Measurement of electrocardiograms in a bath through tap water utilizing capacitive coupling electrodes placed outside the bathtub wall.

BACKGROUND: Taking a bath sometimes poses a risk for subjects with chronic cardiopulmonary disorders, due to the thermal effect and water pressure on his/her body. The ECG measurement would be helpful for the early recognition of abnormal cardiac beats and respiratory conditions. This paper describes a new attempt to improve on previous bathtub ECG measurement techniques that had electrodes placed inside the bathtub that were intrusive to the subjects' bathing experience. This study is concerned with the initial development of a method to measure an electrocardiogram (ECG) through tap water without conscious awareness of the presence of electrodes that are placed outside the bathtub wall. METHODS: A configuration of capacitive coupling electrodes placed outside the bathtub was designed so that the electrodes could be hidden. The capacitive coupling was made from the electrodes to the water through the bathtub wall. Two electrodes with an active shielding amplifier covered further by an electromagnetic shield were fixed to the outside surface of the bathtub wall, near the bather's right scapula and left foot. The potential difference between these two electrodes, similar to the bipolar lead-II ECG, was amplified to obtain raw signals inclusive of ECG/QRS components. Respiration intervals were also derived from ECG/RR intervals. Comparison experiments between this bathtub method and conventional direct methods with spot-electrodes and a chest-band sensor were made using 10 healthy male volunteers (22.2 ± 0.98 years). RESULTS: The ECG signal was detectable through tap water as well as water with differing conductivity resulting from mixing bathwater additives with the water. ECG signals and respiration curves derived from ECG/RR intervals were successfully obtained in all subjects. The intervals of the ECG/RR and respiration obtained by the bathtub system and by the direct method were respectively agreed well with each other. CONCLUSION: The ECG signal, in particular ECG/QRS components, were successfully detected utilizing capacitive coupling electrodes placed outside the bathtub wall. Also, the ECG/RR and respiration intervals were determined with reasonable accuracy as compared with the conventional direct methods.

Measurement of three-dimensional posture and trajectory of lower body during standing long jumping utilizing body-mounted sensors.

The measurement method of three-dimensional posture and flying trajectory of lower body during jumping motion using body-mounted wireless inertial measurement units (WIMU) is introduced. The WIMU is composed of three-dimensional (3D) accelerometer and gyroscope of two kinds with different dynamic range and one 3D geomagnetic sensor to adapt to quick movement. Three WIMUs are mounted under the chest, right thigh and right shank. Thin film pressure sensors are connected to the shank WIMU and are installed under right heel and tiptoe to distinguish the state of the body motion between grounding and jumping. Initial and final postures of trunk, thigh and shank at standing-still are obtained using gravitational acceleration and geomagnetism. The posture of body is determined using the 3D direction of each segment updated by the numerical integration of angular velocity. Flying motion is detected from pressure sensors and 3D flying trajectory is derived by the double integration of trunk acceleration applying the 3D velocity of trunk at takeoff. Standing long jump experiments are performed and experimental results show that the joint angle and flying trajectory agree with the actual motion measured by the optical motion capture system.

Development of a network system combined with ambulatory and non-conscious physiological measurements for supporting challenged kids - a new proposal of a gait monitoring system for use in rehabilitation.

Various physiological measurement techniques have been developed to support healthcare and daily living of adult including elderly. However, in light of the rapid growth of the declining birth rate, promotion in care and life support for children are not enough. Especially in rehabilitation for disabled children, i.e., challenged kids, it is important for therapist to evaluate the efficacy of rehabilitation and the health condition. Share of these information with educational, welfare, and government institutions are also needed for accurate life support. Therefore, the quantitative data of the activities and daily health status are helpful. From these viewpoints, we are developing a new network system for monitoring the activities and the health status of children using ambulatory and non-conscious physiological measurements as well as data browse at anytime and anywhere. Firstly, we propose a wearable gait monitoring system to support evaluation for the efficacy of rehabilitation. In this study, the present system can successfully detect the characteristics of postural changes in children with disorder of movement, demonstrating its usefulness and availability to the evaluation for the effect of the brace attached to the subject's lower limb.

