2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)最新文献

Automatic Diagnosis by Compact Portable Ultrasound Robot: State Estimation of Internal Organs with Steady-State Kalman Filter 小型便携式超声机器人的自动诊断:基于稳态卡尔曼滤波的内脏状态估计

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962758

Yudai Sasaki, Fumio Eura, Kento Kobayashi, Ryosuke Kondo, Kyohei Tomita, Yu Nishiyama, H. Tsukihara, Naoki Matsumoto, N. Koizumi

{"title":"Automatic Diagnosis by Compact Portable Ultrasound Robot: State Estimation of Internal Organs with Steady-State Kalman Filter","authors":"Yudai Sasaki, Fumio Eura, Kento Kobayashi, Ryosuke Kondo, Kyohei Tomita, Yu Nishiyama, H. Tsukihara, Naoki Matsumoto, N. Koizumi","doi":"10.1109/HI-POCT45284.2019.8962758","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962758","url":null,"abstract":"In recent years, research has been very active on the development of artificial intelligence, robot technology, and support for proper image acquisition in ultrasound diagnosis. A conventional problem using robot technology is that robots themselves are large and complicated mechanisms. If a robot is large, there is a restriction where it can be used; that is, a certain amount of space is necessary. In consideration of these constraints, in this research, we developed a compact medical robot holding an ultrasound probe that can easily perform at-home diagnosis that compensates for organ movement. When the robot automatically diagnoses organs, it is necessary to scan organs with the ultrasound probe over the same cross-section always aligned with the center of the organ. Based on the present research, in order to compensate for the movement of the phantom with movement of the ultrasound probe in the ultrasound images, the movement of the phantom in the ultrasound images is analyzed. As a method, Kalman filter model with linear Gaussian noise is applied to position observations obtained by template matching, and system noise and observation noise are estimated in object state estimation. We also constructed a steady-state Kalman filter with asymptotic stability using solutions from the Riccati equation. Furthermore, verification experiments were carried out with the model on dataset acquired in previous research, and the position and velocity of the phantom were analyzed.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124839674","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}

引用次数: 1

Prototyping and Initial Feasibility Study of Palpation Display Apparatus Using Granular Jamming 基于颗粒干扰的触诊显示装置原型设计及初步可行性研究

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962883

Sakura Sikander, Pradipta Biswas, Pankaj Kulkarni, Bradley Atwood, Sang-Eun Song

引用次数: 2

Smartphone-Based Method for Detecting Periodontal Disease 基于智能手机的牙周病检测方法

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962844

B. Askarian, F. Tabei, Grace Anne Tipton, J. Chong

引用次数: 4

Evaluation of synthetic setae pads for dry attachment of an ultrasound transducer 超声换能器干燥附着用合成刚毛垫的评价

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962885

J. LaRocco, Soohong Min, D. Paeng

{"title":"Evaluation of synthetic setae pads for dry attachment of an ultrasound transducer","authors":"J. LaRocco, Soohong Min, D. Paeng","doi":"10.1109/HI-POCT45284.2019.8962885","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962885","url":null,"abstract":"Medical ultrasound requires the coupling of skin with the transducer. Removing this requirement could make ultrasound stimulation and imaging more accessible and convenient. Synthetic setae pads are a biomimetic material that mimics the structure of a gecko’s foot, allowing it to hold substantial weight. By combining synthetic setae with an ultrasound transducer, the attenuation of existing commercial versions was measured using a 10 MHz ultrasound transducer. It was found that ShearGrip® attached to a smooth plastic surface (70.0% power loss) had notably less attenuation than to skin (86.5% power loss). The material was also examined by mounting it on the side of plastic tank, using a 5 MHz ultrasound transducer and hydrophone. In the case of the tank tests, the presence of moisture on the synthetic setae specimen was found to reduce attenuation by 0.29 dB. Otherwise, the attenuation could be 0.35 dB. However, this large attenuation was due to sample porosity and thickness, causing scattering and energy loss. Currently, work is underway to fully characterize the material. Potential improvements to the material’s acoustic conductance include uniform fiber alignment, reduced porosity, optimized thickness, and the use of lower frequency ultrasound stimulation.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123942290","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}

