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An Approach for Human Posture Recognition Based on the Fusion PSE-CNN-BiGRU Model
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作者 Xianghong Cao Xinyu Wang +2 位作者 Xin Geng Donghui Wu Houru An 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期385-408,共24页
This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit(PSECNN-BiGRU)fusion model for human posture recognition to address low accuracy issues in abnormal posture recognit... This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit(PSECNN-BiGRU)fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home environments.Firstly,the deep convolutional network is integrated with the Mediapipe framework to extract high-precision,multi-dimensional information from the key points of the human skeleton,thereby obtaining a human posture feature set.Thereafter,a double-layer BiGRU algorithm is utilized to extract multi-layer,bidirectional temporal features from the human posture feature set,and a CNN network with an exponential linear unit(ELU)activation function is adopted to perform deep convolution of the feature map to extract the spatial feature of the human posture.Furthermore,a squeeze and excitation networks(SENet)module is introduced to adaptively learn the importance weights of each channel,enhancing the network’s focus on important features.Finally,comparative experiments are performed on available datasets,including the public human activity recognition using smartphone dataset(UCIHAR),the public human activity recognition 70 plus dataset(HAR70PLUS),and the independently developed home abnormal behavior recognition dataset(HABRD)created by the authors’team.The results show that the average accuracy of the proposed PSE-CNN-BiGRU fusion model for human posture recognition is 99.56%,89.42%,and 98.90%,respectively,which are 5.24%,5.83%,and 3.19%higher than the average accuracy of the five models proposed in the comparative literature,including CNN,GRU,and others.The F1-score for abnormal posture recognition reaches 98.84%(heartache),97.18%(fall),99.6%(bellyache),and 98.27%(climbing)on the self-builtHABRDdataset,thus verifying the effectiveness,generalization,and robustness of the proposed model in enhancing human posture recognition. 展开更多
关键词 posture recognition mediapipe BiGRU CNN ELU ATTENTION
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Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model
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作者 Awais Khan Chomyong Kim +2 位作者 Jung-Yeon Kim Ahsan Aziz Yunyoung Nam 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第8期1729-1755,共27页
Sleep posture surveillance is crucial for patient comfort,yet current systems face difficulties in providing compre-hensive studies due to the obstruction caused by blankets.Precise posture assessment remains challeng... Sleep posture surveillance is crucial for patient comfort,yet current systems face difficulties in providing compre-hensive studies due to the obstruction caused by blankets.Precise posture assessment remains challenging because of the complex nature of the human body and variations in sleep patterns.Consequently,this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification,thereby enhancing the analysis of body position and comfort.This method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras,which depict six commonly adopted postures:supine,left log,right log,prone head,prone left,and prone right.The study involves 10 participants under two conditions:with and without blankets.Initially,the database is normalized into a video frame.The subsequent step entails training a fine-tuned,pretrained Visual Geometry Group(VGG16)and ResNet50 model.In the third phase,the extracted features are utilized for classification.The fourth step of the proposed approach employs a serial fusion technique based on the normal distribution to merge the vectors derived from both the RGB and thermal datasets.Finally,the fused vectors are passed to machine learning classifiers for final classification.The dataset,which includes human sleep postures used in this study’s experiments,achieved a 96.7%accuracy rate using the Quadratic Support Vector Machine(QSVM)without the blanket.Moreover,the Linear SVM,when utilized with a blanket,attained an accuracy of 96%.When normal distribution serial fusion was applied to the blanket features,it resulted in a remarkable average accuracy of 99%. 展开更多
关键词 Human sleep posture VGG16 deep learning ResNet50 FUSION machine learning
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Multi-Branch High-Dimensional Guided Transformer-Based 3D Human Posture Estimation
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作者 Xianhua Li Haohao Yu +2 位作者 Shuoyu Tian Fengtao Lin Usama Masood 《Computers, Materials & Continua》 SCIE EI 2024年第3期3551-3564,共14页
The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in ... The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample. 展开更多
关键词 Key point detection 3D human posture estimation computer vision deep learning
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Fusion of Convolutional Self-Attention and Cross-Dimensional Feature Transformationfor Human Posture Estimation
