Kouji Sada

A wireless breathing-training support system for kinesitherapy

We have developed a new wireless breathing-training support system for kinesitherapy. The system consists of an optical sensor, an accelerometer, a microcontroller, a Bluetooth module and a laptop computer. The optical sensor, which is attached to the patient’s chest, measures chest circumference. The low frequency components of circumference are mainly generated by breathing. The optical sensor outputs the circumference as serial digital data. The accelerometer measures the dynamic acceleration force produced by exercise, such as walking. The microcontroller sequentially samples this force. The acceleration force and chest circumference are sent sequentially via Bluetooth to a physical therapist’s laptop computer, which receives and stores the data. The computer simultaneously displays these data so that the physical therapist can monitor the patient’s breathing and acceleration waveforms and give instructions to the patient in real time during exercise. Moreover, the system enables a quantitative training evaluation and calculation the volume of air inspired and expired by the lungs.

Effects of clear visual input and change in standing sequence on standing sway related to falls during night toilet use.

AIM The aim of this study is to provide objective evidence that clear visual input and change in standing sequence can reduce fall risk related to night toilet use among hospitalized older patients. BACKGROUND In hospitalized older patients, falls are likely to occur during night toileting needs. METHOD Using a stabilometer, we measured and compared maximal standing sway for 10 seconds immediately after standing with three visual input modes in two standing patterns, comparing healthy younger adults (n=22) and older patients (n=19). The three modes are no visual input (mode 1), vague (mode 2), and clear visual input (mode 3). Standing sequences A and B are defined as supine-to-standing and supine-to-sitting-to-standing, respectively. RESULTS For a given visual mode, maximal moved distance was significantly greater for older patients than for younger adults with both standing patterns (P<0.0001). Both standing pattern B and clear visual input decreased maximal moved distance in younger adults and older patients. A greater maximal moved distance score indicated a greater fall risk. RELEVANCE TO CLINICAL PRACTICE It is important for nurses to train older patients to turn on the light and perform standing pattern B, when going to the bathroom at night. In addition, it is advisable to confirm the placement of distinct visual markers on the way to the bathroom.

A microcomputer-based life-safety monitoring system for elderly people

A new safety and life support system has been developed for monitoring health conditions and daily living activities of solitary elderly people. The system employs a piezoelectric sensor, two low-power active filters, a low-power 8-bit single chip microcomputer (SCM) and a 315 MHz radio transmitter. The body movements produced by respiration, heartbeat, sleep/rest motions, walking and running are detected by the piezoelectric sensor, and the recorded motion signals are inputted to the SMC. If the patient is inactive for 64 minutes, then the SMC detects this emergency situation and informs the patients family, a fire station or a hospital via telephone. The system is powered by a small 3V lithium battery, which provides 14 days of continuous operation.

Analysis of Diameter and Flow Velocity Changes in Small Pulmonary Vessels During Regional Alveolar Hypercapnia

Effects of alveolar hypercapnia on the pulmonary vessels have been studied chiefly by measuring the pressure-flow relationship [1–3]. Some of the results have suggested an increase in the vascular resistance to blood flow in the hypercapnic lung area [1, 2], whereas others have not [3]. However, we consider that for detecting the local pulmonary vasomotion during alveolar hypercapnia, it is necessary to measure directly the internal diameter (ID) of small pulmonary vessels with rich smooth muscle layers. In this study, using a new X-ray TV system developed in our laboratory [4], we quantitatively analyzed the changes in 10 of the small pulmonary arteries and veins (100–600 μm 10) in unilobar alveolar hypercapnia. Simultaneously, flow velocity and volume flow in the small arteries were analyzed.