Several training methods have been developed to obtain motion information during real-time walking and feed it back to trainees who adjust their gait to ensure that the measured gait parameters approach target value, which may not always be suitable for every trainee owing to physical differences between individuals. This paper proposes a method of setting this target value considering these physical differences and discusses the usefulness of the gait training method, wherein a multichannel deep convolutional neural network (MC-DCNN) gait classification model constructed by learning ideal or non-ideal gait features beforehand is used for trainee gait classification. Activation maximization is applied to the MC-DCNN model; data wherein the ideal walking features are activated are generated based on trainee gait data. However, the amounts of features to be activated to generate a possible and natural gait are restricted. The original trainee gait, beyond individual physical differences, and gait data generated based on the original gait data seem to yield the target value considering the physical differences among individuals. This study focused on gait related to stumbling. To verify its usefulness, a multivariate gait dataset consisting of kinematic and kinetic indices labeled as “gait rarely associated with stumbling” or “gait frequently associated with stumbling” was divided into a training set, validation set, and test set. The MC-DCNN model learned gait features for multivariate gait data classification in the training set. It classified the gait with 96.04±0.12% accuracy against the validation set. Finally, by applying the proposed method to the multivariate gait data contained in the test set, we generated multivariate gait data classified as “gait rarely associated with stumbling” based on the input data. In addition, the generated multivariate gait data include motion that increases the thumb-to-ground distance and describe possible and natural gait considering the physical differences among individuals.

Carbon fiber running-specific prostheses (RSPs) are widely used among lower-limb amputee runners. However, which prosthesis provides the best performance for runners remains unknown. For this purpose, a computational model of the human body with a prosthesis was created and the effect of the prosthetic parameters on performance was investigated. First, motion capture systems were used to collect motion data from amputees. Furthermore, marker and force plate data were obtained to create a digital human model. Kinematic data such as limb lengths and joint angles were calculated using marker data. Afterward, the inertial properties were estimated to conduct inverse dynamic analyses. After building a computational model of amputee sprinting, the joint positions and ground reaction forces (GRFs) were compared with the experimental results. The design parameters of the prosthesis were introduced to understand the effects of the prosthesis on motion and performance. The response surface method was used to express motion adaption regarding the geometry and stiffness of the prosthesis. Hip and knee sagittal joint angles were updated based on the response surface method to simulate joint motion adaptations of the worn prosthesis. Additionally, average horizontal velocity, horizontal velocity change over one gait cycle, vertical and horizontal impulses were considered as performance functions. An evaluation parameter was proposed to generalize the idea of performance. The moment of the prosthetic knee and the closest point of the prosthesis to the ground during the swing phase were defined as design constraints to consider knee buckling and prosthetic leg tripping, respectively. The effect of the design parameters on the performance and constraint functions was also investigated and a method to determine and design a suitable prosthesis for an individual was proposed. It was revealed that proper selection and design of prostheses represent an important way to increase performance.

Flying insects perform active flight control with flapping wings by continuously adjusting their wing kinematics in stabilizing the body posture to stay aloft under complex natural environment. While the Proportional Derivative (PD) / Proportional Integral Derivative (PID)-based algorithms have been applied to examine specific single degree of freedom (DoF) and/or 3 DoF flight control associated with insect flights, a full 6 DoF flight control strategy remains yet poorly studied. Here we propose a novel 6 DoF PD controller specified for flight stabilization in flapping flights, in which proportional and derivative gains are optimized to facilitate a fast while precise flight control by combing Laplace transformation and root locus method. The vertical position, yaw, pitch and roll are directly stabilized by tuning the wing kinematics while the forward/backward position and lateral position are indirectly stabilized by controlling the pitch and roll, respectively. Coupled with a recently developed flight dynamic model informed by high-fidelity CFD simulation (Cai et al. 2021), this methodology is proven to be effective as a versatile and efficient tool to achieve fast flight stabilization under both small and large perturbations for bumblebee hovering. The 6 DoF PD flight control strategy proposed may provide a useful bioinspired flight-controller design for flapping-wing micro air vehicles (FWMAVs).

This paper discussed if a powered attendant propelled wheelchairs (PAPW) with assist-as-needed control reduces energy consumption and maximise attendant's physical activity in powered system use. This study introduced a PAPW with force velocity assist control (FVAC) based on individual capability of pushing force velocity relationship. This PAPW assists attendant pushing when more pushing force is needed over usual range of individual physical capabilities of pushing. With the PAPW, we investigated the performance of the FVAC and compared it with proportional assist control (PAC) on a flat level surface and a longitudinal slope (6.5%) with three participants. The experimental results showed that the PAPW with the FVAC reduced 50% of pushing force on the slope and this was similar performance of the PAC in terms of assisting. The FVAC also reduced 79% of mean mechanical assisting power on the flat against the PAC. These results support that the PAPW with the FVAC has flexibilities to adapt to individual physical capabilities and provides certain level of physical activities with sufficient assisting when needed, and low energy consumption for long time and distance operations for attendants.

Various effects have been observed when a slimy fluid is held in palmar skin. The observed effects include friction control of the skin and cleansing and moisturizing of the skin. However, few reports exist regarding the changes in the emotional state of persons when a slimy fluid is held in their palmar skin, even though the viscosity properties of the fluid affect emotional changes. Thus, this study investigates the emotional changes due to holding slimy fluid in the palmar skin by evaluating heart rate variability (HRV) and sensibility. Newtonian and non-Newtonian fluids, with viscosities ranging from 0.01 to 100 Pa·s, were prepared. Eight male subjects in their 20s soaked their palms in the slimy fluid without seeing it. At the room temperature of 25 °C, the subjects moved their palms freely for 1 min. They were allowed to rub their palms together. During the experiments, the HRV was recorded. A frequency analysis was performed for estimating autonomic nerve activity. After holding the fluid, the subjects were asked to provide feedback through the semantic differential method. Significant changes in autonomic nerve activations were observed when the subjects soaked their palms in the slimy fluid. The high viscosity Newtonian fluid reduced the parasympathetic nervous system activity. These changes in the psychophysiological indexes influenced the feelings of the subjects ascertained according to the semantic differential method. A relationship between the characteristic of the slimy fluid and a psychophysiological index can improve the efficiency when developing products exposed to human skin.