Parkinson’s disease manifests in movement disorder symptoms, such as hand tremor. There exists an assortment of therapy interventions. In particular deep brain stimulation offers considerable efficacy for the treatme...Parkinson’s disease manifests in movement disorder symptoms, such as hand tremor. There exists an assortment of therapy interventions. In particular deep brain stimulation offers considerable efficacy for the treatment of Parkinson’s disease. However, a considerable challenge is the convergence toward an optimal configuration of tuning parameters. Quantified feedback from a wearable and wireless system consisting of an accelerometer and gyroscope can be enabled through a novel software application on a smartphone. The smartphone with its internal accelerometer and gyroscope can record the quantified attributes of Parkinson’s disease and tremor through mounting the smartphone about the dorsum of the hand. The recorded data can be then wirelessly transmitted as an email attachment to an Internet derived resource for subsequent post-processing. The inertial sensor data can be consolidated into a feature set for machine learning classification. A multilayer perceptron neural network has been successfully applied to attain considerable classification accuracy between deep brain stimulation “On” and “Off” scenarios for a subject with Parkinson’s disease. The findings establish the foundation for the broad objective of applying wearable and wireless systems for the development of closed-loop optimization of deep brain stimulation parameters in the context of cloud computing with machine learning classification.展开更多
Single-axis rotation technique is often used in the marine laser inertial navigation system so as to modulate the constant biases of non-axial gyroscopes and accelerometers to attain better navigation performance.Howe...Single-axis rotation technique is often used in the marine laser inertial navigation system so as to modulate the constant biases of non-axial gyroscopes and accelerometers to attain better navigation performance.However,two significant accelerometer nonlinear errors need to be attacked to improve the modulation effect.Firstly,the asymmetry scale factor inaccuracy enlarges the errors of frequent zero-cross oscillating specific force measured by non-axial accelerometers.Secondly,the traditional linear model of accelerometers can hardly measure the continued or intermittent acceleration accurately.These two nonlinear errors degrade the high-precision specific force measurement and the calibration of nonlinear coefficients because triaxial accelerometers is urgent for the marine navigation.Based on the digital signal sampling property,the square coefficients and cross-coupling coefficients of accelerometers are considered.Meanwhile,the asymmetry scale factors are considered in the I-F conversion unit.Thus,a nonlinear model of specific force measurement is established compared to the linear model.Based on the three-axis turntable,the triaxial gyroscopes are utilized to measure the specific force observation for triaxial accelerometers.Considering the nonlinear combination,the standard calibration parameters and asymmetry factors are separately estimated by a two-step iterative identification procedure.Besides,an efficient specific force calculation model is approximately derived to reduce the real-time computation cost.Simulation results illustrate the sufficient estimation accuracy of nonlinear coefficients.The experiments demonstrate that the nonlinear model shows much higher accuracy than the linear model in both the gravimetry and sway navigation validations.展开更多
This paper deals with the problem of accelerometer error estimation and compensation for a three-axis gyro-stabilized camera mount. In a dynamic environment, the aircraft motion acceleration affects the accelerome ：e...This paper deals with the problem of accelerometer error estimation and compensation for a three-axis gyro-stabilized camera mount. In a dynamic environment, the aircraft motion acceleration affects the accelerome ：er output and causes a degradation of attitude steady accuracy. In order to improve control accuracy, this paper proposes a proportional multiple-integral observer- based control strategy to estimate and compensate the accelerometer error. The basic idea of this paper is to approximate the error property by using a q-order polynomial function and extend the error and its derivatives as augmented states. Then a proportional multiple-integral observer is developed to estimate the error, with which the relationship between the error and the imbalance torque is formulated. The estimated value is compared to an angle threshold, the result of which is used to compen- sate the accelerometer output. Through static and vehicle-mounted experiments, it is demonstrated that compared with the tra- ditional method, the proposed method can improve the attitude steady accuracy effectively.展开更多
针对传统的航姿参考系统AHRS(Attitude and Heading Reference System)中姿态角精度不高的问题,设计了一种新型的基于卡尔曼滤波的姿态检测系统。该系统采用了三轴磁传感器、三轴陀螺仪及三轴加速度计,用四元数的方法来描述载体运动的姿...针对传统的航姿参考系统AHRS(Attitude and Heading Reference System)中姿态角精度不高的问题,设计了一种新型的基于卡尔曼滤波的姿态检测系统。该系统采用了三轴磁传感器、三轴陀螺仪及三轴加速度计,用四元数的方法来描述载体运动的姿态,通过陀螺仪测姿态四元数,卡尔曼滤波算法融合加速度计和磁传感器数据,对姿态四元数进行修正,从而提高姿态解算精度。实验数据表明,系统能够较好修正陀螺仪漂移,且三个角度的均方根误差均优于0.25°,具有良好的噪声抑制能力。展开更多
文摘Parkinson’s disease manifests in movement disorder symptoms, such as hand tremor. There exists an assortment of therapy interventions. In particular deep brain stimulation offers considerable efficacy for the treatment of Parkinson’s disease. However, a considerable challenge is the convergence toward an optimal configuration of tuning parameters. Quantified feedback from a wearable and wireless system consisting of an accelerometer and gyroscope can be enabled through a novel software application on a smartphone. The smartphone with its internal accelerometer and gyroscope can record the quantified attributes of Parkinson’s disease and tremor through mounting the smartphone about the dorsum of the hand. The recorded data can be then wirelessly transmitted as an email attachment to an Internet derived resource for subsequent post-processing. The inertial sensor data can be consolidated into a feature set for machine learning classification. A multilayer perceptron neural network has been successfully applied to attain considerable classification accuracy between deep brain stimulation “On” and “Off” scenarios for a subject with Parkinson’s disease. The findings establish the foundation for the broad objective of applying wearable and wireless systems for the development of closed-loop optimization of deep brain stimulation parameters in the context of cloud computing with machine learning classification.
