担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

This study describes a heart rate measurement method by considering the harmonics of a respiratory signal. Respiration and heart rates were measured by applying frequency analysis to the time-series data of body pressure. The harmonics of a respiratory signal serve as noises in heart rate measurement. Therefore, heart rate measurement was improved by eliminating the effects of the harmonics. The results of experiments demonstrated that our proposed method enhances the precision of heart rate measurement.

DOI： 10.5954/icarob.2021.gs2-1

CiNii Research

記述言語：英語   掲載種別：研究論文（学術雑誌）

Respiratory Inductance Plethysmography (RIP) is commonly used to detect the respiratory motions of chest and abdomen during sleep. However, this method is not suitable for daily use due to its strong constraints. Many unconstrained methods have been developed, but they have a common problem with distinguishing the chest and abdominal motions, which are required for understanding the type of sleep apnea. In this paper, we proposed an unconstrained method to distinguish chest and abdominal motions by measuring the pressure fluctuations from the chest and abdomen acting on a mattress. We then investigated the feasibility of detecting respiratory motions by using a flexible tactile sensor array, which was laid on a bed like a bed sheet. Ten healthy subjects (five males and five females) were tested and the results were compared with those measured by the RIP band sensors. It was confirmed that the sensor array could measure the motions of the chest and abdomen and obtain the respiratory rate at a high accuracy. However, the phase of the pressure fluctuations measured by the sensor array might disagree with the outputs of the RIP band sensors, depending on the gender and lying position of the subject. The reason was discussed with a dynamic model, which showed that the disagreement might have been related to the coupling of the chest and abdomen. In addition, the influence of the stiffness of the mattress on the pressure fluctuations was investigated. The results showed that mattress stiffness had little effect on the measurement.

DOI： 10.1109/JSEN.2019.2925022

Scopus

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担当区分：筆頭著者,　責任著者   記述言語：日本語   掲載種別：研究論文（学術雑誌）

<p>We describe a method for improving recognition of lying postures using a measured signal intensity of respiration and heartbeat. We have proposed a measurement method of lying posture, respiration, and heartbeat using a Smart Rubber sensor, a rubber-based flexible tactile sensor sheet developed by us. We can obtain respiration and heartbeat by means of using the time series data of the body pressure measured at the suitable location determined by lying posture in this measurement method. Therefore, a recognition rate of lying postures and a measured signal intensity of respiration and heartbeat have positive correlation. In the experiments, we show that recognition of lying postures is improved by means of using a measured signal intensity of respiration and heartbeat.</p>

DOI： 10.1299/transjsme.18-00175

CiNii Article

CiNii Research

その他リンク： https://ci.nii.ac.jp/naid/130007521454

記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2016 by ASME.The management of health through daily monitoring of respiration is of major importance for early diagnosis to prevent respiratory and circulatory diseases. Such daily health monitoring is possible only if the monitoring system is physically and psychologically noninvasive. However, current unconstrained measurement methods cannot distinguish chest and abdominal movements in diagnosing sleep apnea. In this study, a flexible and stretchable tactile sensor sheet was developed to measure the static body pressure of a subject who lies on it and measure the pressure fluctuations induced by respiration or respiratory efforts. The results were compared with the measurements by band sensors that are widely used for measuring chest and abdominal movements in clinic. It was demonstrated that the sensor sheet can distinguish chest and abdominal movements in a supine position. The reasons why the pressure fluctuations measured by the sensor sheet are antiphase with the outputs of band sensors are discussed using a simple dynamic model.

DOI： 10.1115/1.4034465

Scopus

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担当区分：筆頭著者,　責任著者   記述言語：日本語   掲載種別：研究論文（学術雑誌）

DOI： 10.1299/transjsme.14-00642

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1109/EMBC.2014.6943530

Scopus

記述言語：日本語   掲載種別：研究論文（学術雑誌）

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.2316/P.2014.818-031

Scopus

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.2316/P.2014.818-014

Scopus

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1109/ICRA.2012.6225329

Scopus

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1109/ICSENS.2010.5690034

Scopus

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1109/IROS.2010.5649899

Scopus

記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1109/TMECH.2009.2023647

Scopus

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：筆頭著者,　責任著者   記述言語：日本語   掲載種別：研究論文（学術雑誌）

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：最終著者   記述言語：日本語   掲載種別：研究論文（研究会，シンポジウム資料等）

