Curling irons can create curled hair by heating it. However, because the operation of the curling iron involves six degrees of freedom (6DoF) movements, such as translation and rotation, it is difficult to understand and reproduce by simply watching instructional videos. In this study, we proposed Color-Path, a smart mirror-shaped system that allows users to easily understand how to move a curling iron. The proposed system acquires the moving paths of the curling iron using a camera on a smart mirror and an accelerometer on the curling iron. The system displays the curling iron paths of the target hairstyle on a smart mirror in Augmented Reality (AR). From the evaluation experiments, we confirmed that the system contributed to the reproduction of the moving paths of the curling iron through quantitative evaluation. However, a subjective evaluation showed that our system could not reproduce the appearance of the target hairstyle. The results indicate that the time to heat the hair should be considered.

This research aims to build a system that estimates assessment expressions to others by machine learning, collects them in real time, and feeds them back to the participants, and this study proposes two techniques that are necessary for this purpose. First, we propose a method to estimate the evaluative behavior to others, which is simplified to positive, negative, and neutral, from the facial images and head acceleration of participants in the conversation. The supervised machine learning algorithm requires ground-truth labeling. To analyze the expression of a large number of people, such as in a classroom, ground-truth labeling becomes a challenge in analysis and system construction. Second, to ease the labeling process we propose and implement a method to recommend the estimated labels on the labeling software. The accuracy of the proposed method is approximately 0.45 in F-value. Considering the time-series information, the proposed method recognizes major changes in positive evaluation behaviors. Presenting recommended labels on our labeling support system increase with time for the ground-truth labeling. However, the accuracy of labeling positive assessments improve in five out of six subjects.

Field hockey is a popular global sport played with a stick and hard ball, in which stick manipulation is difficult. In field hockey, a push pass is the most basic and common pass to teammates. For the best push pass, the stick should stay in contact with the ball for a long time until it is released for the pass. However, it is difficult for beginners to perceive the contact point of the stick by themselves. This study proposed a system to enable the user hear the movement path of the contact position of the ball on the stick to improve the push pass technique. In the proposed system, eight pressure sensors are placed on a hockey stick. The system detects the contact path of the ball, and feedback sounds with different pitches depending on the contact positions of the piezoelectric speaker are produced in real time. According to the evaluation experiment conducted over a period of two months, the average distance of the movement path of the ball on the stick was significantly longer when the auditory feedback was provided than when it was not given. This confirms the effectiveness of auditory feedback utilizing the proposed system.

We propose DeskWalk, which is an exercise system that replaces key inputs with body movements. Prolonged sitting significantly compromises health. Previous studies have shown that walking and standing during sedentary work can reduce the negative effects of prolonged sitting. However, these movements interrupt the work of the user. DeskWalk allows a user to exercise during his/her work. It recognizes the body movements using stretch sensors attached to the lower limbs and replaces them with preassigned key inputs. In preliminary experiments, we determined three target movements that involved muscle activities equivalent to walking. The average F-value of the motion recognition rate was 0.99. We implemented a system to measure steps using a smartphone and to perform exercises similar to the walking motion with DeskWalk.

In sports, automatic judgments made by electronic devices such as sensors are more accurate than those made by humans. However, automatic judgments are not always satisfactory to players and audiences. In sports that involve ambiguous judging criteria based on the subjectivity of human judges, rigorous automatic judgments may decrease the satisfaction of players and audiences. This decrease hinders the installation of automatic judging, even though computerized officiating is more effective than human judgment in several ways. In this study, we aim to construct an automatic judgment system that satisfies both players and audiences. To investigate the factors that affect the conviction of players and audiences, we implemented an automatic judgment system used for the Japanese statues game. Our system recognizes human motion using an acceleration sensor and automatically judges whether the players are moving. We conducted a user study to compare two threshold patterns for the recognition of the motion.

This paper proposes an auditory feedback system for adjusting the foot pressure balance of runners equally between the left and right feet. A wireless shoe system that measures foot plantar pressure in real time was proposed, and two types of auditory feedback mechanisms were provided and evaluated: 1) "Footstep" with a constant 440-Hz sound presented at the time of contact and 2) "Pitch change" that adaptively changes the sound to 880 Hz for the foot when a higher foot load is detected. The results of the user studies did not show a significant change in foot pressure difference with the proposed technique. The influence of the two auditory feedbacks on foot pressure was different for each subject; however, we confirmed the change of foot pressure balance by the change of sound.