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van der Zee, T. J.

Publications and source records attributed to van der Zee, T. J..

2 recordsLinked to original sources

The high energetic cost of rapid force development in cyclic muscle contraction

Muscles consume metabolic energy for active movement, particularly when performing mechanical work or producing force. Less appreciated is the cost for activating and deactivating muscle quickly, which adds considerably to the overall cost of cyclic force production (Chasiotis et al., 1987). But the cost relative to mechanical work, which features in many movements, is unknown. We therefore tested whether fast activation-deactivation is costly compared to performing work or producing isometric force. We hypothesized that metabolic cost would increase with a proposed measure termed force-rate (rate of increase in muscle force) in cyclic tasks, separate from mechanical work or average force level. We tested humans (N = 9) producing cyclic knee extension torque against an isometric dynamometer (torque 22 N-m, cyclic waveform frequencies 0.5 - 2.5 Hz), while also quantifying the force and work of muscle fascicles against series elasticity (with ultrasonography), along with metabolic rate through respirometry. Net metabolic rate increased by more than fourfold (10.5 to 46.7 W) with waveform frequency. At high frequencies, the hypothesized force-rate cost accounted for nearly half (41%) of energy expenditure. This exceeded the cost for average force (17%) and was comparable to the cost for shortening work (42%). The energetic cost is explained by a simple first-order model of rate-limiting steps in muscle contraction, primarily crossbridge dynamics. The force-rate cost could contribute substantially to the overall cost of movements that require cyclic muscle activation, such as locomotion. Summary statementThe energetic cost of isometric muscle force production during cyclic muscle contraction increases sharply with cycle frequency and in proportion to the rate of force development

physiology

Fully automated algorithm estimates muscle fascicle length from ultrasound image

Ultrasound imaging is valuable for non-invasively estimating fascicle lengths and other features of pennate muscle, especially when performed computationally. Effective analysis techniques to date typically use optic flow to track displacements from image sequences, but are sensitive to integration drift for longer sequences. We here present an alternative algorithm that objectively estimates geometric features of pennate muscle from ultrasound images, without drift sensitivity. The algorithm identifies aponeuroses and estimates fascicle angles to derive fascicle lengths. Length estimates of human vastus lateralis and lateral gastrocnemius in healthy subjects (N = 9 and N = 1 respectively) compared well (root-mean-square error, RMSE < 0.80 cm) to manual estimates by independent observers (n = 3). The coefficient of multiple correlation (CMC) with manual estimates of fascicle length was comparable to previously reported for state-of-the-art optic flow algorithm (0.93-0.99), suggesting similar accuracy. The algorithm requires minimal manual intervention and can optionally extrapolate fascicle lengths that extend beyond the image frame. It facilitates automated analysis of ultrasound images without drift.

physiology