To minimize the interference that skin-contact strain sensors cause natural skin deformation, physical conformability to the epidermal structure is critical. Here, we developed an ultrathin strain sensor made from poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) inkjet-printed on a polystyrene–polybutadiene–polystyrene (SBS) nanosheet. The sensor, whose total thickness and gauge factor were ∼1 µm and 0.73 ± 0.10, respectively, deeply conformed to the epidermal structure and successfully detected the small skin strain (∼2%) while interfering minimally with the natural deformation of the skin. Such an epidermal strain sensor will open a new avenue for precisely detecting the motion of human skin and artificial soft-robotic skin.

Understanding the rheological properties of soft biological tissue is a key issue for mechanical systems used in the health care field. We propose a simple empirical model using fractional dynamics and exponential nonlinearity (FDEN) to identify the rheological properties of soft biological tissue. The model is derived from detailed material measurements using samples isolated from porcine liver. We conducted dynamic viscoelastic and creep tests on liver samples using a plate-plate rheometer. The experimental results indicated that biological tissue has specific properties: (i) power law increase in the storage elastic modulus and the loss elastic modulus of the same slope; (ii) power law compliance (gain) decrease and constant phase delay in the frequency domain; (iii) power law dependence between time and strain relationships in the time domain; and (iv) linear dependence in the low strain range and exponential law dependence in the high strain range between stress-strain relationships. Our simple FDEN model uses only three dependent parameters and represents the specific properties of soft biological tissue.

Although tissue discrimination was not achieved using only a single nonlinear viscoelastic parameter, a set of four nonlinear viscoelastic parameters were able to reliably and accurately discriminate fat, breast fibroglandular tissue and muscle.

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Recently, the range of applications of surgical staplers has been extended to include laparoscopic liver resection because manipulation of a surgical stapler is very simple. Revealing the causes of stapling failure and suggesting a method to solve stapling failure are important for safe laparoscopic liver resection. Surgeons say that tissues make stapling more likely to fail if they are thick and brittle. However, the combinatorial effect of the thickness and stiffness of tissues on the success of surgical stapling for laparoscopic liver resection has not been investigated. Therefore, the objective of the present study was to investigate the effect of tissue thickness and tissue stiffness on the success rate (SR) of surgical stapling. From ex vivo stapling experimental results using pig livers, it is suggested that the effect of tissue thickness is greater than the effect of tissue stiffness on the SR of stapling. If tissue thickness is 5 mm, the SR of stapling is high regardless of the magnitude of the tissue-stiffness parameter. However, if tissue thickness is >10 mm, the SR of stapling has a relationship with nonlinear viscoelastic parameters. Therefore, the SR of stapling could be predicted from tissue thickness and nonlinear elastic parameters.