The functional activation, through electrical stimulation, of the lower limb consisting of several deficient muscles requires well-patterned and coordinated activation of these muscles. This study presents a method for characterizing the parameters of the major muscle groups controlling the ankle and knee joints in cycling motion, the latter having particular significance in the rehabilitation of locomotion. To lower mechanical indeterminacy in the joints the system is reduced by grouping the muscles acting in synergism. The joint torques were calculated by inverse dynamics methods from cycling motion data, including kinematics and foot/pedal reaction loads (forces, moments). The mechanical indeterminacy was resolved by applying optimization criteria and the individual muscle torques were parceled-out from the joint torques. System identification of the individual muscles, part of which being bi-articular, in this non-isometric condition was performed from the relationship between the evaluated force and the measured EMG of each the muscles, using both first and second order linear transfer functions. Feasibility of the presented method was demonstrated through the computation of the coefficients of the muscles involved and validating the results on the experimental data obtained from one subject.
The functional activation, through electrical stimulation, of the lower limb consisting of several deficient muscles requires well-patterned and coordinated activation of these muscles. This study presents a method for characterizing the parameters of the major muscle groups controlling the ankle and knee joints in cycling motion, the latter having particular significance in the rehabilitation of locomotion. To lower mechanical indeterminacy in the joints the system is reduced by grouping the muscles acting in synergism. The joint torques were calculated by inverse dynamics methods from cycling motion data, including kinematics and foot/pedal reaction loads (forces, moments). The mechanical indeterminacy was resolved by applying optimization criteria and the individual muscle torques were parceled-out from the joint torques. System identification of the individual muscles, part of which being bi-articular, in this non-isometric condition was performed from the relationship between the evaluated force and the measured EMG of each the muscles, using both first and second order linear transfer functions. Feasibility of the presented method was demonstrated through the computation of the coefficients of the muscles involved and validating the results on the experimental data obtained from one subject.
A sampling protocol for biomonitoring of the volatile solvent methylene chloride (MeCl(2)) by analysis of urine from exposed workers was established. Storage temperature, sample volume in headspace vial (HSV), and time to sealing HSV on determination of MeCl(2) in urine were evaluated. MeCl(2) was analyzed by a solid-phase microextraction technique combined with gas chromatography. Volume of urine in HSV has no effect on MeCl(2) analysis. Delays of 30 and 60 min from collection of urine until sealing the HSV caused 14.47 +/- 6.98% and 26.17 +/- 9.57% decreases from baseline concentration, respectively. MeCl(2) concentration in spiked urine samples stored in sealed HSVs decreased on day 2 and then remained stable for 2 weeks. Refrigeration did not improve recovery although it seems to be associated with less variability. MeCl(2) in urine samples of seven exposed workers was in the range of 0.02-0.06 mg/L. Sampling of MeCl(2)-containing urine should include collection of urine in closed plastic bottles, transfer to HSV within 15 min, sealing and clamping of HSV within 15 s, and storage of HSV in refrigeration until analysis, but no longer than 2 weeks. Standard samples should be prepared on the day of test sample collection and handled under the same conditions.
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