Kazuya Imaizumi

Analysis of foot pressure distribution data for the evaluation of foot arch type

In order to develop an evaluation system for foot arch type in the elderly using foot pressure distribution data, foot pressure distribution parameters were selected and the data thereby derived were discussed. Results from the study show that the midfoot area and pressure ratios were correlated to foot arch type determined by visual analysis and were not correlated to arch height parameters. It is assumed that foot pressure distribution parameters reflect a different phenomenon from that of arch height parameters. The inconsistency between them is considered to be a result of the effect of the forefoot arch on the arch height parameters.

Effect of foot load changes on foot arch evaluation using foot pressure distribution data

Background The foot arch serves important functions in regard to shock absorption and the action of walking. Simple and quantitative classification of foot arch types such as flat foot and high arch would be helpful in health support for the elderly. The present authors have developed a classification system for foot arch type showing high reliability using foot pressure distribution data [1,2]. However, effect of foot load changes on foot arch evaluation remains unclear. The aim of this study was to investigate the effect of foot load changes on foot arch evaluation using foot pressure distribution data.

Development of an evaluation system for foot arch types in the elderly using foot pressure distribution data

The foot arch serves important functions related to shock absorption and the action of walking. Simple and quantitative classifications of foot arch types, such as flat feet and high arches, help to provide health support services for the elderly. To develop an evaluation system for foot arch types using foot pressure distribution data, discriminant analyses were conducted using data from healthy elderly persons. The midfoot pressure ratio was selected and discriminants were derived. For evaluating the performance of the classification method, the derived discriminants were applied to the data from the other group of healthy elderly persons. Results indicate that both sensitivity and specificity of the classified foot arch types were sufficiently high.

Health Promotion Community Support for Vitality and Empathy: Visualize Quality of Motion (QoM)

Nowadays approximately 30 % of the population is suffering from lifestyle-related diseases in Japan. Both individuals and the government are becoming more and more health-conscious and are taking various measures to improve personal health and to prevent lifestyle-related diseases. Among all the measures, improving trunk stability has been given special attention as it is vital for improving physical strength, preventing injury, and extending healthy life span. Many traditional trunk strength evaluation methods were designed to assess core muscle mass. Less emphasis, if any, was given to the stability of the trunk, which could be represented by the smoothness of trunk movement. In this paper, we proposed a new trunk torsion model for the purpose of evaluating two trunk torsion standard movements. We also developed a mobile application named “Axis Visualizer” based on the proposed trunk torsion model, which gives higher score to users who rotate the shoulders or hips smoothly with axis fixed and high frequencies. This application can support trainers and coaches to visualize the smoothness of trunk movement and to increase training outcome, as well as support health promotion community to easily evaluate the effectiveness of group exercise.

Axis Visualizer: Enjoy Core Torsion and Be Healthy for Health Promotion Community Support

In Japan, the ratio of people with lifestyle-related diseases has increased to approximately 30%. Individuals as well as the Nation are getting more and more health-conscious, and special attention has been made to body trunk because it is vital for injury prevention, physical strength, and beauty. Various training methods have been proposed to increase the muscle mass of body trunk. However, for sports that emphasize somatoform such as dance, the strength of the trunk is mainly decided by smooth use of the trunk rather than its muscle mass. In this paper, in order to evaluate the use of the trunk torsion movement, we proposed a new trunk torsion model for the purpose of evaluating two trunk torsion standard movements. We also developed a mobile application named “Axis Visualizer” based on the proposed trunk torsion model analyzing sensor data in the device. Axis Visualizer generates higher score when a user rotates the shoulders or hips smoothly with axis fixed and high frequencies. This application can support trainers and coaches to visualize the use of customers’ trunk and to increase the training effect.

Effect of Exercise Intervention and Foot Load Changes on Foot Arch Evaluation Using Foot Pressure Distribution Data

The foot arch serves important functions in regard to shock absorption and the action of walking. Simple and quantitative classification of foot arch types such as flat foot and high arch would be helpful in health support for the elderly. The present authors have developed a classification system for foot arch type showing high reliability using foot pressure distribution data. However, effect of exercise intervention and foot load changes on foot arch evaluation using foot pressure distribution data remain unclear. The aim of this study was to investigate the effect of exercise intervention and foot load changes on foot arch evaluation using foot pressure distribution data.

Description of movement of the upper extremities based on anatomical structure model (with special regard to signing gesture)

In the sign gesture, various hand shapes move in a space in front of signers upper body, at the same time, change by the side of palm and direction of the top of palm, according to the movements of the arms. In this study, the upper extremity movements used in sign gesture were described by modeling the anatomical structure of the arm movements, and combining the rotation of shoulder, elbow, forearm and wrist joints. Using this model, the range of rotation of each joint involved in the upper extremities was extracted from the video recording of sign gesture, and based on the result, a descriptive system for the upper extremity movement was proposed. It was also shown that, among the possible range of rotation of the upper extremity joints, the range with lesser dynamic work required is used in actual sign gestures.