<p>The number of people requiring nursing care is expected to increase significantly in the future. However, the number of nursing care workers is not keeping pace with this increase. If the sleep state of those requiring nursing care can be easily estimated, it will be effective in reducing the burden on nursing care workers. We have already developed a method to measure respiration, heartbeat, and body movement of a healthy subject using a flexible tactile sensor sheet by frequency analysis of measured body pressure time series data. In this study, we measured those pieces of biological information of hospitalized patients throughout a night. In addition, we confirmed that the measured biological information can be used to estimate the sleep state.</p>

DOI： 10.1299/jsmeiip.2023.iipb-4-1

CiNii Research

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

This paper examines the performance improvement via combining feature vectors for speaker verification. As feature vectors, we use LPC (linear predictive coding) spectral envelope (LPCSE), Mel-frequency cepstral coefficients (MFCC) and piecewise LPC (pLPC) pole distribution (pLPCPD). Here, pLPCPD is the feature which we have introduced and developed, and this paper shows a relationship of the underlying pLPC speech signal model for speaker verification with ARMA and AR models for speech production. We execute experiments of speaker verification with the combinations of the features. We examine the experimental results and show that (1) the smallest AER (average error rate) is achieved by MFCC followed in order by pLPCPD and LPCSE, (2) the AER achieved by LPCSE, MFCC and LPCSE+MFCC (combination of LPCSE and MFCC) is reduced by combining pLPCPD, (3) there are conflicting features in LPCSE, MFCC and pLPCPD to increase the AER, and the smallest AER is obtained by MFCC+pLPCPD among the combinations of LPCSE, MFCC and pLPCPD. We also investigate the relationship between pLPCPD and the aperiodicity used for vocal cord excitation in recent vocoders, which seems to explain the above result (2).

DOI： 10.1007/978-3-030-96308-8_20

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

This paper examines a method of speaker verification from mixture of speech and non-speech audio signals via using pole distribution of speech signals. The poles of speech signal derived from the all-pole speech production model are obtained via a neural net called bagging CAN2 (competitive associative net 2) for learning efficient piecewise linear approximation of nonlinear functions. We show an analysis that poles of the mixture of two audio signals are expected to show three typical phenomena. Namely, with the change of the weight of the mixture, there will be (1) a sudden change of the number of poles, (2) a gradual change of the number of poles, and (3) novel poles not in the original signals. By means of experiments, we show that there are poles exhibiting those phenomena, and they are considered to affect the performance on speaker verification. As a performance measure of speaker verification, recall shows large decrease with the change of speech signal from unmixed to mixed, especially for the mixture with violin signal as well as with speech signal. Furthermore, precision has larger value than recall for the same dataset of mixture of audio signals. Finally, we show the usefulness of the present method in further researches.

DOI： 10.1007/s12652-020-01716-6

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2020, Springer Nature Switzerland AG. Recently, we have presented several methods to select representative predictions of chaotic time series. Here, the methods employ strong learners capable of making predictions with small error, where usual ensemble mean does not work well owing to an ensemble member with short term predictable horizon because the ensemble prediction error of chaotic time series grows exponentially after the smallest predictable horizon of the ensemble member. Here, we refer to ‘predictable horizon’ as the first point in time after which the prediction error exceeds a certain error threshold. So far, we have developed several methods to select representative predictions from a set of many predictions by means of using a LOOCV (leave-one-out cross-validation) measure to estimate predictable horizon. From the analysis of the methods showing that the method works well with sufficiently large number of predictions generated by sufficiently strong learning machines, this paper presents a method to generate a large number of predictions and select a learning machine and a representative prediction using the entropy of LOO predictable horizons. By means of numerical experiments, we show and examine the effectiveness of the present method.

DOI： 10.1007/978-3-030-63823-8_88

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2020, Springer Nature Switzerland AG. So far, we have developed a multiobjective robust controller using GPC (generalized predictive controller) and CAN2s (competitive associative neural nets) to learn and approximate Jacobian matrices of nonlinear dynamics of the plant to be controlled. Here, the CAN2 is an artificial neural net for learning efficient piecewise linear approximation of nonlinear function. In our recent research study, we have clarified a significant property of the controller that it achieves the closed loop transfer function to have unstable poles for quick response during transient period and to have stable poles during steady state. Here, the controller for multiobjective control usually has conflicting multiple control objectives, such as reducing settling time and overshoot, and then the control strategy has to adjust weighted objectives. Thus, in this paper, we focus on Pareto optimal compromise solutions of the proposed controller, where the controller should achieve reasonable Pareto solutions for a wide range of weighted control objectives. By means of numerical experiments, we show that the controller can achieve a reasonable Pareto solutions by using integrated CAN2s consisting of two primitive CAN2s, each trained for one of the multiple objectives.

