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— Falls in the elderly have always been a serious medical and social problem. To detect and predict falls, a hidden Markov model (HMM)-based method using tri-axial accelerations of human body is proposed. A wearable motion detection device using tri-axial accelerometer is designed and realized, which can detect and predict falls based on tri-axial(More)
In this paper, the surface electromyographic (EMG) signals is acquired from the upper limb when the experimenter competes with the arm wrestling robot (AWR) which is integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3D MEMS accelerometer, and USB camera. The arm wrestling robot (AWR) is intended to play arm wrestling game with(More)
Data association is a fundamental problem in multisensor fusion, tracking, and localization. The joint compatibility test is commonly regarded as the true solution to the problem. However, traditional joint compatibility tests are computationally expensive, are sensitive to linearization errors, and require the knowledge of the full covariance matrix of(More)
Frequent and high-risk fall accidents of the elders have become a serious medical and social problem. In this paper, a wireless automatic human fall detection device based on tri-axis accelerator is designed and realized; and a novel method to distinguish fall events from other daily activities is proposed also, including multi-impact falls and rolling down(More)
In this paper a novel prediction method of elbow torque from EMG signal using SVM is proposed. How to model the relations between EMG signals and various kinematical aspects of the movement behavior is a difficult problem in the researches of neurophysiology and biomechanics. Traditional prediction methods include using neural networks to model the(More)
Movement in micro-scale precision cannot be achieved by unaided human hand. This paper describes the design of a six degrees of freedom (DOF) micromanipulator based on compliant parallel mechanism. It is capable of delivering 6-DOF pure motions with high precision and featured by piezo-driven actuators, flexure hinges and integrated force sensor that can(More)
The static coupling of wrist force sensor is a major influencing factor to its measuring precision. Aiming at resolving the disadvantages such as low decoupling precision of the traditional method, we put forward a nonlinear decoupling method based on neural network. The major idea applied is to use the BP network to realize the mapping from input to output(More)
A novel human identification method based on dynamic plantar pressure distribution was proposed in this paper. An in-shoe plantar pressure measure system was applied to collect pressure information and the plantar pressure database was established. The wavelet transform was used to remove the noise. We extracted two sides of information including pressure(More)
This paper presents a pneumatic design on the Intelligent Air Transfer System (IATS) which will lead to realistic and extended applications as well as the technical means to transfer cask system over 30 tons in the fusion nuclear environment. Air bearings, as the core of the pneumatic drive, could be adaptively controlled for attitudes of the IATS with(More)
This paper presents the development of a micro-scale positioning device based on two degrees of freedom (DOF) plane compliant parallel mechanism, which is featured by piezo-driven actuators and flexure joints, integrated force/torque sensor that capable of delivering 2-DOF motions with high precision and providing real-time force/torque or position(More)