Quanjun Song

Learn More
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)
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)
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)
Power assist robot (PAR) would be of great value to certain human activities or for special groups such as the aged and the weakling. If PAR can provide appropriate power assist, it would be more effective to adapt to human intention accordingly, otherwise, it would be a burden to human body, especially for those have difficulty in standing up and sitting(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)
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)
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)
This paper presents a novel 2 DOF robotic arm wrestling system integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3-D MEMS accelerometer, and USB camera. The arm wrestling robot (AWR) is used to play arm wrestling game with human for entertainment. Based on the force testing equipment, we acquire the data of surface(More)