Kazuki Nakajima

Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique

An apparatus for simultaneously monitoring heart and respiratory rates was developed using photoplethysmography (PPG) and digital filters, and compared with conventional methods. The PPG signal, which includes both heart and respiratory components, was measured at the earlobe with an original transmission mode photoplethysmographic device. A digital filtering technique was used to distinguish heart and respiratory signals from the PPG signal. The cut-off frequency of the respiratory signal filter was selected automatically depending on the heart rate. Using digital filtering techniques, heart and respiratory signals were separated at rest and during exercise. The digital signal processor was employed to realize an adaptive and real-time filtering. The heart rate was calculated by the zero-crossing method and the respiratory rate from the peak interval of the filtered signal. To evaluate the newly developed monitor, an ECG for heart rate and a transthoracic impedance plethysmogram for respiratory rate were monitored simultaneously. To obtain higher heart and respiratory rates, exercise was performed on an electrical bicycle ergometer. Heart and respiratory rates calculated by the new method compare to those obtained from ECG and the transthoracic impedance plethysmogram. The maximum error of heart and respiratory rates was 10 beats/min and 7 breaths/min, respectively.

Footprint-based personal recognition

Proposes a new method of personal recognition based on footprints. In this method, an input pair of raw footprints is normalized, both in direction and in position for robustness image-matching between the input pair of footprints and the pair of registered footprints. In addition to the Euclidean distance between them, the geometric information of the input footprint is used prior to the normalization, i.e., directional and positional information. In the experiment, the pressure distribution of the footprint was measured with a pressure-sensing mat. Ten volunteers contributed footprints for testing the proposed method. The recognition rate was 30.45% without any normalization (i.e., raw image), and 85.00% with the authors method.

Development of real-time image sequence analysis for evaluating posture change and respiratory rate of a subject in bed

An image sequence analysis technique was developed to evaluate posture change and respiratory rate of a subject in bed without any physical contact. Although the image sequence analysis requires many calculations, the system can perform them in real time. The system consisted of a CCD video camera and a PC equipped with a high-speed image processor. To evaluate the system, we tested it on five subjects at a nursing home. The system evaluated 99.4% of the movements of subjects during the total monitoring time (about 61 hours). The waveform was flat when the subject was out of view of the video camera. The system has the possibility of evaluating not only posture changes and respiratory rate. but also sleeping patterns.

An algorithm for the automatic detection of health conditions

In this article, an algorithm for a health diagnosis system for the elderly that uses image processing was developed. This algorithm reconstructs monochrome images from data of the time a subject watches TV and calculates the index for diagnosis of the subjects health condition from the entropy of the image. When this algorithm was applied to the data obtained for seven months, the result almost corresponded to the health condition of the subject. It is assumed that this method can be used not only for diagnosis of a physical condition but also for diagnosis of a mental condition. As a result of the evaluation, this algorithm is considered to be effective according to the subject. In addition, this method was economical because the algorithm needed only simple data acquired from simple sensors. In the future, an automatic diagnosis will be available using this algorithm. Finally, total medical expenses will be reduced if this system is practical.

Detection of Physiological Parameters without Any Physical Constraints in Bed Using Sequential Image Processing.

Physiological parameters, specifically, body movement and respiratory waveform, were observed utilizing an original image sequence processing system. In this study, sequential image processing methods were used to observe both patients with acute myocardial infarction and normal subjects in bed. The results of standard differential image processing and a gradient-based method were strongly correlated with body movement of the subject. Furthermore, the respiratory waveform was detected using the gradient-based method. This image sequence processing system appears very promising for the evaluation of physical activity without any physical constraints in bed.

A monitor for posture changes and respiration in bed using real time image sequence analysis

The authors developed a real time system of image sequence analysis to evaluate both a subjects posture changes and respiration in bed. The system consists of a CCD video camera (used as the sensor), an image processing board and a PC. An image processing board that includes 256 CPUs detects optical flow (apparent velocity) of 256/spl times/240 pixels within 150 ms. The representative field-averaged velocity shows a waveform including two components with large peaks and a periodic fluctuation. The large peaks occur during posture change, and the periodic fluctuation corresponds to that of respiration obtained with a nasal thermistor. The system was tested in a nursing home, where it worked for 56 hours in total without any trouble. The authors found two sleep apnea syndrome patients who had not been diagnosed before the test.

Evaluation of Body Motion by Optical Flow Analysis

For quantitative evaluation of body motion, a fully noncontact and unconstraining monitoring method was developed by introducing image sequence analysis. A spatiotemporal local optimization method was applied to determine optical flow in the image sequence. The optical flow visualized the apparent velocity field of the entire body motion, including both breast movement of respiration and posture changes in a bed. The experiment was carried out under regulated posture changes and under a sleeping condition by measuring heart rate, respiration and digitized image sequences using a video camera. A temporal increase in heart rate reflected the magnitude of physical activities. We proposed two candidate parameters for evaluation of respiratory and physical activities based on comparison among experimental results. The average of squared motion velocities reflected the magnitude of physical activities. The representative field-averaged component showed a waveform with periodic fluctuation corresponding to that of respiration obtained with a nasal thermistor.

Photoplethysmographic measurement of heart and respiratory rates using digital filters

A monitor. for simultaneous recording of heart and respiratory rates has been developed using photoplethysmography (PPG) and digital filters. PPG signal includes both heart and respiratory synchronous components. Digital filtering technique was employed to differentiate between those. With increasing heart and respiratory rates, the cut-off frequency o f filter was changed empirically. Obtained signals agreed with those obtained with ECG and thermistor. The digital filtering technique may provide on-line monitor for heart and respiratory rates.

A method for measuring respiration and physical activity in bed by optical flow analysis

A fully noncontact and unconstrained monitoring method, based on optical flow of movement of body surface that is developed by introducing image sequence analysis, is described. A spatiotemporal local optimization method is applied to determine optical flow in the image sequence. The optical flow visualizes the apparent velocity field of the entire body motion, including breast movement due to respiration and posture changes in a bed. A temporal increase in heart rate reflects the magnitude of physical activities. We propose two candidate parameters for evaluation of respiratory and physical activities based on comparison among experimental results. The average of squared motion velocities reflects the magnitude of physical activities. The representative field-averaged component shows a waveform with periodic fluctuation corresponding to that of respiration obtained with a nasal thermistor. This optical flow analysis is a promising new technique for evaluation of body motion for clinical use.

Relationship between resting cytosolic Ca2+ and responses induced byN-methyl-d-aspartate in hippocampal neurons

Cytosolic calcium concentrations ([Ca2+]i) in cultured hippocampal neurons from rat embryos were measured using fura-2. Neurons with higher resting [Ca2+]i showed greater [Ca2+]i responses to N-methyl-D-aspartate (NMDA) and K+ depolarization. There was a strong relationship between resting [Ca2+]i and the maximal changes in [Ca2+]i (delta[Ca2+]i), which fit the our proposed equation to describe this relationship.