Recently, technology to augment human body movements is being developed. Herein, we aimed to focus on technologies developed to assist joint movements and human’s interaction with it and discusses research issues that should be addressed via human factors and ergonomics. In addition, we have presented an overview of near-future issues related to human factors and ergonomics by foreseeing technological enhancements and expansion of the user numbers and application areas.
This study clarifies the effects of handling force magnitude and foot position on postural sway evoked by momentary loss of hand reaction force （MLRF）. In the experiment, 15 participants performed pushing tasks that varied the magnitude of the handling force when the MLRF occurred and the foot position. This study assumed that postural sway was represented by the position variation and velocity at the center of mass （COM） and that postural control factors were represented by the impulse of horizontal force difference, which integrated the difference between the horizontal components of ground and hand reaction forces, and the position variation at the center of pressure （COP）. Thus, in the experiment, we recorded these evaluation indexes and asked the participants about subjective ratings such as postural instability. By stepping forward during the pushing task, the position variations in COM and COP after MLRF decreased. The position variation in COM before MLRF, the impulse of horizontal force difference, and the subjective postural instability increased with the magnitude of the handling force. In conclusion, this study showed that in the pushing task with MLRF, the step forward suppressed the postural sway, and the increase in the handling force caused a greater postural sway.
Diagnosis and assessment of nail lesions require an understanding of normal anatomical structures and information on their size. However, accurate measurement of the toenail plate on the nail bed has not been reported. This study investigated the usefulness and validity of a method of drawing and measuring the toenail plate through the water-bath method using an ultrasound system. The ultrasound images of the gel and water-bath methods of participants without nail lesions were compared. The thickness of the toenail plate was measured over time in the water. In addition, the thickness, height, width, and nail height index of the toenail plate of participants in their 20s and 40＋ age groups were compared. The results showed that the water-bath method clearly depicted the toenail plate without artifacts. The thickness of the immersed toenail plate remained unchanged at 0 mm, and no significant difference was observed. Furthermore, significant differences were observed in the thickness, height, and nail height index of the toenail plate of participants in their 20s and 40＋ age groups. These results demonstrate that this method can clearly image the toenail structure, and measure and evaluate the toenail plate.
This study aimed to clarify the influence of match on action and background image on continuity during video transitions through subjective evaluation analysis. We created 3DCG videos as stimuli, with three factors employing two levels of shot composition （close to wide, wide to close）, two levels of the match on action （match, mismatch）, and two levels of the background image （present, absent）. Participants were presented with the stimuli and asked to rate on a 5-point scale whether they saw a continuous connection between the two shots. The results suggested that continuity evaluation was lower for the background condition, where it was difficult to perceive the space in the “close-up to wide shot” transition. Therefore, it is possible that understanding of the story in the video through background information is important to enhance subjective evaluation of continuity during transitions. Furthermore, videos where the motion matched regardless of the presence or absence of the background image had a greater effect in enhancing the continuity evaluation compared to videos in which the motion did not match. This effect was more pronounced when the shot composition was “wide to close”.
In this paper, we proposed person identification system based on gait pattern. As a preliminary study, classification was performed only on registered persons. The system uses the 2-dimention Light Imaging Detection and Ranging （LiDAR） to get gait feature. We use the LiDAR to measure the temporal change of distance between the LiDAR and body parts of a person walking towards below the LiDAR. The measured distance is drawn as a RGB color surface plot image showing the gait feature. Vertical and horizontal axes of the plot are time and angular direction viewed from the LiDAR respectively, and the distance is represented by color of the surface. We use deep learning approach to classify images. Convolutional Neural Network （CNN） is employed to predict person who passed below the LiDAR. We obtained 300 images per each of the 12 persons. Those 3,600 images were used for training of the CNN （2,400 images） and testing （1,200 images）. As results, our proposed identification system outperformed those 12 persons classified with accuracy of 0.89.