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Estimation of human pose in physical human-machine interactions such as bicycling is challenging because of highly-dimensional human motion and lack of inexpensive, effective motion sensors. In this paper, we present a computational scheme to estimate both the rider trunk pose and the bicycle roll angle using only inertial and force sensors. The estimation(More)
We have studied the behavior of Cd1-xZnxTe detectors in the temperature range 24-70°C. The detector count rate stability and leakage currents are presented as a function of voltage, time, and temperature. Detector polarization due to bulk and surface effects leading to a decreased leakage current was observed. At 70°C, the position of the 32 keV photopeak(More)
Modeling and control of physical human-machine interactions (pHMI) are challenging due to the high-dimensional movement of human body. In this paper, we present a hybrid statistical/physical dynamic model scheme to capture the pHMI through a rider-bicycle interaction example. We use the Gaussian process dynamical model (GPDM) to capture the high-dimensional(More)
Pose estimation of human motor skills such as bicycling in natural environments is challenging because of highly-dimensional human motion. In this paper, we present a dynamic rider/bicycle pose estimation scheme that can be used in outdoor environments. The proposed estimation scheme is based on the integration of the rider/bicycle dynamic model with the(More)
Slip is the major cause of falls in human locomotion. We present a new bipedal modeling approach to capture and predict human walking locomotion with slips. Compared with the existing bipedal models, the proposed slip walking model includes the human foot rolling effects, the existence of the double-stance gait and active ankle joints. One of the major(More)
Tracking whole-body human pose in physical human-machine interactions such as bicycling is challenging because of highly-dimensional human motions and lack of inexpensive, effective motion sensors in outdoor environment. In this paper, we present a computational scheme to estimate the whole-body pose in human-machine interaction with application to the(More)
Modeling physical human-robot interactions (pHRI) is important in studying human sensorimotor skills and designing human assistive and rehabilitation systems. One of the main challenges for modeling pHRI is the high dimensionality and complexity of human motion and its interactions with robots and the environment. We present an integrated physicallearning(More)
Evodia rutaecarpa (ER) and Tetradium glabrifolium (TG) are closely related species collected from different locations, with processed versus unprocessed and fresh versus 1-year-old samples. The purpose of this study is to determine the variability of their bioactive constituents; evodiamine, dehydroevodiamine, rutaecarpine and synephrine--as well as their(More)
Slip and fall is one of the major causes for human injuries for elders and professional workers. Real-time detection and prediction of the foot slip is critical for developing effective assistive and rehabilitation devices to prevent falls and train balance disorder patients. This paper presents a novel real-time slip detection and prediction scheme with(More)
Dynamic modeling of human bipedal walking is important for studying human locomotion and designing assistive and rehabilitation robotic devices. Physical principle-based models and data-driven learning models are two main methods to obtain human walking dynamics. We present analysis and connections between these two different modeling approaches. Mapping(More)