Yuki Suzuki, M. Hori, S. Kido, Y. Otake, Mariko Ono, N. Tomiyama, Yoshinobu Sato
Segmenting blood vessels is an important step in a wide variety of tasks in medical image analysis. Patch-based convolutional neural networks (CNNs) are often used for vascular detection, but the impact of patch size and choice of CNN architecture have not been addressed in detail in previous studies. In this study, we aim to investigate the impact of patch size and CNN architecture on the accuracy of vascular detection from contract enhanced computed tomography (CT). We targeted the renal arteries as the primary focus of detection. We conducted experiments using contrast enhanced abdominal CT data of 30 cases. For the experiments, arteries in pre-de ned regions of interest were manually labeled to build a dataset of input CT images and ground truth labels. We repeated the experiments with four patch sizes and two patch-based 3D CNN architectures (U-Net-like model and a simple sequential model) and evaluated the differences. Moreover, a Hessian-based line enhancing method was included in the evaluation to compare this non-deep learning method with the CNNs. The experimental results showed that patch size had a signi cant impact on detection accuracy. U-Netlike model showed peak accuracy at a certain patch size, unlike the sequential model that plateaued at large patch sizes. Although both CNNs outperformed Hessian-based line enhancement by a large margin, Hessianbased line enhancement achieved good recall when enhancing vessel structures not included in the CNN training. Our experiments show that different network architectures have different characteristics regarding their response to various patch sizes and vessel structures unseen during training.
{"title":"Comparative Study of Vessel Detection Methods for Contrast Enhanced Computed Tomography: Effects of Convolutional Neural Network Architecture and Patch Size","authors":"Yuki Suzuki, M. Hori, S. Kido, Y. Otake, Mariko Ono, N. Tomiyama, Yoshinobu Sato","doi":"10.14326/abe.10.138","DOIUrl":"https://doi.org/10.14326/abe.10.138","url":null,"abstract":"Segmenting blood vessels is an important step in a wide variety of tasks in medical image analysis. Patch-based convolutional neural networks (CNNs) are often used for vascular detection, but the impact of patch size and choice of CNN architecture have not been addressed in detail in previous studies. In this study, we aim to investigate the impact of patch size and CNN architecture on the accuracy of vascular detection from contract enhanced computed tomography (CT). We targeted the renal arteries as the primary focus of detection. We conducted experiments using contrast enhanced abdominal CT data of 30 cases. For the experiments, arteries in pre-de ned regions of interest were manually labeled to build a dataset of input CT images and ground truth labels. We repeated the experiments with four patch sizes and two patch-based 3D CNN architectures (U-Net-like model and a simple sequential model) and evaluated the differences. Moreover, a Hessian-based line enhancing method was included in the evaluation to compare this non-deep learning method with the CNNs. The experimental results showed that patch size had a signi cant impact on detection accuracy. U-Netlike model showed peak accuracy at a certain patch size, unlike the sequential model that plateaued at large patch sizes. Although both CNNs outperformed Hessian-based line enhancement by a large margin, Hessianbased line enhancement achieved good recall when enhancing vessel structures not included in the CNN training. Our experiments show that different network architectures have different characteristics regarding their response to various patch sizes and vessel structures unseen during training.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66998059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ryutaro Kasedo, A. Iijima, K. Nakahara, Yusuke Adachi, I. Hasegawa
The rhythm of vocalizing a written language depends on a merge process that combines meaningless linguistic units into a meaningful lexical unit, word, or Bunsetsu in Japanese. However, in most previous studies, written language was presented to the participants in lexical units (word-by-word) with explicit in-ter-word (or inter-Bunsetsu) marks or spacing. Therefore, it has been difficult to conduct psychophysical assessment of the participants ʼ own speed in segmenting meaningful units from unstructured written language when reading. Here, we hypothesized that the spontaneous reading speed of Japanese readers reflects their own punctuation process, even when sentences are written without punctuation marks or spaces. To test this hypoth-esis, we developed a new “ self-paced sequential letterstring reading task, ” which visually presents sentences letter-by-letter. The task required participants to push a button to proceed to the next letter at their own pace, hence allowing evaluation of the reaction time (RT) to individual letters. We found that the average RT decreased parametrically as the position of the letter approached the end of a Bunsetsu. Moreover, the RT increased drastically at the last letter completing the Bunsetsu. Participants were not shown any punctuation marks and not instructed to explicitly recognize the punctuations during reading. Therefore, these effects strongly suggest that the implicit and spontaneous punctuation is the origin of the rhythm in reading. These results show that spontaneous punctuation of letterstring affects the reading speed. The task we have developed is a promising tool for revealing the temporal dynamics of natural reading, which opens a way to shape the fluency of script-to-speech human interfaces.
