This study proposes a gait model that describes the relation between the lower limb muscle forces and the center-of-gravity (CoG) velocity in the forward, vertical, and lateral directions. Based on the CoG velocity and lower limb muscle forces obtained from gait measurements, the unknown parameters in the gait model are identified using a Kalman filter. The CoG velocity is estimated by applying the identified parameters and lower limb muscle forces to the model. After the accuracy of the proposed model is verified, the model is used to examine the relationship between the lower limb muscle groups used to construct the gait model and the gait velocity in three directions. The estimated CoG velocity in the vertical and lateral directions is more accurate than that in the forward direction. The analysis results indicate that the fluctuation of the CoG trajectory in the vertical and lateral directions can be accurately expressed using the 10 muscle forces for each leg used in the model. The obtained results can be used to quantitatively evaluate CoG sway. The proposed model can be applied in medical care and sports medicine.

Herein, an implantable energy-harvesting system utilizing the contraction of electrically stimulated skeletal muscle is proposed for self-sustainable batteries of implantable medical devices (IMDs) and health-monitoring devices. To achieve high energy conversion efficiency, a resonance generator utilizing the vibration of the skeletal muscle, called as incomplete tetanus, is proposed. Considering the multi-dynamics of muscle contraction, oscillator, and electrostatic induction, design parameters, such as the stimulation condition of the muscle and the mechanical characteristics of the resonance generator, are optimized. In the benchtop experiment, the power generated by the prototype is 20.48 μW. Moreover, a positive net power of 13.1 μW is generated in the ex vivo experiments using the skeletal muscles of toads; this power is sufficient to operate IMDs, thus demonstrating the feasibility of the proposed energy harvesting system using incomplete tetanus of the skeletal muscle.

Bioactuators using skeletal muscle are expected to be applied to medical and welfare equipment as functional materials with self-growth functions. In this regard, their contraction force must be controlled with high accuracy for the desired operation. Therefore, in this study, a model-based control method that follows the contraction force against an arbitrary reference contraction force is proposed to control the contraction of skeletal muscle. The muscle-contraction mechanism is modeled, and the stimulating voltage for exerting the desired contraction force is obtained using this model. Furthermore, the proposed method is validated experimentally using the gastrocnemius muscle of a toad. In the experiment, we identify muscle-contraction model parameters that can reproduce the contraction-force response of the gastrocnemius muscle from experimental data. Using the model, the stimulating voltage for exerting a reference is calculated. The voltage is applied to the gastrocnemius muscle of a toad to control the contraction force. The experimental results show that the proposed model-based control method can control muscle contractions even under a complicated reference contraction force.

Irreversible electroporation (IRE) is a less-invasive therapy to treat tumors by delivering short and intensive electric pulses to the tissue. The pulse settings are important factors that affect IRE outcome. In this study, we proposed a three-dimensional (3-D) cell culture model to determine the critical electric field for IRE depending on the effect of pulse parameters, particularly pulse repetition and interval, and adjuvants. Agarose gel containing fibroblasts was used as a tissue phantom. After application of electric pulses, the area that contained full of necrotized cells was quantified and compared with the distribution of the electric field estimated from a numerical analysis, so that the critical electric field strength to cause cell necrosis was determined. Ablated area increased as a function of pulse repetition, and reached a plateau at 120 pulses. When the pulse interval was extended from 100 ms to 1 s, the ablated area increased by approximately 30%. Addition of 10% DMSO and 5% ethanol also significantly increased the ablated area by 15% and 55%, respectively, indicating a reduction of the critical electric field strength. The critical electric field strength was independent of the magnitude of the applied voltage when the pulse length, interval, and the number of pulses were fixed. A longer interval and adjuvants increased the ablated area, and therefore decreased the critical electric field strength. The 3-D tissue phantom composed of agarose gel and cells was useful for examination of the IRE effect by comparing the experimentally determined necrotized region with a numerical analysis.

The two-joint link model of mono- and biarticular muscles in human hindlimbs has been established on the basis of biomechanical and mechanical engineering analyses of electromyographic data and testing of the results using robotic hindlimbs equipped with mono- and/or biarticular actuators. The present review applies this model to the analysis of pedaling biomechanics and demonstrates its applicability to studies of human and non-human limb locomotion. Previously published three examples of electromyographic data on pedaling biomechanics are analyzed and reviewed in light of the two-joint link model. As comparable to published data on pedaling biomechanics, the results propose the essential parameters of the model, including activity switches and their directional changes, forces and their combined forces, all that occur in 360 degrees around the right ankle joint during the stationary and continuous pedaling activities. In addition, the co-activation of an antagonistic pair of biarticular muscles and parallel linkage function of a biarticular muscle are proposed to be tested further in both engineering and biological sciences. As biomimetics has contributed to engineering science, the models and/or hypotheses that would be generated in engineering science can be applied to biological science.