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作者 Anzhan Liu Yilu Ding Xiangyang Lu 《Journal of Beijing Institute of Technology》 EI CAS 2024年第4期346-360,共15页
Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which ... Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which is crucial for intelligent applications,contradicts the lowdetection accuracy of human posture detection models in practical scenarios.To address this issue,a human pose estimation network called AT-HRNet has been proposed,which combines convolu-tional self-attention and cross-dimensional feature transformation.AT-HRNet captures significantfeature information from various regions in an adaptive manner,aggregating them through convolu-tional operations within the local receptive domain.The residual structures TripNeck and Trip-Block of the high-resolution network are designed to further refine the key point locations,wherethe attention weight is adjusted by a cross-dimensional interaction to obtain more features.To vali-date the effectiveness of this network,AT-HRNet was evaluated using the COCO2017 dataset.Theresults show that AT-HRNet outperforms HRNet by improving 3.2%in mAP,4.0%in AP75,and3.9%in AP^(M).This suggests that AT-HRNet can offer more beneficial solutions for human posture estimation. 展开更多
关键词 human posture estimation adaptive fusion method cross-dimensional interaction attention module high-resolution network
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Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid(MHAVH)Model
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作者 Hina Naz Zuping Zhang +3 位作者 Mohammed Al-Habib Fuad A.Awwad Emad A.A.Ismail Zaid Ali Khan 《Computers, Materials & Continua》 SCIE EI 2024年第5期2673-2696,共24页
Cardiovascular disease is the leading cause of death globally.This disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may ... Cardiovascular disease is the leading cause of death globally.This disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as possible.Thus,minimizing the death ratio can be achieved by early detection of heart attack(HA)symptoms.In the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four fatalities.However,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives significantly.Our objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their lives.To address these challenges,we employ deep learning techniques.We have utilized a vision transformer(ViT)to address this problem.However,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product attention.Also,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more challenging.In response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction capabilities.By incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack detection.Given the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original datasets.The training accuracy of our model reached an impressive 99.77%.Upon testing,the accuracy for male and female datasets was recorded at 92.87%and 75.47%,respectively.The combined dataset accuracy is 93.96%,showcasing a commendable performance overall.Our proposed approach demonstrates versatility in accommodating small and large datasets,offering promising prospects for real-world applications. 展开更多
关键词 Image analysis posture of heart attack(PHA)detection hybrid features VGG-16 ResNet-50 vision transformer advance multi-head attention layer
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Computer Vision-Based Human Body Posture Correction System
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作者 Yangsen QIU Yukun WANG +2 位作者 Yuchen WU Xinyi QIANG Yunzuo ZHANG 《Mechanical Engineering Science》 2024年第1期1-7,共7页
With the development of technology and the progress of life,more and more people,regardless of entertainment,learning,or work,cannot do without computer desks and cannot put down their mobile phones.Due to prolonged s... With the development of technology and the progress of life,more and more people,regardless of entertainment,learning,or work,cannot do without computer desks and cannot put down their mobile phones.Due to prolonged sitting and often neglecting the importance of posture,incorrect posture can often lead to health problems such as hunchback,lumbar muscle strain,and shoulder and neck pain over time.To address this issue,we designed a computer vision-based human body posture detection system.The system utilizes YOLOv8 technology to accurately locate key points of the human body skeleton,and then analyzes the coordinate positions and depth information of these key points to establish a criterion for distinguishing different postures.With the assistance of an SVM classifier,the system achieves an average recognition rate of 95%.Finally,we successfully deployed the posture detection system on Raspberry Pi hardware and conducted extensive testing.The test results demonstrate that the system can effectively detect various postures and provide real-time reminders to users to correct poor posture,demonstrating good practicality and stability. 展开更多
关键词 computer vision human posture deep learning image processing
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A Survey on Artificial Intelligence in Posture Recognition 被引量:3