{"title":"Development of a Self-paced Sequential Letterstring Reading Task to Capture the Temporal Dynamics of Reading a Natural Language","authors":"Ryutaro Kasedo, A. Iijima, K. Nakahara, Yusuke Adachi, I. Hasegawa","doi":"10.14326/ABE.10.26","DOIUrl":"https://doi.org/10.14326/ABE.10.26","url":null,"abstract":"The rhythm of vocalizing a written language depends on a merge process that combines meaningless linguistic units into a meaningful lexical unit, word, or Bunsetsu in Japanese. However, in most previous studies, written language was presented to the participants in lexical units (word-by-word) with explicit in-ter-word (or inter-Bunsetsu) marks or spacing. Therefore, it has been difficult to conduct psychophysical assessment of the participants ʼ own speed in segmenting meaningful units from unstructured written language when reading. Here, we hypothesized that the spontaneous reading speed of Japanese readers reflects their own punctuation process, even when sentences are written without punctuation marks or spaces. To test this hypoth-esis, we developed a new “ self-paced sequential letterstring reading task, ” which visually presents sentences letter-by-letter. The task required participants to push a button to proceed to the next letter at their own pace, hence allowing evaluation of the reaction time (RT) to individual letters. We found that the average RT decreased parametrically as the position of the letter approached the end of a Bunsetsu. Moreover, the RT increased drastically at the last letter completing the Bunsetsu. Participants were not shown any punctuation marks and not instructed to explicitly recognize the punctuations during reading. Therefore, these effects strongly suggest that the implicit and spontaneous punctuation is the origin of the rhythm in reading. These results show that spontaneous punctuation of letterstring affects the reading speed. The task we have developed is a promising tool for revealing the temporal dynamics of natural reading, which opens a way to shape the fluency of script-to-speech human interfaces.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"14 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66997806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shun Hinatsu, Daisuke Suzuki, H. Ishizuka, Sei Ikeda, O. Oshiro
Several kinds of biometric authentications have been used as countermeasures against identity spoofing. Recently, some approaches have utilized time-series biosignals for biometrics, and one of the approaches is photoplethysmogram (PPG)-based authentication. PPG sensing has the advantage of fewer restric-tion of measurement sites than other time-series physiological signals. Moreover, it can connect the authentication and the healthcare applications seamlessly with one sensor. However, identity spoofing against PPG-based authentication may occur by exploiting this advantage. To develop a PPG-based authentication system with countermeasures, we propose the feasibility of a presentation attack against PPG-based authentication. The attack stealthily records PPGs on non-genuine measurement sites, and transmits the signals to the authentication device, thereby utilizing the advantage of PPG sensing in which signals can be recorded on various sites of a subject ʼ s body. We conducted an experiment to investigate the feasibility of the attack. We developed a PPG-based authentication system comprising a PPG sensing system including PPG sensors for multiple measurement sites, and an authentication algorithm based on an existing PPG-based identification algorithm. We recorded PPGs on three measurement sites on the subjects ʼ bodies using the developed system. Then, we investigated the feasibility of the attack by inputting the feature values extracted from the PPGs recorded on non-genuine measurement sites to the classifier generated by the values from the PPGs recorded on genuine measurement sites. The results indicate that the attack can occur within a short time without any mapping under an ideal condition. Therefore, countermeasures such as liveness detection and utilization of unique information of measurement sites are required against the attack. implemented PPG-based authentication. The values are extracted from each PPG segment.
