Masaaki Makikawa

Joint motion monitoring by accelerometers set at both near sides around the joint

In this paper we examined a joint motion monitoring method utilizing accelerometers to monitor upper limb motion in daily activities. In this method two accelerometers are set at both near sides around the joint. The difference of these sensor outputs depends on the joint angle because centrifugal and turning acceleration occurring in the rotation around the joint can be neglected. We confirmed the validity of this method in the measurement of elbow and shoulder motion.

ECG monitoring of a car driver using capacitively-coupled electrodes

Many reports show that there are a lot of traffic accidents due to sleeping while driving. Then, demand for measuring electrocardiogram (ECG) to estimate drowsiness of drivers has increased to prevent these accidents. In this paper, we propose an ECG monitoring system of a car driver using capacitively-coupled electrode. This capacitively-coupled electrode on which an operational amplifier (OP amp) was mounted was embedded inside a seat for measuring ECG signal. A ground electrode was placed on a steering wheel, i.e. ECG signal was amplified by a single-ended amplifier. Subjects wore their regular suits and pants made of wool, and ECG was obtained during driving at low speed on a rough road with one corner. Results show that our system can be used to obtain ECG while driving at low speed except some motion artifacts caused by the steering operation, road surface, braking, and accelerating.

Development of an ambulatory physical activity and behavior map monitoring system

To know where a subject is, what he does and how his physiological function responds in daily life, the authors have developed an ambulatory physical activity and behavior map monitoring system, which is a kind of portable microprocessor-based computer. Here the authors used two piezoresistive-type accelerometers to measure a subjects posture change and physical activities, and a GPS (Global Positioning System) sensor to get the subjects behavior map. This accelerometer can output the DC component of the acceleration change and by putting this sensor in front of the subjects waist, his posture change can be detected. This sensor also responds to the subjects action, and the authors tried to categorize this acceleration data for the subjects individual actions, like walking, getting on a vehicle and so on. The GPS sensor uses the information sent from space satellites orbiting the Earth, but some positioning error is embedded in this information for military purposes. The authors adopted the DGPS method to obtain more precisely the subjects location.

Electrocardiogram Measurement during Sleep with Wearing Clothes Using Capacitively-Coupled Electrodes

The electrocardiogram (ECG) was measured by non-contact, non-restraint and unconscious method using capacitively-coupled electrodes made of electro-conductive cloth while subjects lay on bed wearing their clothes. These electrodes are very sensitive so measure not only signals but noise. The seat grounded, which arranged under the electrode could suppress noise. Two types of electrode different in length were used, that is long type and short type. Results showed that both electrodes could sense ECG. Noise generated from e.g. commercial power source was almost the same for both electrodes though the length of electrode was longer than the subject for the long type electrode. Setting position was rather serious and noise component changed greatly by the part of body that touches the electrode. Next, ECG was measured on these condition participants lay with supine position, prone position, right lateral position and left lateral position. The ECG was measured on each condition.

Cuff Actuator for Adaptive Holding Condition around Nerves

A nerve stimulation technology is expected in the biomedical field. Above all, a functional electrical stimulation is studied in order to recover paralyzed functions. We have proposed a new nerve stimulation strategy and reported successful results. It is indispensable to guarantee a reliable contact between nerves and a stimulator for the nerve stimulation. Most of the conventional stimulators, however, were passive structures, and hence it was not easy to obtain the desired contact. This paper presents a cuff actuator that allows an adaptive contact between nerves and the stimulator in order to solve the above problem. A trial towards an implantable device is also presented.