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作者 Xiaoyan Jiang Zuojin Hu +1 位作者 Shuihua Wang Yudong Zhang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第10期35-82,共48页
Over the years,the continuous development of new technology has promoted research in the field of posture recognition and also made the application field of posture recognition have been greatly expanded.The purpose o... Over the years,the continuous development of new technology has promoted research in the field of posture recognition and also made the application field of posture recognition have been greatly expanded.The purpose of this paper is to introduce the latest methods of posture recognition and review the various techniques and algorithms of posture recognition in recent years,such as scale-invariant feature transform,histogram of oriented gradients,support vectormachine(SVM),Gaussian mixturemodel,dynamic time warping,hiddenMarkovmodel(HMM),lightweight network,convolutional neural network(CNN).We also investigate improved methods of CNN,such as stacked hourglass networks,multi-stage pose estimation networks,convolutional posemachines,and high-resolution nets.The general process and datasets of posture recognition are analyzed and summarized,and several improved CNNmethods and threemain recognition techniques are compared.In addition,the applications of advanced neural networks in posture recognition,such as transfer learning,ensemble learning,graph neural networks,and explainable deep neural networks,are introduced.It was found that CNN has achieved great success in posture recognition and is favored by researchers.Still,a more in-depth research is needed in feature extraction,information fusion,and other aspects.Among classification methods,HMM and SVM are the most widely used,and lightweight network gradually attracts the attention of researchers.In addition,due to the lack of 3Dbenchmark data sets,data generation is a critical research direction. 展开更多
关键词 posture recognition artificial intelligence machine learning deep neural network deep learning transfer learning feature extraction CLASSIFICATION
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A Realistic 3D Non-Stationary Channel Model for UAV-to-Vehicle Communications Incorporating Fuselage Posture 被引量:1
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作者 Boyu Hua Tongtong Zhou +3 位作者 Qiuming Zhu Kai Mao Junwei Bao Weizhi Zhong 《China Communications》 SCIE CSCD 2023年第6期277-290,共14页
Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) chann... Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) channels. It consists of a line-of-sight(Lo S) and non-line-of-sight(NLo S) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e.the temporal autocorrelation function(ACF) and spatial cross correlation function(CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture. 展开更多
关键词 channel model unmanned aerial vehicle NON-STATIONARY fuselage posture
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Force Sensitive Resistors-Based Real-Time Posture Detection System Using Machine Learning Algorithms
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作者 Arsal Javaid Areeb Abbas +4 位作者 Jehangir Arshad Mohammad Khalid Imam Rahmani Sohaib Tahir Chauhdary Mujtaba Hussain Jaffery Abdulbasid S.Banga 《Computers, Materials & Continua》 SCIE EI 2023年第11期1795-1814,共20页
To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this work.The addressed problem correlates to the third Susta... To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this work.The addressed problem correlates to the third Sustainable Development Goal(SDG),ensuring healthy lives and promoting well-being for all ages,as specified by the World Health Organization(WHO).An improper sitting position can be fatal if one sits for a long time in the wrong position,and it can be dangerous for ulcers and lower spine discomfort.This novel study includes a practical implementation of a cushion consisting of a grid of 3×3 force-sensitive resistors(FSR)embedded to read the pressure of the person sitting on it.Additionally,the Body Mass Index(BMI)has been included to increase the resilience of the system across individual physical variances and to identify the incorrect postures(backward,front,left,and right-leaning)based on the five machine learning algorithms:ensemble boosted trees,ensemble bagged trees,ensemble subspace K-Nearest Neighbors(KNN),ensemble subspace discriminant,and ensemble RUSBoosted trees.The proposed arrangement is novel as existing works have only provided simulations without practical implementation,whereas we have implemented the proposed design in Simulink.The results validate the proposed sensor placements,and the machine learning(ML)model reaches a maximum accuracy of 99.99%,which considerably outperforms the existing works.The proposed concept is valuable as it makes it easier for people in workplaces or even at individual household levels to work for long periods without suffering from severe harmful effects from poor posture. 展开更多
关键词 posture detection FSR sensor machine learning REAL-TIME KNN
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Calf Posture Recognition Using Convolutional Neural Network
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作者 Tan Chen Tung Uswah Khairuddin +3 位作者 Mohd Ibrahim Shapiai Norhariani Md Nor Mark Wen Han Hiew Nurul Aisyah Mohd Suhaimie 《Computers, Materials & Continua》 SCIE EI 2023年第1期1493-1508,共16页