{"title":"Basic Study on Presentation Attacks against Biometric Authentication using Photoplethysmogram","authors":"Shun Hinatsu, Daisuke Suzuki, H. Ishizuka, Sei Ikeda, O. Oshiro","doi":"10.14326/abe.10.101","DOIUrl":"https://doi.org/10.14326/abe.10.101","url":null,"abstract":"Several kinds of biometric authentications have been used as countermeasures against identity spoofing. Recently, some approaches have utilized time-series biosignals for biometrics, and one of the approaches is photoplethysmogram (PPG)-based authentication. PPG sensing has the advantage of fewer restric-tion of measurement sites than other time-series physiological signals. Moreover, it can connect the authentication and the healthcare applications seamlessly with one sensor. However, identity spoofing against PPG-based authentication may occur by exploiting this advantage. To develop a PPG-based authentication system with countermeasures, we propose the feasibility of a presentation attack against PPG-based authentication. The attack stealthily records PPGs on non-genuine measurement sites, and transmits the signals to the authentication device, thereby utilizing the advantage of PPG sensing in which signals can be recorded on various sites of a subject ʼ s body. We conducted an experiment to investigate the feasibility of the attack. We developed a PPG-based authentication system comprising a PPG sensing system including PPG sensors for multiple measurement sites, and an authentication algorithm based on an existing PPG-based identification algorithm. We recorded PPGs on three measurement sites on the subjects ʼ bodies using the developed system. Then, we investigated the feasibility of the attack by inputting the feature values extracted from the PPGs recorded on non-genuine measurement sites to the classifier generated by the values from the PPGs recorded on genuine measurement sites. The results indicate that the attack can occur within a short time without any mapping under an ideal condition. Therefore, countermeasures such as liveness detection and utilization of unique information of measurement sites are required against the attack. implemented PPG-based authentication. The values are extracted from each PPG segment.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66997837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To facilitate capturing the characteristic variations of blood pressure (BP) such as BP surges during the nocturnal period, the in-bed continuous daily measurement of BP may be useful. In this study, we proposed and evaluated a method for cuffless continuous estimation of relative mean arterial pressure (MAP) using capacitive ballistocardiogram (cBCG) and electrocardiogram (cECG) measured using an unrestrained and noncontact method. We adapted a well-known equation for calculating MAP, which is equal to the product of cardiac output and peripheral vascular resistance. We then derived an estimation formula for the relative MAP using the J–K amplitude from the cBCG, heart rate from the cECG, and pulse beat arrival time calculated from the cBCG and cECG. To determine the coefficients for the estimation formula, we measured the MAP of a subject with a commercial device and used the least squares method. To obtain input data for the estimation formula, the cBCG from the heel of the right leg and cECG from the back of the subject were measured simultaneously with capacitively coupled electrodes placed under a bed sheet. The total length of the input data was 80 s for each Valsalva test (VT), and the Valsalva maneuver was used to increase BP during measurement. The data for each VT was separated into a training segment (Tr) and a test segment (Te). To evaluate the proposed estimation method, the following indices were calculated for each VT in 7 subjects: (1) correlation coefficient (CC) between estimated and reference MAP values, (2) confidence interval (CI), and (3) root mean square error (RMSE). For the Tr, average CC was 0.93 ± 0.06, average CI was 2.96 ± 1.29 mmHg, and average RMSE was 0.75 ± 0.33 mmHg. Furthermore, average RMSE for the Te was 2.49 ± 2.22 mmHg. These results indicate that the continuous cuffless method proposed in this study can be used for estimating relative MAP over a short time period. As the subjects in this study were all men in their early twenties, further validation in diverse subjects is required for broad application of the proposed method.
