A NEW METHOD FOR MEASURING SEGMENT MASS & SEGMENT CENTER OF MASS LOCATION OF HUMAN BODY

The purpose of this study was to introduce a new method for measuring segment mass & segment center of mass of human body, and determine whether valid measures of segment inertial properties can be generated from using this new method. In first place, we introduced the principles of two types of instruments used in this new method, one for measuring segment moment of mass (mb x rb), and the other for measuring segment center of mass (rb), and then we obtained segment mass (mb)' We measured 9 subjects using the above two types of instruments, and these segments measured included one forearm-hand, one upper limb, one shank-foot and one lower limb. There is no significance discrepancy between the calculations of database provided by Xiuyuan Zheng using eT method and ours, which showed that the new method is a valid method

Front-end multi-channel PMT-associated readout chip for hodoscope application

International audienceThe system development requires a dedicated multi-channel readout ASIC (Application Specific Integrated Circuit) to be associated with the MaPMTs. Each channel should have very low input impedance to avoid electrical crosstalk between adjacent channels and to minimize effects of detector and wiring capacitances (Cd + Cw). Crosstalk between channels may degrade position resolution, while these capacitances may degrade both frequency and noise performances. Each channel should also provide two separated outputs corresponding respectively to high-speed signal-event detection and low-noise signal-charge quantification at low counting rate. This paper presents a readout chip for this purpose. It has been designed in a 0.35µm SiGe BiCMOS process (AMS). This process allows the use of RF and large-transconductance bipolar components, which is useful for the design of wide-band, low-impedance and low-noise circuits with improved performances

Smart Meters Integration in Distribution System State Estimation with Collaborative Filtering and Deep Gaussian Process

The problem of state estimations for electric distribution system is considered. A collaborative filtering approach is proposed in this paper to integrate the slow time-scale smart meter measurements in the distribution system state estimation, in which the deep Gaussian process is incorporated to infer the fast time-scale pseudo measurements and avoid anomalies. Numerical tests have demonstrated the higher estimation accuracy of the proposed method