New extensometer to measure in vivo uniaxial mechanical properties of human skin.

Biomechanical properties of skin are important for clinical decision making as well as clinical intervention. Measuring these properties in vivo is critical for estimating dimensional behaviour of skin flap or graft after harvest. However, existing methodologies and devices often suffer from lack of standardisation and unwanted peripheral force contribution due to the deformation of surrounding tissues during measurement. This naturally leads to measurement inaccuracies and lack of reproducibility. In order to improve the measurement accuracy, a new portable extensometer, which measures the non-invasive in vivo biomechanical properties of skin, has been designed and constructed. This design incorporates three pads that attach to the skin, including a C-shaped pad to shield the force sensor from peripheral forces. Such design produces data that are significantly closer to in vitro measurements. The results have been verified by finite element analysis, and experiments on rubber sheets and pig skins. This device can be used to obtain biomechanical properties of skin that will aid doctors in measuring skin elasticity and surgical planning, especially in skin flap surgery.

Non-invasive prediction of skin flap shrinkage: a new concept based on animal experimental evidence.

A non-invasive, in vivo method has been developed to predict the skin flap shrinkage (retraction) following a harvest. It involves the use of a novel custom-designed extensometer to measure the force-displacement behaviour of skin and subsequent data analysis to estimate the shrinkage. In validation experiments performed on pigs, this method has been shown to produce results with an average absolute error of 6.0% between the actual and predicted shrinkages. This may be close to what an experienced surgeon would estimate subjectively, thus indicating the potential usefulness of this method to predict flap shrinkage of patient's donor sites.

The effects of repeatedly heated frying oil and high cholesterol diet on the bone in ovariectomised rats.

The use of repeatedly heated frying oils and intake of high cholesterol diet have been linked to bone damage. The aim of this study is to determine the combined effects of taking repeatedly heated frying oils (palm or soy oil) and high cholesterol diet on the dynamic histomorphometric parameters of bone. Ovariectomised rats were used as animal model of post-menopausal osteoporosis. After six months of treatment, Double-labeled Surface (dLS/BS), Mineralising surface (MS/BS) and Bone Formation Rate (BFR/BS) of ovariectomised rats (OvxC) were significantly reduced compared to the normal control group. Additions of fresh or once-heated palm or soy oil into high cholesterol diet seem to have improved the dynamic parameters towards the normal control values. However, when these oils were repeatedly heated, the protective effects were lost and the dynamic parameters except MS/BS dropped back towards the ovariectomised-control values.

Stability and motor adaptation in human arm movements.

In control, stability captures the reproducibility of motions and the robustness to environmental and internal perturbations. This paper examines how stability can be evaluated in human movements, and possible mechanisms by which humans ensure stability. First, a measure of stability is introduced, which is simple to apply to human movements and corresponds to Lyapunov exponents. Its application to real data shows that it is able to distinguish effectively between stable and unstable dynamics. A computational model is then used to investigate stability in human arm movements, which takes into account motor output variability and computes the force to perform a task according to an inverse dynamics model. Simulation results suggest that even a large time delay does not affect movement stability as long as the reflex feedback is small relative to muscle elasticity. Simulations are also used to demonstrate that existing learning schemes, using a monotonic antisymmetric update law, cannot compensate for unstable dynamics. An impedance compensation algorithm is introduced to learn unstable dynamics, which produces similar adaptation responses to those found in experiments.

A model of force and impedance in human arm movements.

This paper describes a simple computational model of joint torque and impedance in human arm movements that can be used to simulate three-dimensional movements of the (redundant) arm or leg and to design the control of robots and human-machine interfaces. This model, based on recent physiological findings, assumes that (1) the central nervous system learns the force and impedance to perform a task successfully in a given stable or unstable dynamic environment and (2) stiffness is linearly related to the magnitude of the joint torque and increased to compensate for environment instability. Comparison with existing data shows that this simple model is able to predict impedance geometry well.