{"title":"Cuffless Continuous Estimation of Relative Mean Arterial Pressure Using Unrestrained and Noncontact Ballistocardiogram and Electrocardiogram: Evaluation in Short Time In-bed Experiments","authors":"Masaki Arai, T. Takeuchi, A. Ueno","doi":"10.14326/ABE.10.36","DOIUrl":"https://doi.org/10.14326/ABE.10.36","url":null,"abstract":"To facilitate capturing the characteristic variations of blood pressure (BP) such as BP surges during the nocturnal period, the in-bed continuous daily measurement of BP may be useful. In this study, we proposed and evaluated a method for cuffless continuous estimation of relative mean arterial pressure (MAP) using capacitive ballistocardiogram (cBCG) and electrocardiogram (cECG) measured using an unrestrained and noncontact method. We adapted a well-known equation for calculating MAP, which is equal to the product of cardiac output and peripheral vascular resistance. We then derived an estimation formula for the relative MAP using the J–K amplitude from the cBCG, heart rate from the cECG, and pulse beat arrival time calculated from the cBCG and cECG. To determine the coefficients for the estimation formula, we measured the MAP of a subject with a commercial device and used the least squares method. To obtain input data for the estimation formula, the cBCG from the heel of the right leg and cECG from the back of the subject were measured simultaneously with capacitively coupled electrodes placed under a bed sheet. The total length of the input data was 80 s for each Valsalva test (VT), and the Valsalva maneuver was used to increase BP during measurement. The data for each VT was separated into a training segment (Tr) and a test segment (Te). To evaluate the proposed estimation method, the following indices were calculated for each VT in 7 subjects: (1) correlation coefficient (CC) between estimated and reference MAP values, (2) confidence interval (CI), and (3) root mean square error (RMSE). For the Tr, average CC was 0.93 ± 0.06, average CI was 2.96 ± 1.29 mmHg, and average RMSE was 0.75 ± 0.33 mmHg. Furthermore, average RMSE for the Te was 2.49 ± 2.22 mmHg. These results indicate that the continuous cuffless method proposed in this study can be used for estimating relative MAP over a short time period. As the subjects in this study were all men in their early twenties, further validation in diverse subjects is required for broad application of the proposed method.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66998220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Takashi Ijiri, Shogo Tsuruoka, Hiryu Kamoshita, A. Hirabayashi, S. Inada, I. Shiraishi, K. Kurosaki, K. Nakazawa
Segmentation of computed tomography (CT) images has provided promising methods of constructing precise 3-dimensional heart models. However, the process is labor intensive, because heart regions such as cardiac chambers and blood vessels have similar intensities and exist within a small space. In this paper, we present a tool to ef ciently segment cardiac chambers and blood vessels. We extend traditional region growing to be spatially controllable. A user places multiple seeds, each having a bounding area and a threshold, and our tool “grows” regions around each seed independently within its bounding area. To ef ciently specify the bounding area, we propose two types of seeds (i.e., sphere and cylinder). We also provide a negative seed that generates xed background to avoid over-extraction errors. We compared our tool with a traditional scissor tool and con rmed that ours signi cantly reduced the time required for a segmentation task. We also present segmentation results of CT images of hearts having congenital diseases to illustrate the feasibility of our tool.
{"title":"Spatially Controllable Region Growing for Segmenting Heart Chambers","authors":"Takashi Ijiri, Shogo Tsuruoka, Hiryu Kamoshita, A. Hirabayashi, S. Inada, I. Shiraishi, K. Kurosaki, K. Nakazawa","doi":"10.14326/abe.9.172","DOIUrl":"https://doi.org/10.14326/abe.9.172","url":null,"abstract":"Segmentation of computed tomography (CT) images has provided promising methods of constructing precise 3-dimensional heart models. However, the process is labor intensive, because heart regions such as cardiac chambers and blood vessels have similar intensities and exist within a small space. In this paper, we present a tool to ef ciently segment cardiac chambers and blood vessels. We extend traditional region growing to be spatially controllable. A user places multiple seeds, each having a bounding area and a threshold, and our tool “grows” regions around each seed independently within its bounding area. To ef ciently specify the bounding area, we propose two types of seeds (i.e., sphere and cylinder). We also provide a negative seed that generates xed background to avoid over-extraction errors. We compared our tool with a traditional scissor tool and con rmed that ours signi cantly reduced the time required for a segmentation task. We also present segmentation results of CT images of hearts having congenital diseases to illustrate the feasibility of our tool.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"9 1","pages":"172-180"},"PeriodicalIF":1.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67007292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information technology has been applied to health management. In our laboratory, we have developed and produced prototypes of new sensors, and attempted to monitor various health parameters noninvasive-ly and unobtrusively. This paper reviews the results of our research related to sensor development. The contents include unobtrusive monitoring in the bed, bath and toilet, and smart house. Then wearable sensors used for photoplethysmography, inertia sensor, deep body temperature measurement, and oxygen uptake monitor are presented. Finally, the requirement of regulatory science is commented
