Dynamics of MEMS-Based Angular Rate Sensors Excited via External Electrostatic Forces

2021 ◽  
Author(s):  
Ibrahim Gebrel ◽  
Ligang Wang ◽  
Samuel Asokanthan
2000 ◽  
Vol 10 (1-2) ◽  
pp. 15
Author(s):  
Eugene Sprague ◽  
Julio C. Palmaz ◽  
Cristina Simon ◽  
Aaron Watson

Micromachines ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 79
Author(s):  
Jijun Geng ◽  
Linyuan Xia ◽  
Dongjin Wu

The demands for indoor positioning in location-based services (LBS) and applications grow rapidly. It is beneficial for indoor positioning to combine attitude and heading information. Accurate attitude and heading estimation based on magnetic, angular rate, and gravity (MARG) sensors of micro-electro-mechanical systems (MEMS) has received increasing attention due to its high availability and independence. This paper proposes a quaternion-based adaptive cubature Kalman filter (ACKF) algorithm to estimate the attitude and heading based on smart phone-embedded MARG sensors. In this algorithm, the fading memory weighted method and the limited memory weighted method are used to adaptively correct the statistical characteristics of the nonlinear system and reduce the estimation bias of the filter. The latest step data is used as the memory window data of the limited memory weighted method. Moreover, for restraining the divergence, the filter innovation sequence is used to rectify the noise covariance measurements and system. Besides, an adaptive factor based on prediction residual construction is used to overcome the filter model error and the influence of abnormal disturbance. In the static test, compared with the Sage-Husa cubature Kalman filter (SHCKF), cubature Kalman filter (CKF), and extended Kalman filter (EKF), the mean absolute errors (MAE) of the heading pitch and roll calculated by the proposed algorithm decreased by 4–18%, 14–29%, and 61–77% respectively. In the dynamic test, compared with the above three filters, the MAE of the heading reduced by 1–8%, 2–18%, and 2–21%, and the mean of location errors decreased by 9–22%, 19–31%, and 32–54% respectively by using the proposed algorithm for three participants. Generally, the proposed algorithm can effectively improve the accuracy of heading. Moreover, it can also improve the accuracy of attitude under quasistatic conditions.


2021 ◽  
Author(s):  
Hui Zhao ◽  
Zhong Su ◽  
Qing Li ◽  
Fu-chao Liu ◽  
Ning Liu

2021 ◽  
Vol 11 (4) ◽  
pp. 1902
Author(s):  
Liqiang Zhang ◽  
Yu Liu ◽  
Jinglin Sun

Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian navigation systems (PNSs) suffer from drift, especially heading drift. To mitigate heading drift, considering the complexity of human motion and the environment, we introduce a novel hybrid framework that integrates a foot-state classifier that triggers the zero-velocity update (ZUPT) algorithm, zero-angular-rate update (ZARU) algorithm, and a state lock, a magnetic disturbance detector, a human-motion-classifier-aided adaptive fusion module (AFM) that outputs an adaptive heading error measurement by fusing heuristic and magnetic algorithms rather than simply switching them, and an error-state Kalman filter (ESKF) that estimates the optimal systematic error. The validation datasets include a Vicon loop dataset that spans 324.3 m in a single room for approximately 300 s and challenging walking datasets that cover large indoor and outdoor environments with a total distance of 12.98 km. A total of five different frameworks with different heading drift correction methods, including the proposed framework, were validated on these datasets, which demonstrated that our proposed ZUPT–ZARU–AFM–ESKF-aided PNS outperforms other frameworks and clearly mitigates heading drift.


Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2363
Author(s):  
Darya A. Kuznetsova ◽  
Dinar R. Gabdrakhmanov ◽  
Denis M. Kuznetsov ◽  
Svetlana S. Lukashenko ◽  
Valery M. Zakharov ◽  
...  

The solution behavior and physicochemical characteristics of polymer–colloid complexes based on cationic imidazolium amphiphile with a dodecyl tail (IA-12) and polyacrylic acid (PAA) or DNA decamer (oligonucleotide) were evaluated using tensiometry, conductometry, dynamic and electrophoretic light scattering and fluorescent spectroscopy and microscopy. It has been established that PAA addition to the surfactant system resulted in a ca. 200-fold decrease in the aggregation threshold of IA-12, with the hydrodynamic diameter of complexes ranging within 100–150 nm. Electrostatic forces are assumed to be the main driving force in the formation of IA-12/PAA complexes. Factors influencing the efficacy of the complexation of IA-12 with oligonucleotide were determined. The nonconventional mode of binding with the involvement of hydrophobic interactions and the intercalation mechanism is probably responsible for the IA-12/oligonucleotide complexation, and a minor contribution of electrostatic forces occurred. The latter was supported by zeta potential measurements and the gel electrophoresis technique, which demonstrated the low degree of charge neutralization of the complexes. Importantly, cellular uptake of the IA-12/oligonucleotide complex was confirmed by fluorescence microscopy and flow cytometry data on the example of M-HeLa cells. While single IA-12 samples exhibit roughly similar cytotoxicity, IA-12–oligonucleotide complexes show a selective effect toward M-HeLa cells (IC50 1.1 µM) compared to Chang liver cells (IC50 23.1 µM).


Author(s):  
Daniel Rojas-Valverde ◽  
José Pino-Ortega ◽  
Rafael Timón ◽  
Randall Gutiérrez-Vargas ◽  
Braulio Sánchez-Ureña ◽  
...  

The extensive use of wearable sensors in sport medicine, exercise medicine, and health has increased the interest in their study. That is why it is necessary to test these technologies’ efficiency, effectiveness, agreement, and reliability in different settings. Consequently, the purpose of this article was to analyze the magnetic, angular rate, and gravity (MARG) sensor’s test-retest agreement and reliability when assessing multiple body segments’ external loads during off-road running. A total of 18 off-road runners (38.78 ± 10.38 years, 73.24 ± 12.6 kg, 172.17 ± 9.48 cm) ran two laps (1st and 2nd Lap) of a 12 km circuit wearing six MARG sensors. The sensors were attached to six different body segments: left (MPLeft) and right (MPRight) malleolus peroneus, left (VLLeft) and right (VLRight) vastus lateralis, lumbar (L1-L3), and thorax (T2-T4) using a special neoprene suit. After a principal component analysis (PCA) was performed, the total data set variance of all body segments was represented by 44.08%–70.64% for the 1st PCA factor considering two variables, Player LoadRT and Impacts, on L1-L3, respectively. These two variables were chosen among three total accelerometry-based external load indicators (ABELIs) to perform the agreement and reliability tests due to their relevance based on PCAs for each body segment. There were no significant differences between laps in the Player LoadRT or Impacts ( p > 0.05, trivial). The intraclass correlation and lineal correlation showed a substantial to almost perfect over-time test consistency assessed via reliability in both Player LoadRT and Impacts. Bias and t-test assessments showed good agreement between Laps. It can be concluded that MARGs sensors offer significant test re-test reliability and good agreement when assessing off-road kinematics in the six different body segments.


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