Particle Tracking of Microelectromechanical System Performance and Reliability

Copeland, Craig R.; McGray, Craig D.; Geist, Jon; Stavis, Samuel M.

doi:10.1109/jmems.2018.2874771

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…Copeland et al propose a recognition method to extract the information features of MEMS inertial sensor data, that is, to recognize gestures by extracting the feature quantities and variation laws of acceleration and angular velocity. This method cannot recognize gestures related to time sequence, and there are some limitations in the recognition of complex gestures [ 7 ]. Tu et al improve the feature extraction method and added time series to recognize gestures related to time sequence.…”

Section: Literature Reviewmentioning

confidence: 99%

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

Zhou

2022

Applied Bionics and Biomechanics

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In order to track the limb movement trajectory of gymnasts, a method based on MEMS inertial sensor is proposed. The system mainly collects the acceleration and angular velocity data of 11 positions during gymnastics by constructing sensor network. Based on the two kinds of preprocessed data, the parameters such as sample mean, standard deviation, information entropy, and mean square error are calculated as classification features, the support vector machine (SVM) classification model is established, and the movements of six kinds of gymnastics are effectively recognized. The experimental results show that when the human body is doing gymnastics, the measured three-axis acceleration values are between -0.5 g~2.2 g, -1 g~2.8 g, and -1.8 g~1 g, respectively, and the static error range accounts for only 1.6%~2% of the actual measured data range. Therefore, it is considered that such static error has little effect on the accuracy of data feature extraction and action recognition, which can be ignored. It is proved that MEMS inertial sensor can effectively track the movement trajectory of gymnasts’ limbs.

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Section: Literature Reviewmentioning

confidence: 99%

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

Zhou

2022

Applied Bionics and Biomechanics

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“…We consider two that bracket the range of experimental complexity, and we introduce a second new concept of tracking multiple emitters as indicators of the six degrees of freedom of microscale bodies. Our two new concepts are synergistic, as multiple emitters improve tracking precision by rigid transformations that combine information through the central limit theorem [9][10][11][12] , while the rigidity and planarity of a microscale body enable rigorous tests of tracking accuracy. Toward the simple end of the application range, the deposition of fluorescent particles on an imaging substrate -a microscale body that is ubiquitous in localization microscopy -allows calibration of aberration effects 5,6,13,14 and correction of instrument drift [15][16][17] .…”

Section: Introductionmentioning

confidence: 99%

“…This essential function of machines has diverse applications to optical traps 21 , colloidal motors 22 , tunable photonics 23,24 , reconfigurable metadevices 25 , materials characterization 26,27 , and even safety switches of extreme consequence 28 . The latter application motivated the development of our test system, which is exemplary of microsystem technologies that integrate multiple parts, are nominally planar, and benefit from tracking in two dimensions and three degrees of freedom to elucidate their motion 9,11,12,29,30 . However, measurements in three dimensions 31 and six degrees of freedom are much more informative, as we show in this study.…”

Section: Introductionmentioning

confidence: 99%

Accurate localization microscopy by intrinsic aberration calibration

et al. 2021

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A standard paradigm of localization microscopy involves extension from two to three dimensions by engineering information into emitter images, and approximation of errors resulting from the field dependence of optical aberrations. We invert this standard paradigm, introducing the concept of fully exploiting the latent information of intrinsic aberrations by comprehensive calibration of an ordinary microscope, enabling accurate localization of single emitters in three dimensions throughout an ultrawide and deep field. To complete the extraction of spatial information from microscale bodies ranging from imaging substrates to microsystem technologies, we introduce a synergistic concept of the rigid transformation of the positions of multiple emitters in three dimensions, improving precision, testing accuracy, and yielding measurements in six degrees of freedom. Our study illuminates the challenge of aberration effects in localization microscopy, redefines the challenge as an opportunity for accurate, precise, and complete localization, and elucidates the performance and reliability of a complex microelectromechanical system.

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“…The presence of contaminants is vital in the production of very sensitive to dirt electronic packages [1]. The products should be of acceptable quality.…”

Section: Introductionmentioning

confidence: 99%

Automated data monitoring of MEMS cleanroom parametric requirements

Capanang

Panganiban²,

Ortiz³

et al. 2021

IJEECS

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<p>Cleanroom parameters such as temperature, relative humidity and particle count are vital in maintaining cleanliness. People and machines working inside the cleanroom are main contributors for the sudden changes of the separameters. Measurements and monitoring of these parameters are therefore necessary to reduce rejects and downtime in the production of micro-electro-mechanical systems (MEMS). This paper presents a method of developmentof an automated data monitoring of MEMS cleanroom parametric requirements. The prototype developed uses DHT11 sensor and Sharp dust sensor for measuring the temperature, humidity and particle count respectively which are displayed in an LCD display. These parameters are recorded through a data logger for analysis and control. Additionally, agraphical user interface was also developed using visual studio for the working personnel and for supervisory monitoring and control. As a result, the possible quality compromise in the production of MEMS is detected when the monitored parameters are beyond the range.</p>

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Particle Tracking of Microelectromechanical System Performance and Reliability

Cited by 9 publications

References 17 publications

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

Accurate localization microscopy by intrinsic aberration calibration

Automated data monitoring of MEMS cleanroom parametric requirements

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