{"title":"Progress of Home Healthcare Sensor in Our Experience: Development of Wearable and Unobtrusive Monitoring","authors":"T. Tamura","doi":"10.14326/abe.9.189","DOIUrl":"https://doi.org/10.14326/abe.9.189","url":null,"abstract":"Information technology has been applied to health management. In our laboratory, we have developed and produced prototypes of new sensors, and attempted to monitor various health parameters noninvasive-ly and unobtrusively. This paper reviews the results of our research related to sensor development. The contents include unobtrusive monitoring in the bed, bath and toilet, and smart house. Then wearable sensors used for photoplethysmography, inertia sensor, deep body temperature measurement, and oxygen uptake monitor are presented. Finally, the requirement of regulatory science is commented","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67007404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Being overweight is one of several causes of balance impairment, and it increases the risk of falls. Balance assessments help diagnose this impairment. The outcomes from these assessments are not usually clear to investigate balance impairment in overweight adults. Several methods such as mathematical modeling can be used to investigate the postural control mechanisms in normal balance function. However, there is no study that is focused on the postural control mechanisms in overweight adults. This study aimed to de ne the postural control models underlying the application of the arti cial neural network (ANN) systems in normal weight and overweight populations. Ten participants were recruited and separated into two groups: normal weight (NW) and overweight (OW). There were two processes for determining the postural model in both groups. First, the optimal orders of the nonlinear autoregressive moving average (NARMA) model and the hidden nodes of the ANN system were identi ed. Mean square error (MSE), Akaike’s information criteria (AIC) and residual variance (RV) were used to identify these variables for both groups. Second, the coef cients of these models were de ned by the learned weights in the ANN system. The MSE, percent coef cient of variation (%CV), Kolmogorov-Smirnov (KS) test and maximal distance of cumulative distribution function (CDF) were de ned to evaluate the performance of the postural models. Furthermore, the orders of the NARMA model and relative importance were utilized to distinguish the postural control mechanisms between the two groups. During the training process, our results indicated that low MSE, AIC and RV were the criteria for hidden nodes and order selection in the NARMA model, which resulted in different patterns of postural models in each group. In the case of the testing process, the ndings revealed that the proposed technique could present different postural control strategies for each group. The ndings indicated that the postural control mechanism of NW subjects relied on the center of pressure (CoP) in the anterior-posterior (AP) direction, while body sway in the medio-lateral (ML) direction was vital to maintain equilibrium in the OW subjects. Accordingly, the proposed technique could be used to investigate the difference in postural control mechanism between the two groups.
{"title":"Determination of Postural Control Mechanism in Overweight Adults Using The Artificial Neural Networks System and Nonlinear Autoregressive Moving Average Model","authors":"T. Prasertsakul, W. Charoensuk","doi":"10.14326/abe.9.154","DOIUrl":"https://doi.org/10.14326/abe.9.154","url":null,"abstract":"Being overweight is one of several causes of balance impairment, and it increases the risk of falls. Balance assessments help diagnose this impairment. The outcomes from these assessments are not usually clear to investigate balance impairment in overweight adults. Several methods such as mathematical modeling can be used to investigate the postural control mechanisms in normal balance function. However, there is no study that is focused on the postural control mechanisms in overweight adults. This study aimed to de ne the postural control models underlying the application of the arti cial neural network (ANN) systems in normal weight and overweight populations. Ten participants were recruited and separated into two groups: normal weight (NW) and overweight (OW). There were two processes for determining the postural model in both groups. First, the optimal orders of the nonlinear autoregressive moving average (NARMA) model and the hidden nodes of the ANN system were identi ed. Mean square error (MSE), Akaike’s information criteria (AIC) and residual variance (RV) were used to identify these variables for both groups. Second, the coef cients of these models were de ned by the learned weights in the ANN system. The MSE, percent coef cient of variation (%CV), Kolmogorov-Smirnov (KS) test and maximal distance of cumulative distribution function (CDF) were de ned to evaluate the performance of the postural models. Furthermore, the orders of the NARMA model and relative importance were utilized to distinguish the postural control mechanisms between the two groups. During the training process, our results indicated that low MSE, AIC and RV were the criteria for hidden nodes and order selection in the NARMA model, which resulted in different patterns of postural models in each group. In the case of the testing process, the ndings revealed that the proposed technique could present different postural control strategies for each group. The ndings indicated that the postural control mechanism of NW subjects relied on the center of pressure (CoP) in the anterior-posterior (AP) direction, while body sway in the medio-lateral (ML) direction was vital to maintain equilibrium in the OW subjects. Accordingly, the proposed technique could be used to investigate the difference in postural control mechanism between the two groups.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67007224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Sonoda, K. Sasagawa, K. Fujisaki, T. Moriwaki, H. Kayaba