Dairy farm management is crucial to maintain the longevity of the farm,and poor dairy youngstock or calf management could lead to gradually deteriorating calf health,which often causes premature death.This was found t... Dairy farm management is crucial to maintain the longevity of the farm,and poor dairy youngstock or calf management could lead to gradually deteriorating calf health,which often causes premature death.This was found to be the most neglected part among the management workflows in Malaysia and has caused continuous loss over the recent years.Calf posture recognition is one of the effective methods to monitor calf behaviour and health state,which can be achieved by monitoring the calf behaviours of standing and lying where the former depicts active calf,and the latter,passive calf.Calf posture recognition module is an important component of some automated calf monitoring systems,as the system requires the calf to be in a standing posture before proceeding to the next stage of monitoring,or at the very least,to monitor the activeness of the calves.Calf posture such as standing or resting can easily be distinguished by human eye,however,to be recognized by a machine,it will require more complicated frameworks,particularly one that involves a deep learning neural networks model.Large number of highquality images are required to train a deep learning model for such tasks.In this paper,multiple ConvolutionalNeuralNetwork(CNN)architectures were compared,and the residual network(ResNet)model(specifically,ResNet-50)was ultimately chosen due to its simplicity,great performance,and decent inference time.Two ResNet-50 models having the exact same architecture and configuration have been trained on two different image datasets respectively sourced by separate cameras placed at different angle.There were two camera placements to use for comparison because camera placements can significantly impact the quality of the images,which is highly correlated to the deep learning model performance.After model training,the performance for both CNN models were 99.7%and 99.99%accuracies,respectively,and is adequate for a real-time calf monitoring system. 展开更多
关键词 Calf posture machine vision deep learning transfer learning
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Advancements in Functional Magnetic Resonance Imaging for Persistent Postural-Perceptual Dizziness
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作者 Mengchun Zhou Lan Zhang +2 位作者 Tao Yang Qiang Tu Tingting Hu 《Journal of Biosciences and Medicines》 2024年第8期40-50,共11页
Persistent postural-perceptual dizziness, defined in 2017, is a chronic functional vestibular disorder. Which is characterized by persistent dizziness, unsteadiness, and/or non-spinning vertigo. However, the exact mec... Persistent postural-perceptual dizziness, defined in 2017, is a chronic functional vestibular disorder. Which is characterized by persistent dizziness, unsteadiness, and/or non-spinning vertigo. However, the exact mechanisms remain unclear. In recent years, FMRI studies have provided key insights into the pathogenesis of PPPD. This review summarized functional imaging studies of persistent postural dizziness and its predecessors in recent years and found changes in the activity and functional connectivity of important areas of visual processing, multisensory vestibular and spatial cognition in patients with PPPD. In addition, factors such as stimulation mode, personality traits, mental comorbidities and external vestibular lesions have important effects on brain functional activities and connectivity patterns, and further stratified studies on these factors are needed in the future to further clarify and draw exact conclusions on the pathological mechanism of PPPD. 展开更多
关键词 Persistent postural Dizziness Functional Imaging Magnetic Resonance Imaging
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Digital Evaluation of Sitting Posture Comfort in Human-vehicle System under Industry 4.0 Framework 被引量:9
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作者 TAO Qing KANG Jinsheng +2 位作者 SUN Wenlei LI Zhaobo HUO Xiao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2016年第6期1096-1103,共8页
Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation method... Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation methods in real environment and virtual environment is described. The real experimental environment includes the WBV(whole body vibration) test, questionnaires for human subjective sensation and motion capture. The virtual experimental environment includes the theoretical calculation on simplified 5-DOF human body vibration model, the vibration simulation and analysis within ADAMS/VibrationTM module, and the digital human biomechanics and occupational health analysis in Jack software. While the real experimental environment provides realistic and accurate test results, it also serves as core and validation for the virtual experimental environment. The virtual experimental environment takes full advantages of current available vibration simulation and digital human modelling software, and makes it possible to evaluate the sitting posture comfort in a human-vehicle system with various human anthropometric parameters. How this digital evaluation system for car seat comfort design is fitted in the Industry 4.0 framework is also proposed. 展开更多
