2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)最新文献_第2页

Finding the critical impact energy for micro debris generation in MEMS inertial sensors MEMS惯性传感器中微碎片产生的临界冲击能量求解

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430462

L. G. Pagani, L. Guerinoni, L. Falorni, P. Fedeli, G. Langfelder

引用次数: 0

Sensor Fusion To Improve State Estimate Accuracy Using Multiple Inertial Measurement Units 传感器融合提高多惯性测量单元状态估计精度

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430484

Ujjval N. Patel, Imraan A. Faruque

引用次数: 3

Resonant Accelerometer with Compliant Parallel Motion Linkage Force Amplification Mechanism 具有柔性并联运动连杆力放大机构的谐振加速度计

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430489

O. Halevy, Stella Lulinsky, S. Krylov

引用次数: 1

Theoretical Consideration of Mismatch Compensation for MEMS Resonator Having Unaligned Principle Axes 主轴未对准的MEMS谐振器失配补偿的理论思考

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430491

T. Tsukamoto, Shuji Tanaka

引用次数: 2

Exploiting Nonlinearities for Frequency-Matched MEMS Gyroscopes Tuning 利用非线性进行频率匹配MEMS陀螺仪调谐

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430478

J. Marconi, Giacomo Bonaccorsi, D. Giannini, L. Falorni, F. Braghin

引用次数: 2

Vibration Immune, Long-Term Stable and Low Noise Synchronized Mass MEMS Gyroscope 抗振动、长期稳定、低噪声的同步大质量MEMS陀螺仪

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430483

I. Prikhodko, J. Geen, Carey Merritt, Sam Zhang

引用次数: 3

Insole-based Real-time Gait Analysis: Feature Extraction and Classification 基于鞋垫的实时步态分析:特征提取和分类

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430482

A. R. Anwary, Damla Arifoglu, Michael Jones, M. Vassallo, H. Bouchachia

{"title":"Insole-based Real-time Gait Analysis: Feature Extraction and Classification","authors":"A. R. Anwary, Damla Arifoglu, Michael Jones, M. Vassallo, H. Bouchachia","doi":"10.1109/INERTIAL51137.2021.9430482","DOIUrl":"https://doi.org/10.1109/INERTIAL51137.2021.9430482","url":null,"abstract":"Gait assessment relies on clinical tools based on observation by trained staffs who give a subjective opinion. Objective gait analysis via motion capture systems (e.g. Qualisys) have limited availability as they are laboratory based and require complex equipment. A low-cost user-friendly Inertial Measurement Units (IMUs) embedded insole and an Android App based personalized gait analysis system is developed for uses in home or clinics. Accelerometer and gyroscope synchronous data are collected from both right and left legs for 10 young and 10 older adults a period of 100 consecutive days. We propose an automatic gait features extraction method, real-time visualization and age-groups classification. Accuracy of stride detection method is 100% for young. Accuracy for older adults is 91% for right and 88% for left leg. Convolutional neural networks (CNNs) are used to extract features from gait data and are combined with long short-term memory (LSTM) to exploit the time information between features. This is evaluated empirically using traditional classification and deep learning techniques (CNN+LSTM RNN) regardless of feature engineering. Accuracy to classify young and older adults with CNN-LSTM, NB, SVM and J48 is 100%. Our insole-based gait analysis automatically interprets the gait features and users can monitor their gait at home using our simple visualization tool that allows widespread home-based diagnosis and management of gait abnormalities and rehabilitation.","PeriodicalId":424028,"journal":{"name":"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122574686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Identification of Gain Mismatches in Control Electronics of Rate Integrating CVGs 速率积分CVGs控制电子学增益失配辨识

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430479

D. Vatanparvar, A. Shkel

{"title":"Identification of Gain Mismatches in Control Electronics of Rate Integrating CVGs","authors":"D. Vatanparvar, A. Shkel","doi":"10.1109/INERTIAL51137.2021.9430479","DOIUrl":"https://doi.org/10.1109/INERTIAL51137.2021.9430479","url":null,"abstract":"In Coriolis Vibratory Rate Integrating Gyroscopes (CVRIG), accuracy of angle measurement is known to be coupled to symmetry of the mechanical structure. This paper provides a study on the effect of asymmetries in control electronics on operation and accuracy of direct angle measurements. We demonstrated that gain mismatch in detection electronics affects the estimation of the pendulum variables in the CVRIG mathematical model. An error in the pendulum variables was shown to adversely affect the estimated orientation of the orbital trajectory and the closed-loop control. In the case of gain mismatch in actuation electronics, the control forces were observed to interfere with free precession of the oscillation pattern causing additional errors in the angle measurement. We proposed a method to distinguish the angle errors due to mechanical asymmetries from the angle errors caused by imperfections in control electronics. Using the method, we identified gain mismatches in the control electronics and subsequently used the identified parameters for calibration of a micro-fabricated gyroscope. By applying the method of calibration to a Dual Foucault Pendulum (DFP) gyroscope, we were able to reduce the angle bias error by 10-times and reached a 0.06 degree of precession accuracy at the input angular rate of 500 dps, without any compensation for mechanical asymmetries.","PeriodicalId":424028,"journal":{"name":"2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115748007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Effect of EAM on Quality Factor and Noise in MEMS Vibratory Gyroscopes EAM对MEMS振动陀螺仪质量因数和噪声的影响

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430471

Danmeng Wang, A. Shkel

引用次数: 2

Improved Sensor Based Human Activity Recognition via Hybrid Convolutional and Recurrent Neural Networks 基于混合卷积和递归神经网络的改进传感器人体活动识别

2021 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL) Pub Date : 2021-03-22 DOI: 10.1109/INERTIAL51137.2021.9430460

Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

引用次数: 10