DOI： 10.1007/978-3-030-63823-8_81

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

So far, we have developed a multiobjective robust controller using GPC (generalized predictive controller) and CAN2s (competitive associative neural nets) to learn and approximate Jacobian matrices of nonlinear dynamics of the plant to be controlled. Here, the CAN2 is an artificial neural net for learning efficient piecewise linear approximation of nonlinear function. In our previous studies, we have shown that the controller is capable of coping with the change of plant parameter values as well as the change of control objective by means of switching CAN2s. This paper examines the stability of the controller by means of using a linear plant to be controlled, and show the properties and the effectiveness of the present method.

DOI： 10.1007/978-3-030-36802-9_39

Scopus

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2017 IEEE. This paper presents a method for grading fruits and vegetables by means of using RGB-D (RGB and depth) images and convolutional neural network (CNN). Here, we focus on grading according to the size of objects. First, the method transforms positions of pixels in RGB image so that the center of the object in 3D space is placed at the position equidistant from the focal point by means of using the corresponding depth image. Then, with the transformed RGB images involving equidistant objects, the method uses CNN for learning to classify the objects or fruits and vegetables in the images for grading according to the size, where the CNN is structured for achieving both size sensitivity for grading and shift invariance for reducing position error involved in images. By means of numerical experiments, we show the effectiveness and the analysis of the present method.

DOI： 10.1109/SSCI.2017.8285278

Scopus

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2017 IEEE. Recently, we have presented a method of ensemble prediction of chaotic time series. The method employs strong learners capable of making predictions with small error, where usual ensemble mean does not work well owing to the long term unpredictability of chaotic time series. Thus, we have developed a method to select a representative prediction from a set of plausible predictions by means of using LOOCV (leave-one-out cross-validation) measure to estimate predictable horizon. Although we have shown the effectiveness of the method, it sometimes fails to select the representative prediction with long predictable horizon. In order to cope with this problem, this paper presents a method to select multiple candidates of representative prediction by means of employing hierarchical K-means clustering with K = 2. From numerical experiments, we show the effectiveness of the method and an analysis of the property of LOOCV predictable horizon.

DOI： 10.1109/SSCI.2017.8285285

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer Nature Switzerland AG 2018. This paper presents a method of text-independent speaker verification from mixed speech of multiple speakers via using pole distribution of speech signals. The poles of speech signal derived from all-pole speech production model are obtained via a neural net called bagging CAN2 (competitive associative net 2) for learning efficient piecewise linear approximation of nonlinear function. We show an analysis that poles of mixed speech are expected to be composed of the poles farther from zeros of ARMA (autoregressive moving average) models of constituent speeches. By means of experiments using unmixed and mixed speeches, we show the distribution of the poles of speeches has two typical regions: one involves poles which change suddenly with the change of the speech from unmixed to mixed, and the other involves poles which change continuously with the change of the mixing weight, which is considered to support the analysis. We execute experiments of speaker verification, and obtain the following properties of recall and precision as measures of verification performance: the recall decreases suddenly with the change of the speech from unmixed to mixed, while the precision does not decreases so much with the decrease of SNR (signal to noise ratio) until below 0 dB. Finally, we show the usefulness of the present method.

DOI： 10.1007/978-3-030-04224-0_37

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer Nature Switzerland AG 2018. So far, we have presented several methods for chaotic time series prediction, and shown performance improvement on predictability horizon. However, we could not have shown the comparison of the performance with other methods. In order to obtain general and absolute performance measure of predictability horizon, this paper analyzes to formulate the relationship between the mean predictability horizon and the step size of the fourth-order Runge-Kutta method, or RK4. By means of using the formula which we have obtained in this article, the step size of RK4 corresponding to the mean predictability horizon achieved by a learning machine can be obtained without executing RK4. We execute numerical experiment of the prediction by several learning machines, and compare the performance by means of the step size of RK4 corresponding to the mean horizon achieved by the learning machines, and we show the effectiveness of the present method.