关键词 sitting posture comfort human-vehicle system digital design digital evaluation Industry 4.0
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A Human Body Posture Recognition Algorithm Based on BP Neural Network for Wireless Body Area Networks 被引量:10
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作者 Fengye Hu Lu Wang +2 位作者 Shanshan Wang Xiaolan Liu Gengxin He 《China Communications》 SCIE CSCD 2016年第8期198-208,共11页
Human body posture recognition has attracted considerable attention in recent years in wireless body area networks(WBAN). In order to precisely recognize human body posture,many recognition algorithms have been propos... Human body posture recognition has attracted considerable attention in recent years in wireless body area networks(WBAN). In order to precisely recognize human body posture,many recognition algorithms have been proposed.However, the recognition rate is relatively low. In this paper, we apply back propagation(BP) neural network as a classifier to recognizing human body posture, where signals are collected from VG350 acceleration sensor and a posture signal collection system based on WBAN is designed. Human body signal vector magnitude(SVM) and tri-axial acceleration sensor data are used to describe the human body postures. We are able to recognize 4postures: Walk, Run, Squat and Sit. Our posture recognition rate is up to 91.67%. Furthermore, we find an implied relationship between hidden layer neurons and the posture recognition rate. The proposed human body posture recognition algorithm lays the foundation for the subsequent applications. 展开更多
关键词 wireless body area networks BP neural network signal vector magnitude posture recognition rate
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Research on Passive Locating Method Using Phase Rate of Change with Variant Posture of the Observer 被引量:4
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作者 单月晖 安玮 +1 位作者 孙仲康 皇甫堪 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2002年第3期166-170,共5页
Technology of passive location has broad prospects in applications. In this paper, the method using the phase rate of change for the single observer passive location is introduced based on existing methods. One can ob... Technology of passive location has broad prospects in applications. In this paper, the method using the phase rate of change for the single observer passive location is introduced based on existing methods. One can obtain the direction of the target with phase information of two orthogonal interferometers on the observer and the radial distance with the corresponding phase rate of change. Then the target can be located with high speed and precision. A locating approach is given when the flying posture of t... 展开更多
关键词 PHASE rate of change single observer passive location variant posture direction radial distance MGEKF
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Motion/Posture Modeling and Simulation Verification of Physically Handicapped in Manufacturing System Design 被引量:3
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作者 FU Yan LI Shiqi CHEN Gwen-guo 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2013年第2期225-231,共7页
Non-obstacle design is critical to tailor physically handicapped workers in manufacturing system. Simultaneous consideration of variability in physically disabled users, machines and environment of the manufacturing s... Non-obstacle design is critical to tailor physically handicapped workers in manufacturing system. Simultaneous consideration of variability in physically disabled users, machines and environment of the manufacturing system is extremely complex and generally requires modeling of physically handicapped interaction with the system. Most current modeling either concentrates on the task results or functional disability. The integration of physical constraints with task constraints is far more complex because of functional disability and its extended influence on adjacent body parts. A framework is proposed to integrate the two constraints and thus model the specific behavior of the physical handicapped in virtual environment generated by product specifications. Within the framework a simplified model of physical disabled body is constructed, and body motion is generated based on 3 levels of constraints(effecter constraints, kinematics constraints and physical constraints). The kinematics and dynamic calculations are made and optimized based on the weighting manipulated by the kinematics constraints and dynamic constraints. With object transferring task as example, the model is validated in Jack 6.0. Modelled task motion elements except for squatting and overreaching well matched with captured motion elements. The proposed modeling method can model the complex behavior of the physically handicapped by integrating both task and physical disability constraints. 展开更多
关键词 physical handicapped motion/posture modeling manufacturing system design
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Design and Efficacy of Surgery for Horizontal Idiopathic Nystagmus with Abnormal Head Posture and Strabismus 被引量:4
