Thermally-induced change in the relaxation behavior of skin tissue.

Skin biothermomechanics is highly interdisciplinary, involving bioheat transfer, burn damage, biomechanics, and physiology. Characterization of the thermomechanical behavior of skin tissue is of great importance and can contribute to a variety of medical applications. However, few quantitative studies have been conducted on the thermally-dependent mechanical properties of skin tissue. The aim of the present study is to experimentally examine the thermally-induced change in the relaxation behavior of skin tissue in both hyperthermal and hypothermic ranges. The results show that temperature has great influence on the stress-relaxation behavior of skin tissue under both hyperthermal and hypothermic temperatures; the quantitative relationship that has been found between temperature and the viscoelastic parameter (the elastic fraction or fractional energy dissipation) was temperature dependent, with greatest dissipation at high temperature levels.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.