DOI： 10.1007/978-3-030-04224-0_2

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Recently, we have presented a method of probabilistic prediction of chaotic time series. The method employs learning machines involving strong learners capable of making predictions with desirably long predictable horizons, where, however, usual ensemble mean for making representative prediction is not effective when there are predictions with shorter predictable horizons. Thus, the method selects a representative prediction from the predictions generated by a number of learning machines involving strong learners as follows: first, it obtains plausible predictions holding large similarity of attractors with the training time series and then selects the representative prediction with the largest predictable horizon estimated via LOOCV (leave-one-out cross-validation). The method is also capable of providing average and/or safe estimation of predictable horizon of the representative prediction. We have used CAN2s (competitive associative nets) for learning piecewise linear approximation of nonlinear function as strong learners in our previous study, and this paper employs bagging (bootstrap aggregating) to improve the performance, which enables us to analyze the validity and the effectiveness of the method.

DOI： 10.1007/s00521-017-3149-7

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer International Publishing AG 2016.This paper analyzes entropy of occupancy grid map (OGM) for evaluating registration performance of SLAM (simultaneous localization and mapping) algorithms. So far, there are a number of SLAM algorithms having been proposed, but we do not have general measure to evaluate the registration performance of point clouds obtained by LRF (laser range finder) for SLAM algorithms. This paper analyzes to show that good registration seems corresponding to large overlap of point clouds in OGM as well as large entropy, large uncertainty and low information of OGM. This analysis indicates a method of entropy maximization of OGM for selecting good registration of SLAM algorithms. By means of executing numerical experiments, we show the validity and the effectiveness of the entropy of OGM to evaluate the registration performance.

DOI： 10.1007/978-3-319-46687-3_17

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer International Publishing AG 2016.This paper presents a method of speaker detection using probabilistic prediction for avoiding the tuning of thresholds to detect a speaker in an audio stream. We introduce g-GEBI (generalized GEBI) as a generalization of BI (Bayesian Inference) and GEBI (Gibbsdistribution- based Extended BI) to execute iterative detection of a speaker in audio stream uttered by more than one speaker. Then, we show a method of probabilistic prediction in multiclass classification to classify the results of speaker detection. By means of numerical experiments using recorded real speech data, we examine the properties and the effectiveness of the present method. Especially, we show that g-GEBI and g-BI (generalized BI) are more effective than the conventional BI and GEBI in incremental speaker detection task.

DOI： 10.1007/978-3-319-46681-1_37

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer International Publishing AG 2016.So far, we have presented a method of probabilistic prediction using GEBI (Gibbs-distribution based Bayesian inference) for flexible text-prompted speaker verification. For more flexible and practical verification, this paper presents a method of verification capable of accepting spoken words with the same meaning but different pronunciations. For example, Japanese language has different pronunciations for a digit, such as /yon/ and /shi/ for 4, /nana/ and /shichi/ for 7, which are usually uttered via unintentional selection, and then it is a practical problem in speech verification of words involving digits, such as ID numbers. With several assumptions, we present a modification of GEBI for dealing with such words. By means of numerical experiments using recorded real speech data, we examine the properties of the present method and show the validity and the effectiveness.

DOI： 10.1007/978-3-319-46681-1_38

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer International Publishing AG 2016.Recently, we have presented a method of ensemble prediction of chaotic time series. The method employs strong learners capable of making predictions with small error and usual ensemble mean does not work for long term prediction owing to the long term unpredictability of chaotic time series. Thus, the method uses similarity of attractors to select plausible predictions from original predictions generated by strong leaners, and then calculates LOOCV (leave-one-out crossvalidation) measure to estimate predictable horizons. Finally, it provides representative prediction and an estimation of the predictable horizon. We have used CAN2s (competitive associative nets) for learning piecewise linear approximation of nonlinear function as strong learners in the previous study, and this paper employs bagging of them to improve the performance, and shows the validity and the effectiveness of the method.

DOI： 10.1007/978-3-319-46681-1_70

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1007/978-3-319-26555-1_9

Scopus

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1007/978-3-319-26532-2_24

Scopus

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1007/978-3-642-39173-6_43

Scopus

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

DOI： 10.1109/ICIES.2012.6530874

Scopus

開催期間： 2013年05月   記述言語：日本語  

開催期間： 2012年12月   記述言語：英語  

開催期間： 2010年10月   記述言語：英語  

開催期間： 2010年06月   記述言語：日本語  

開催期間： 2009年10月   記述言語：英語  

開催期間： 2009年05月   記述言語：日本語  

開催期間： 2009年03月   記述言語：日本語  

開催期間： 2008年05月   記述言語：日本語  

開催期間： 2007年11月   記述言語：英語  

開催期間： 2007年09月   記述言語：日本語  

開催期間： 2006年09月   記述言語：日本語  

科目区分：学部専門科目