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作者 王平 娄丽萍 宋琳 《Journal of Huazhong University of Science and Technology(Medical Sciences)》 SCIE CAS 2011年第5期678-681,共4页
The design and efficacy of surgery for horizontal idiopathic nystagmus (HIN) with abnormal head posture and strabismus were investigated. Different surgical procedures were selected according to the angle of head tu... The design and efficacy of surgery for horizontal idiopathic nystagmus (HIN) with abnormal head posture and strabismus were investigated. Different surgical procedures were selected according to the angle of head turn in 44 cases of HIN with abnormal head posture and strabismus. For patients with a head turn of 15° or less, the Anderson procedure was used; the yoke muscles were recessed upon slow-phase. For patients with a head turn between 15° and 25°, the surgery was designed as a Kestenbaum 5-4-4-5 procedure. For patients with a head turn of 25° or more, the surgery was designed as a Parks 5-8-6-7 procedure. The surgery to correct the abnormal head posture was performed on the fixating eye while that to correct the deviation was then performed on the non-fixating eye at the same time. The amount of surgery of the horizontal rectus muscles on the nonfixating eye was sum of the angle of head turn and the degree of deviation, which was calculated as follows: recession/resection amount of medial and lateral rectis/2×5=angle of head turn±degree of deviation. The results showed as follows: (1) Visual acuity: the visual acuity in the primary ocular position increased two lines or more in 35 patients, accounting for 79.55%. Nine patients had no or only one-line improvement, accounting for 20.45% of the entire study population; (2) The degree of deviation in the primary ocular position: 37 cases had a normal primary ocular position or the degree of deviation ≤8△ after surgery, accounting for 84.09%. Six patients had a residual degree of deviation of 8△―15△, accounting for 13.64%. One patient had a residual degree of deviation 〉20△, accounting for 2.27% of the patients examined; (3) Abnormal head posture: 34 patients had a normal head posture or a head turn of less than 5°, accounting for 72.27%. Eight patients had a residual head turn of 5°―15°, accounting for 18.18%. Two patients had a head turn of 15°― 25°, accounting for 4.55%. It was concluded that different surgical procedures based on the angle of head turn and the relationship between deviation and null zone can eliminate anomalous head posture, correct deviation, and improve vision acuity in the primary ocular position simultaneously. 展开更多
关键词 horizontal idiopathic nystagmus abnormal head posture and strabismus SURGERY
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Investigation of compensatory postures with videofluoromanometry in dysphagia patients 被引量:3
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作者 Antonio Solazzo Luigi Monaco +7 位作者 Lucia Del Vecchio Stefania Tamburrini Francesca Iacobellis Daniela Berritto Nunzia Luisa Pizza Alfonso Reginelli Natale Di Martino Roberto Grassi 《World Journal of Gastroenterology》 SCIE CAS CSCD 2012年第23期2973-2978,共6页
AIM: To investigate the effectiveness of head compensatory postures to ensure safe oropharyngeal transit. METHODS: A total of 321 dysphagia patients were enrolled and assessed with videofluoromanometry (VFM). The dysp... AIM: To investigate the effectiveness of head compensatory postures to ensure safe oropharyngeal transit. METHODS: A total of 321 dysphagia patients were enrolled and assessed with videofluoromanometry (VFM). The dysphagia patients were classified as follows: safe transit; penetration without aspiration; aspiration before, during or after swallowing; multiple aspirations and no transit. The patients with aspiration or no transit were tested with VFM to determine whether compensatory postures could correct their swallowing disorder. RESULTS: VFM revealed penetration without aspiration in 71 patients (22.1%); aspiration before swallowing in 17 patients (5.3%); aspiration during swallowing in 32 patients (10%); aspiration after swallowing in 21 patients (6.5%); multiple aspirations in six patients (1.9%); no transit in five patients (1.6%); and safe transit in 169 patients (52.6%). Compensatory postures guaranteed a safe transit in 66/75 (88%) patients with aspiration or no transit. A chin-down posture achieved a safe swallow in 42/75 (56%) patients, a head-turned posture in 19/75 (25.3%) and a hyperextended head posture in 5/75 (6.7%). The compensatory postures were not effective in 9/75 (12%) cases. CONCLUSION: VFM allows the speech-language therapist to choose the most effective compensatory posture without a trial-and-error process and check the effectiveness of the posture. 展开更多
关键词 ASPIRATION Compensatory postures Oro-pharyngeal dysphagia Videofluoromanometry Chin-down posture Head-turned Hyperextended head
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Gravitational effects on global hemodynamics in different postures:A closed-loop multiscale mathematical analysis 被引量:2
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作者 Xiancheng Zhang Shigeho Noda +1 位作者 Ryutaro Himeno Hao Liu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2017年第3期595-618,共24页