Flexible Fabric Sensor Toward a Humanoid Robot's Skin: Fabrication, Characterization, and Perceptions

We have developed a fabric sensor knitted of tension-sensitive electro-conductive yarns. Each yarn has an elastic core, around which is wound two other separate, tension-sensitive electro-conductive threads, making this sensor inherently flexible and stretchable and allowing it to conform to any complicated surface on a robot, acting as a robotic skin. The pile-shaped surface of the sensor enhances its ability to detect tangential traction, while also enabling it to sense a normal load. Our aim is to use this sensor in applications involving relative sliding between its surface and a touched object, such as contact recognition, slip detection, and surface identification through a sliding motion. We carefully analyzed the static and dynamic characteristics of this sensor while varying the load and stretching force to fully understand its response and determine its degree of flexibility and stretchability. We found that a discrete wavelet transformation may be used to indicate stick/slip states while the sensor is sliding over surfaces. This method was then used to detect slippage events acting on the sensors surface, and to decode textures in a classification test using an artificial neural network. Because of its flexibility and sensitivity, this sensor can be used widely as a robotic skin in humanoid robots.

Experimental investigation of surface identification ability of a low-profile fabric tactile sensor

Humans usually distinguish objects by sliding their fingertips on the surface to feel the texture via mechanoreceptor underneath the skin. We have developed a human-imitated system for robotic fingertip to sense objects texture via sliding action. Design of the sensory skin was inspired by the localized displacement phenomenon of a sliding soft fingertip ([1]) to capture stick-slip events on the contact surface that mainly represent texture characteristics. The soft skin is knitted by electro-conductive tension-sensitive yarns, then covered over a hemispherical fingertip. The pile-shaped surface of the fabric sensor enhances tangential traction detection ability of the sensor, even though the normal load is also sensible. Our aim is to exploit this sensor in applications regarding relative sliding between the touched object and the surface of the sensor, such as slip detection ([2]), and surface identification in this paper. In surface encoding, we have experimentally investigated ability of the fabric sensor in recognition touched objects via multiple machine learning algorithms, such as naive Bayes, Multi-Layer Artificial Neural Network (ANN) with input extracted from autoregressive models, and ANN with input extracted from Discrete Wavelet Transformation (DWT), have been trained to distinguish three typical textures. As a result, we have found that the last method outperforms the remains with an average successful rate of 90%.

Development of a Portable Acceleration Monitor Device and its clinical application for the Quantitative Gait Assessment of the Elderly

In this study, a handy gait assessment system with a tri-axial accelerometer has been developed and its application for a quantitative assessment of gait in the elderly was examined. This assessment system consists of a portable acceleration monitor device and PC analysis software. This portable device was fixed to the lower front of the subject, and the subject was asked to walk around a test course at a voluntary speed. The activities performed on the test course include standing up, normal walking, fast walking, and walking over a barrier. Gaits in 402 elderly people were measured three times every three months. These subjects were under nursing health services, such as expert place nursing, walking training, power rehabilitation, fall prevention training, and pool training. The measured acceleration was converted into relative velocity and relative displacement of the center of gravity of the subject. Four evaluation indices, i.e., physical activity, stability, symmetry, and average speed were calculated. The results reveal that both the physical activity and average speed decreased after six months under nursing services

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.

Reentrant excitation in an analog-digital hybrid circuit model of cardiac tissue

We propose an analog-digital hybrid circuit model of one-dimensional cardiac tissue with hardware implementation that allows us to perform real-time simulations of spatially conducting cardiac action potentials. Each active nodal compartment of the tissue model is designed using analog circuits and a dsPIC microcontroller, by which the time-dependent and time-independent nonlinear current-voltage relationships of six types of ion channel currents employed in the Luo-Rudy phase I (LR-I) model for a single mammalian cardiac ventricular cell can be reproduced quantitatively. Here, we perform real-time simulations of reentrant excitation conduction in a ring-shaped tissue model that includes eighty nodal compartments. In particular, we show that the hybrid tissue model can exhibit real-time dynamics for initiation of reentries induced by uni-directional block, as well as those for phase resetting that leads to annihilation of the reentry in response to impulsive current stimulations at appropriate nodes and timings. The dynamics of the hybrid model are comparable to those of a spatially distributed tissue model with LR-I compartments. Thus, it is conceivable that the hybrid model might be a useful tool for large scale simulations of cardiac tissue dynamics, as an alternative to numerical simulations, leading toward further understanding of the reentrant mechanisms.