Accurate and trouble-free blood collection reduces the physical and mental risk of patients. Visualization of expert venipuncture techniques is important when conducting blood collection training. Fine motions such as needle insertion for venipuncture should be evaluated by measuring both finger motion and haptic sense. This paper proposes a method for evaluating the needle insertion process in blood collection. Blood collection technique of expert medical staff was measured and analyzed experimentally. A winged blood collection needle was inserted into a forearm model used for venipuncture training. A motion capture system was used to detect finger motions during needle insertion. Furthermore, haptic measurements were made by applying a thin and flexible sensor at the contact interface of the grip to measure both contact pressure and shear stress. The haptic sensor measured contact pressure at the fingers while holding a winged needle, and detected changes in stress components along the directions of needle insertion and skin compression during the venipuncture process. During needle insertion, characteristic changes in stress profiles were observed along with the process of puncturing the component layers of the forearm model. The blood collection procedure could be visualized using haptic sensing throughout the experiment. The proposed haptic sensing system may be useful in enhancing blood collection technique and developing automation of the process.
{"title":"Evaluation of Venipuncture Techniques Based on Measurements of Haptic Sense and Finger Motion","authors":"M. Sonoda, K. Sasagawa, K. Fujisaki, T. Moriwaki, H. Kayaba","doi":"10.14326/abe.9.197","DOIUrl":"https://doi.org/10.14326/abe.9.197","url":null,"abstract":"Accurate and trouble-free blood collection reduces the physical and mental risk of patients. Visualization of expert venipuncture techniques is important when conducting blood collection training. Fine motions such as needle insertion for venipuncture should be evaluated by measuring both finger motion and haptic sense. This paper proposes a method for evaluating the needle insertion process in blood collection. Blood collection technique of expert medical staff was measured and analyzed experimentally. A winged blood collection needle was inserted into a forearm model used for venipuncture training. A motion capture system was used to detect finger motions during needle insertion. Furthermore, haptic measurements were made by applying a thin and flexible sensor at the contact interface of the grip to measure both contact pressure and shear stress. The haptic sensor measured contact pressure at the fingers while holding a winged needle, and detected changes in stress components along the directions of needle insertion and skin compression during the venipuncture process. During needle insertion, characteristic changes in stress profiles were observed along with the process of puncturing the component layers of the forearm model. The blood collection procedure could be visualized using haptic sensing throughout the experiment. The proposed haptic sensing system may be useful in enhancing blood collection technique and developing automation of the process.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67007437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Yamashita, Tomoko Yamashita, Mitsuru Sato, Masahiro Inoue, Yoshimasa Takase
AKASE** Abstract Chronic diseases such as diabetes, hypertension, and hyperlipidemia increase the medical costs for middle-aged and elderly people, thus requiring preventive intervention. Monitoring, maintaining, or increasing the number of steps walked per day could be expected to effectively reduce medical costs. We evaluated the medical costs for chronic diseases after the implementation of a step count monitoring system with an information communication technology that we hypothesized would efficiently decrease medical costs. We enrolled 342 subjects in the intervention group. An additional 1,025 subjects were selected as controls by matching with the intervention group for age, gender, and total medical costs accumulated in the year prior to the study. The subjects in the intervention group were provided with pedometers that were used with reading de-vices stationed throughout the city. The duration of the intervention was 18 months. The subjects were given health points based on their activity performance improvements such as the number of steps they walked. The medical costs for the 18 months before and afer the intervention were compared. The effect of cost reduction was evaluated by comparing the percent increase in medical cost from before to after intervention between the control group and the intervention group. After the intervention period, the medical costs increased in the control group but not in the intervention group. The step counts for the first three months and the last three months of the intervention period were assessed, and the results showed that an average step count of 8000 steps was maintained throughout the intervention period. Assuming that the control group showed a natural increase in medical costs, the results suggest that the natural increase in medical costs was suppressed in the intervention group during the intervention period as a result of using the pedometer technology and health points. Therefore, we found that encouraging the participants to proactively participate in walking was an effective
