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Biomedical subjects

Kurt G Clowers

Publications and source records attributed to Kurt G Clowers.

2 recordsLinked to original sources

Ground reaction force and 3D biomechanical characteristics of walking in short-leg walkers.

Short-leg walking boots offer several advantages over traditional casts. However, their effects on ground reaction forces (GRF) and three-dimensional (3D) biomechanics are not fully understood. The purpose of the study was to examine 3D lower extremity kinematics and joint dynamics during walking in two different short-leg walking boots. Eleven (five females and six males) healthy subjects performed five level walking trials in each of three conditions: two testing boot conditions, Gait Walker (DeRoyal Industries, Inc.) and Equalizer (Royce Medical Co.), and one pair of laboratory shoes (Noveto, Adidas). A force platform and a 6-camera Vicon motion analysis system were used to collect GRFs and 3D kinematic data during the testing session. A one-way repeated measures analysis of variance (ANOVA) was used to evaluate selected kinematic, GRF, and joint kinetic variables (p<0.05). The results revealed that both short-leg walking boots were effective in minimizing ankle eversion and hip adduction. Neither walker increased the bimodal vertical GRF peaks typically observed in normal walking. However, they did impose a small initial peak (<1BW) earlier in the stance phase. The Gait Walker also exhibited a slightly increased vertical GRF during midstance. These characteristics may be related to the sole materials/design, the restriction of ankle movements, and/or the elevated heel heights of the tested walkers. Both walkers appeared to increase the demand on the knee extensors while they decreased the demand of the knee and hip abductors based on the joint kinetic results.

Adult↗

A novel method for using accelerometer data to predict energy expenditure.

The purpose of this study was to develop a new two-regression model relating Actigraph activity counts to energy expenditure over a wide range of physical activities. Forty-eight participants [age 35 yr (11.4)] performed various activities chosen to represent sedentary, light, moderate, and vigorous intensities. Eighteen activities were split into three routines with each routine being performed by 20 individuals, for a total of 60 tests. Forty-five tests were randomly selected for the development of the new equation, and 15 tests were used to cross-validate the new equation and compare it against already existing equations. During each routine, the participant wore an Actigraph accelerometer on the hip, and oxygen consumption was simultaneously measured by a portable metabolic system. For each activity, the coefficient of variation (CV) for the counts per 10 s was calculated to determine whether the activity was walking/running or some other activity. If the CV was 10, a lifestyle/leisure time physical activity regression was used. In the cross-validation group, the mean estimates using the new algorithm (2-regression model with an inactivity threshold) were within 0.75 metabolic equivalents (METs) of measured METs for each of the activities performed (P >or= 0.05), which was a substantial improvement over the single-regression models. The new algorithm is more accurate for the prediction of energy expenditure than currently published regression equations using the Actigraph accelerometer.

Activities of Daily Living↗