometers are expected to appear in the future. Gesture recognition systems with an accelerometer generally have to construct models with user’s gesture data before use and recognize unknown gestures by comparing them with the models. Because the recognition process generally starts after the gesture has finished, the output of the recognition result and feedback delay, which may cause users to retry gestures, degrades the interface usability.

The simplest way to achieve early recognition is to start it at a fixed time after a gesture starts. However, the degree of accuracy would decrease if a gesture in an early stage was similar to the others. Moreover, the timing of a recognition has to be capped by the length of the shortest gesture, which may be too early for longer gestures. On the other hand, retreated recognition timing will exceed the length of the shorter gestures. In addition, a proper length of training data has to be found, as the full length of training data does not fit the input data until halfway. To recognize gestures in an early stage, proper recognition timing and a proper length of training data have to be decided. This paper proposes a gesture recognition method used in the early stages that sequentially calculates the distance between the input and training data. The proposed method outputs the recognition result when one candidate has a stronger likelihood of recognition than the other candidates so that similar incorrect gestures are not output.

The proposed method was experimentally evaluated on 27 kinds of gestures and it was confirmed that the recognition process finished 1,000 msec before the end of the gestures on average without deteriorating the level of accuracy. Gestures were recognized in an early stage of motion, which would lead to an improvement in the interface usability and a reduction in the number of incorrect operations such as retried gestures. Moreover, a gesture-based photo viewer was implemented as a useful application of our proposed method, the proposed early gesture recognition system was used in a live unscripted performance and its effectiveness is ensured.

Gesture recognition methods with accelerometers generally learn a given user’s gesture data before using the system, then recognizes any unknown gestures by comparing them with the training data. The recognition process starts after a gesture has finished, and therefore, any interaction or feedback depending on the recognition result is delayed. For example, an image on a smartphone screen rotates a few seconds after the device has been tilted, which may cause the user to retry tilting the smartphone even if the first one was correctly recognized. Although many studies on gesture recognition using accelerometers have been done, to the best of the authors’ knowledge, none of these studies has taken the potential delays in output into consideration.