Development of a ubiquitous healthcare monitoring system combined with non-conscious and ambulatory physiological measurements and its application to medical care.

The demand for ubiquitous healthcare monitoring has been increasingly raised for prevention of lifestyle-related diseases, acute life support or chronic therapies for inpatients and/or outpatients having chronic disorder and home medical care. From these view points, we developed a non-conscious healthcare monitoring system without any attachment of biological sensors and operations of devices, and an ambulatory postural changes and activities monitoring system. Furthermore in this study, in order to investigate those applicability to the ubiquitous healthcare monitoring, we have developed a new healthcare monitoring system combined with the non-conscious and the ambulatory measurements developed by us. In patients with chronic cardiovascular disease or stroke, the daily health conditions such as pulse, respiration, activities and so on, could be continuously measured in the hospital, the rehabilitation room and subject's own home, using the present system. The results demonstrated that the system appears useful for the ubiquitous healthcare monitoring not only at medical facility, but also during daily living at home.

Attempt of a novel calibration method of pulse oximetry using support vector machines regression.

A novel calibration method using support vector machines regression (SVMsR) of pulse oximetry was proposed and attempted. Conventional calibration method of pulse oximetry that based on an optical density ratio of transmitted visible red light and infrared radiation whereas a proposed method here was not based on the optical density ratio directly. In theory, conventional calibrations using the ratio can be considered as a technique for nonlinear problem: nonlinear relation between two optical densities (red and IR) and oxygen saturation could be linearized by the ratio calculation. We thought, that nonlinear problem could be solved by using nonlinear analyses. Among them, the support vector machines regression method that has been studied well in this decade was attempted to be applied for pulse oximetry calibration. As an experiment, two photo plethysmograms (PPGs) by red and IR were measured on five subjects. Simultaneously, oxygen saturation (SpO(2)) level was measured by a commercial pulse oxymeter. SpO(2)) level was controlled by breathing 10% oxygen gas obtaining 98-75% SpO(2) level. Sequentially, feature points of two PPGs were extracted in beat by beat. Convex peaks and concave valleys on waveform and DC levels of PPGs were selected as feature points. Then, nonlinear regression using SVMs were attempted to obtain relationship between SpO2 by meter (regressand) and feature points of PPG (regressor). In result, a regression model was constructed from training data that is three fourths of measured cardiac data by using SVMsR. Finally, the constructed calibration model was evaluated by other one third data (validation data). The root mean squared error for the validation data is 1.90 [SpO(2)) level %] and 89% of validation data fell within +/- 2 % of SpO(2) level by the meter. In conclusion, SVMsR might be applicable on calibration for pulse oximetry.

A fully automated health-care monitoring at home without attachment of any biological sensors and its clinical evaluation.

Daily monitoring of health condition is important for an effective scheme for early diagnosis, treatment and prevention of lifestyle-related diseases such as adiposis, diabetes, cardiovascular diseases and other diseases. Commercially available devices for health care monitoring at home are cumbersome in terms of self-attachment of biological sensors and self-operation of the devices. From this viewpoint, we have been developing a non-conscious physiological monitor installed in a bath, a lavatory, and a bed for home health care and evaluated its measurement accuracy by simultaneous recordings of a biological sensors directly attached to the body surface. In order to investigate its applicability to health condition monitoring, we have further developed a new monitoring system which can automatically monitor and store the health condition data. In this study, by evaluation on 3 patients with cardiac infarct or sleep apnea syndrome, patients' health condition such as body and excretion weight in the toilet and apnea and hypopnea during sleeping were successfully monitored, indicating that the system appears useful for monitoring the health condition during daily living.

Feasibility study of a urine glucose level monitor for home healthcare using near infrared spectroscopy.

Urine glucose level monitoring technique using near infrared spectroscopy in conjunction with the chemometric method was newly developed aiming for the use of home health care. The calibration models were obtained by the partial least square method and their validity were assessed using albumin added glucose solution and urine samples. From the results obtained, it was clearly demonstrated that the present method had a capability of predicting urine glucose level with reasonable accuracy (standard error of prediction; 22.3 mg/dl, correlation coefficient; 0.99) and appeared to be a useful means for long-term home health care.