We present a novel methodology and strategy to predict pressures and flow rates in the global cardiovascular network in different postures varying from supine to upright. A closed-loop, multiscale mathematical model o... We present a novel methodology and strategy to predict pressures and flow rates in the global cardiovascular network in different postures varying from supine to upright. A closed-loop, multiscale mathematical model of the entire cardiovascular system (CVS) is developed through an integration of one-dimensional (1D) modeling of the large systemic arteries and veins, and zero-dimensional (0D) lumped-parameter modeling of the heart, the cardiac-pulmonary circulation, the cardiac and venous valves, as well as the microcirculation. A versatile junction model is proposed and incorporated into the 1D model to cope with splitting and/or merging flows across a multibranched junction, which is validated to be capable of estimating both subcritical and supercritical flows while ensuring the mass conservation and total pressure continuity. To model gravitational effects on global hemodynamics during postural change, a robust venous valve model is further established for the 1D venous flows and distributed throughout the entire venous network with consideration of its anatomically realistic numbers and locations. The present integrated model is proven to enable reasonable prediction of pressure and flow rate waveforms associated with cardiopulmonary circulation, systemic circulation in arteries and veins, as well as microcirculation within normal physiological ranges, particularly in mean venous pressures, which well match the in vivo measurements. Applications of the cardiovascular model at different postures demonstrate that gravity exerts remarkable influence on arterial and venous pressures, venous returns and cardiac outputs whereas venous pressures below the heart level show a specific correlation between central venous and hydrostatic pressures in right atrium and veins. 展开更多
关键词 Gravitational effects Cardiovascular system (CVS) postural change Multiscale cardiovascular model Multibranched junction model Venous valve
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Posture Maintenance Control of 2-Link Object By Nonprehensile Two-Cooperative-Arm Robot Without Compensating Friction 被引量:1
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作者 Changan Jiang Satoshi Ueno 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2019年第6期1397-1403,共7页
In this paper, a method to posture maintenance control of 2-link object by nonprehensile two-cooperative-arm robot without compensating friction is proposed. In details, a mathematical model of the 2-link object is fi... In this paper, a method to posture maintenance control of 2-link object by nonprehensile two-cooperative-arm robot without compensating friction is proposed. In details, a mathematical model of the 2-link object is firstly built. Based on the model, stable regions for holding motion of nonprehensile two-cooperative-arm robot are obtained while the 2-link object is kept stable on the robot arms with static friction. Among the obtained stable regions, the robust pairs of orientation angles of the 2-link object are found. Under the robust orientation angles, a feedback control system is designed to control the arms to maintain the 2-link object's posture while it is being held or lifted up. Finally, experimental results are shown to verify the effectiveness of the proposed method. 展开更多
关键词 Nursing care nonprehensile ROBOT posture maintenance static FRICTION two-cooperative-arm ROBOT
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STRUCTURAL PARAMETERS CALIBRATION BY POSTURE MEASUREMENT ON PARALLEL 6-DOF PLATFORM 被引量:1
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作者 Wu Jiangning Li ShilunState Key Laboratory of Fluid Power Transmission and Control, Zhejiang University,Hangzhou 310027, China 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2002年第4期334-338,343,共6页
Some approaches to measure parallel 6-degree of freedom platform's posturestatically and to calibrate the platform's actual structural parameters by measuring a series of theplatform's varying postures are... Some approaches to measure parallel 6-degree of freedom platform's posturestatically and to calibrate the platform's actual structural parameters by measuring a series of theplatform's varying postures are studied. In the case where high posture accuracy is requiredrelatively, to obtain the platform's actual structural parameters is very important. Threedimensions measurement with 2 theodolites are used to obtain the platform's postures statically andNewton iterative method is adopted to calibrate structural parameters. Some measures taken in themeasurement and the calibration are discussed in detail. And the experiment results of theplatform's posture control before and after the calibration are given. The results show that theplatform's posture control accuracy after the calibration is improved notably. 展开更多
关键词 parallel 6-DOF platform theodolite posture measurement nonlinearequation group structural parameters calibration
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