{"title":"The Effects of an 18-Month Walking Habit Intervention on Reducing the Medical Costs of Diabetes, Hypertension, and Hyperlipidemia—A Prospective Study","authors":"K. Yamashita, Tomoko Yamashita, Mitsuru Sato, Masahiro Inoue, Yoshimasa Takase","doi":"10.14326/abe.9.117","DOIUrl":"https://doi.org/10.14326/abe.9.117","url":null,"abstract":"AKASE** Abstract Chronic diseases such as diabetes, hypertension, and hyperlipidemia increase the medical costs for middle-aged and elderly people, thus requiring preventive intervention. Monitoring, maintaining, or increasing the number of steps walked per day could be expected to effectively reduce medical costs. We evaluated the medical costs for chronic diseases after the implementation of a step count monitoring system with an information communication technology that we hypothesized would efficiently decrease medical costs. We enrolled 342 subjects in the intervention group. An additional 1,025 subjects were selected as controls by matching with the intervention group for age, gender, and total medical costs accumulated in the year prior to the study. The subjects in the intervention group were provided with pedometers that were used with reading de-vices stationed throughout the city. The duration of the intervention was 18 months. The subjects were given health points based on their activity performance improvements such as the number of steps they walked. The medical costs for the 18 months before and afer the intervention were compared. The effect of cost reduction was evaluated by comparing the percent increase in medical cost from before to after intervention between the control group and the intervention group. After the intervention period, the medical costs increased in the control group but not in the intervention group. The step counts for the first three months and the last three months of the intervention period were assessed, and the results showed that an average step count of 8000 steps was maintained throughout the intervention period. Assuming that the control group showed a natural increase in medical costs, the results suggest that the natural increase in medical costs was suppressed in the intervention group during the intervention period as a result of using the pedometer technology and health points. Therefore, we found that encouraging the participants to proactively participate in walking was an effective","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67006868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lumbar loading causes increased intervertebral pressure and is an important factor in low back pain. However, it is difficult to quantitatively judge the actions that affect lumbar load and the magnitude of lumbar load increase. Low back pain occurs not only in the workplace but also during activities of daily living. Therefore, it is necessary to investigate the factors inducing low back pain by measuring movements in various planes and determining the magnitude of the lumbar load. Accordingly, the lumbar spine should be examined during various movements. Several studies have examined vertebral bodies in the anteflexion posture. Howev-er, the relationship between body flexion angle and vertebral body angle during lateral flexion and rotation re-mains unknown. In this study, we proposed an estimation method for changes in vertebral body angle during lateral flexion and rotation in the lumbosacral region using a wearable sensor system we previously developed. The accuracy of the proposed estimation method was evaluated and demonstrated using X-ray images.
{"title":"Relationship between Upper Body Posture Angle and Vertebral Body Posture Angle in Lateral Flexion and Rotation Posture","authors":"Yoshio Tsuchiya, Takayuki Tanaka, Tamotsu Kamishima","doi":"10.14326/abe.9.181","DOIUrl":"https://doi.org/10.14326/abe.9.181","url":null,"abstract":"Lumbar loading causes increased intervertebral pressure and is an important factor in low back pain. However, it is difficult to quantitatively judge the actions that affect lumbar load and the magnitude of lumbar load increase. Low back pain occurs not only in the workplace but also during activities of daily living. Therefore, it is necessary to investigate the factors inducing low back pain by measuring movements in various planes and determining the magnitude of the lumbar load. Accordingly, the lumbar spine should be examined during various movements. Several studies have examined vertebral bodies in the anteflexion posture. Howev-er, the relationship between body flexion angle and vertebral body angle during lateral flexion and rotation re-mains unknown. In this study, we proposed an estimation method for changes in vertebral body angle during lateral flexion and rotation in the lumbosacral region using a wearable sensor system we previously developed. The accuracy of the proposed estimation method was evaluated and demonstrated using X-ray images.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67007347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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