Shima Okada

Development of a low-profile sensor using electro-conductive yarns in recognition of slippage

We have developed a slip sensor which is knitted by tension-sensitive electro-conductive yarns. When elongating this yarn, its resistance will drop remarkably. Because the yarn is mainly sensitive to deformation along its main axis, a special way to knit these yarns has been proposed to form a slip sensor. This sensor is used in detection of the human fingertips slip during rubbing action on its surface. We found that, a simple derivative of the sensors output was sufficient to detect slippage. However, in some cases, the sensor gets troublesome to distinguish between change of normal load and the occurrence of slip, since human implements their action without caring much about keeping the stable applied force on the sensor. Therefore, a well-known DWT (Discrete Wavelet Transform) method is employed to overcome this problem. As a result, depending on the purpose of the application, several data processing methods are employed to detect slippage of humans rubbing action, or robotic fingertip. Results in this paper promise an applicable sensory mean, which can be employed in haptic devices, teleoperation, or robotic skin.

Analysis of Difference in Center-of-Pressure Positions Between Experts and Novices During Asymmetric Lifting

Although numerous studies have analyzed the relationship between manual material handling (MMH) and the forces acting on the lumbar spine, the difference in the MMH between experts and novices through the analysis of measured data has not been well studied. The purpose of this paper was to analyze the difference in the MMH positions between ten skilled experts working at a freight transport company (Group 1) and five unskilled novices without any experience (Group 2) during asymmetric lifting. All the human subjects performed asymmetric lifting experiments with closed eyes; the experiments involved moving loads (6 and 18 kg) to the left side. Time series data of the vertical ground reaction force were measured, using a Wii Balance Board, and then, the center-of-pressure (CoP) trajectories were calculated. The balance board was used for the measurement, because it was reliable, inexpensive, and portable and provided good repeatability even on rough surfaces, and all the information pertaining to the load and worker under various conditions was captured without any omissions. Under the 18 kg load condition, the CoP positions for Group 2 were located on the same side during left asymmetric lifting; however, those for Group 1 were located on the opposite side during left asymmetric lifting (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}

Body movement analysis during sleep for children with ADHD using video image processing

P <0.001

Fundamentals of Wearable Sensors for the Monitoring of Physical and Physiological Changes in Daily Life

\end{document}). Furthermore, under the 6 kg load condition, the load weight influenced asymmetric lifting for most subjects of Group 2 such that the CoP positions were located on the opposite side (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}

Signal Source Estimation Inside Brain Using Switching Voltage Divider

P <0.001

Gait analysis of sit-to-walk motion by using portable acceleration monitor device for fall prevention

\end{document}). Based on the simulation and electromyography measurement results, we inferred that the difference in the CoP positions between the two different groups could be attributed to the difference in the hip positions. Most skilled experts position their hips in such a way that their CoP trajectories move toward the opposite side during left asymmetric lifting. Although the skillful characteristics of experts may be responsible for the lightening of the burden on the waist during asymmetric lifting, there are still two points that this paper does not clarify: the relationship between the experts’ adjustment of the hip position and the load of the weight, and the influence of an imbalance of the CoP position on the forces acting on the lumbar spine.

Comparison of Gross Body Movements during Sleep between Normally Developed Children and ADHD Children Using Video Images

In recent years, the amount of children with sleep disorders that cause arousal during sleep or light sleep is increasing. Attention-deficit hyperactivity disorder (ADHD) is a cause of this sleep disorder; children with ADHD have frequent body movement during sleep. Therefore, we investigated the body movement during sleep of children with and without ADHD using video imaging. We analysed large gross body movements (GM) that occur and obtained the GM rate and the rest duration. There were differences between the body movements of children with ADHD and normally developed children. The children with ADHD moved frequently, so their rest duration was shorter than that of the normally developed children. Additionally, the rate of gross body movement indicated a significant difference in REM sleep (p <; 0.05). In the future, we will develop a new device that can easily diagnose children with ADHD, using video image processing.

Electric motor assisted bicycle as an aerobic exercise machine

This chapter provides an overview of wearable sensors for the monitoring of physical and physiological change in daily life, their fundamentals, and applications. The following three cases need to be considered for the applications of a wearable biosignal measurement system: continuous and long-term measurement for accident prevention (e.g., an alarm for heart attack), once-daily measuring for the evaluation of health condition, and biosignal monitoring as the machine interface. In long-term monitoring, the biosignal measurement system must be small in size, with minimal power consumption, and portable. However, in the case of sleep monitoring, the biosignal sensors should not be wearable, but incorporated into a bed. This chapter presents several kinds of wearable and ambient sensors for the monitoring of physiological and physical changes in daytime and nighttime.

Classification of forearm and finger motions using electromyogram and arm-shape-changes

Visualization of neural activities inside the brain is useful for clarifying human brain function. Electroencephalogram (EEG) using a surface electrode is the most popular visualization method in laboratories, and estimation of the signal source using EEG has been extensively studied. Owing to the low spatial resolution of EEG, many surface electrodes are currently required for highly accurate estimates. In an attempt to improve the resolution, we developed a new EEG method in which the position information and potential of the signal source inside a human brain are obtained simultaneously from one signal electrode. A prototype device for proposed method has been developed, and experiments focused on EEG when the eyes were open and closed are conducted to validate our proposed method and device. Results show that the signal source position changes for the two conditions, and our method is plausible.

Measurement of swallowing using flexible polymer sensor

The purpose of this study is to investigate whether the acceleration of the center of gravity of body during sit-to-walk motion have a relationship with falling or not. In this study, we measured sit-to-walk motion of fall experienced and inexperienced subjects by using a portable acceleration monitor device that we have developed. The result of discriminant analysis by using indexes with a significant difference revealed a 90.3% correct prediction rate for falling. The results indicated possibility of fall prevention by this method.