引用次数: 1

Colorimetric Point-of-Care Human Papillomavirus Diagnostic Reader 比色点护理人乳头瘤病毒诊断阅读器

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962666

R. Flores, Sahra Afshari, J. Christen

引用次数: 2

Novel Keratoconus Detection Method Using Smartphone 新型智能手机圆锥角膜检测方法

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962648

B. Askarian, F. Tabei, Grace Anne Tipton, J. Chong

引用次数: 5

Improved Classification of Malaria Parasite Stages with Support Vector Machine Using Combined Color and Texture Features 结合颜色和纹理特征的支持向量机改进疟疾寄生虫分期分类

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962686

Md. Khayrul Bashar

{"title":"Improved Classification of Malaria Parasite Stages with Support Vector Machine Using Combined Color and Texture Features","authors":"Md. Khayrul Bashar","doi":"10.1109/HI-POCT45284.2019.8962686","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962686","url":null,"abstract":"Malarial is a mosquito born deadly disease that quickly grows from person to person because of the infectious mosquito bite. Knowing accurately the developing stages of a parasite is critical for accurate drag selection for early recovery. However, limited study were found that dealt with the automated classification of malaria parasite stages. In this study, a supervised method for classifying malaria parasite stages from microscopy images has been proposed. To achieve the target, this method combines color and texture features with the support vector machine (SVM) classifier. Three texture features, namely histogram of oriented pattern (HOG), local binary pattern (LBP), Grey-level Co-occurrence Matrix (GLCM), and four color features, namely local color moments (StatMom) and color histograms (HSV, LAB, and YCrCb), have been considered. An experimental analysis with an unbalanced dataset of 46,978 single-cell thin blood smear images showed promising performances of the color features compared to the texture features. Using SVM classifier, the proposed color-texture feature (YCrCb_HOG) showed the highest classification accuracy (96.9%) on average, which exceeds the performance of a recently published method using HOG_LBP feature with the SVM (87.1%).","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128724720","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}

引用次数: 4

HI-POCT 2019 Welcome Message HI-POCT 2019欢迎辞

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/hi-poct45284.2019.8962638

引用次数: 0

Emotion Recognition by Point Process Characterization of Heartbeat Dynamics 基于心跳动态点过程特征的情绪识别

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962886

A. S. Ravindran, Sho Nakagome, D. S. Wickramasuriya, J. Contreras-Vidal, R. Faghih

{"title":"Emotion Recognition by Point Process Characterization of Heartbeat Dynamics","authors":"A. S. Ravindran, Sho Nakagome, D. S. Wickramasuriya, J. Contreras-Vidal, R. Faghih","doi":"10.1109/HI-POCT45284.2019.8962886","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962886","url":null,"abstract":"Recognizing human emotion from heartbeat information alone is a challenging but ongoing research area. Here, we utilize a point process model to characterize heartbeat dynamics and use it to extract instantaneous heart rate variability (HRV) features. These features are then fed into a convolutional neural network (CNN) to characterize different emotional states from small windows. On average, we achieved over 60% classification accuracy and as high as 77% in some subjects. This is comparable to other studies that use a combination of physiological signals as opposed to only HRV measures as done here. Informative features were identified for the different affective states. These findings enable the possibility of augmenting electrocardiogram or photoplethysmogram monitoring wearable devices with automated human emotion recognition capabilities for mental health applications. They also allow for the use of instantaneous estimation of HRV features to be used in combination with models that use other types of physiological signals for instantaneous emotion recognition.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121348885","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}

引用次数: 10

HI-POCT 2019 TOC

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/hi-poct45284.2019.8962628

引用次数: 0