Excellence in Research and Innovation for Humanity

T Kaburagi

Publications

3

Publications

3
10000181
Analysis of Brain Activities due to Differences in Running Shoe Properties
Abstract:

Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for 10 min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords:
Brain activities, NIRS, PASAT, running shoes.
2
10002019
Evaluation Using a Bidirectional Microphone as a Pressure Pulse Wave Meter
Abstract:
This paper describes a novel sensor device, a pressure pulse wave meter, which uses a bidirectional condenser microphone. The microphone work as a microphone as well as a sensor with high gain over a wide frequency range; they are also highly reliable and economic. Currently aging is becoming a serious social issue in Japan causing increased medical expenses in the country. Hence, it is important for elderly citizens to check health condition at home, and to care the health conditions through daily monitoring. Given this circumstances, we developed a novel pressure pulse wave meter based on a bidirectional condenser microphone: this device is used as a measuring instrument of health conditions.
Keywords:
Bidirectional microphone, pressure pulse wave meter, health condition.
1
10007797
Classification Method for Turnover While Sleeping Using Multi-Point Unconstrained Sensing Devices
Abstract:
Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.
Keywords:
Turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system.