基金Project(61174002)supported by the National Natural Science Foundation of ChinaProject(200897)supported by the Foundation of National Excellent Doctoral Dissertation of PR China+1 种基金Project(NCET-10-0900)supported by the Program for New Century ExcellentTalents in University,ChinaProject(131061)supported by the Fok Ying Tung Education Foundation,China
文摘Single-axis rotation technique is often used in the marine laser inertial navigation system so as to modulate the constant biases of non-axial gyroscopes and accelerometers to attain better navigation performance.However,two significant accelerometer nonlinear errors need to be attacked to improve the modulation effect.Firstly,the asymmetry scale factor inaccuracy enlarges the errors of frequent zero-cross oscillating specific force measured by non-axial accelerometers.Secondly,the traditional linear model of accelerometers can hardly measure the continued or intermittent acceleration accurately.These two nonlinear errors degrade the high-precision specific force measurement and the calibration of nonlinear coefficients because triaxial accelerometers is urgent for the marine navigation.Based on the digital signal sampling property,the square coefficients and cross-coupling coefficients of accelerometers are considered.Meanwhile,the asymmetry scale factors are considered in the I-F conversion unit.Thus,a nonlinear model of specific force measurement is established compared to the linear model.Based on the three-axis turntable,the triaxial gyroscopes are utilized to measure the specific force observation for triaxial accelerometers.Considering the nonlinear combination,the standard calibration parameters and asymmetry factors are separately estimated by a two-step iterative identification procedure.Besides,an efficient specific force calculation model is approximately derived to reduce the real-time computation cost.Simulation results illustrate the sufficient estimation accuracy of nonlinear coefficients.The experiments demonstrate that the nonlinear model shows much higher accuracy than the linear model in both the gravimetry and sway navigation validations.
基金supported by the National Natural Science Foundation of China(Grant Nos.61174121,61333005 and 61121003)the Ph.D Programs Foundations of the Ministry of Education China
文摘This paper deals with the problem of accelerometer error estimation and compensation for a three-axis gyro-stabilized camera mount. In a dynamic environment, the aircraft motion acceleration affects the accelerome ：er output and causes a degradation of attitude steady accuracy. In order to improve control accuracy, this paper proposes a proportional multiple-integral observer- based control strategy to estimate and compensate the accelerometer error. The basic idea of this paper is to approximate the error property by using a q-order polynomial function and extend the error and its derivatives as augmented states. Then a proportional multiple-integral observer is developed to estimate the error, with which the relationship between the error and the imbalance torque is formulated. The estimated value is compared to an angle threshold, the result of which is used to compen- sate the accelerometer output. Through static and vehicle-mounted experiments, it is demonstrated that compared with the tra- ditional method, the proposed method can improve the attitude steady accuracy effectively.
文摘针对传统的航姿参考系统AHRS(Attitude and Heading Reference System)中姿态角精度不高的问题,设计了一种新型的基于卡尔曼滤波的姿态检测系统。该系统采用了三轴磁传感器、三轴陀螺仪及三轴加速度计,用四元数的方法来描述载体运动的姿态,通过陀螺仪测姿态四元数,卡尔曼滤波算法融合加速度计和磁传感器数据,对姿态四元数进行修正,从而提高姿态解算精度。实验数据表明,系统能够较好修正陀螺仪漂移,且三个角度的均方根误差均优于0.25°,具有良好的噪声抑制能力。
