Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336097
Kat R. Agres, Dorien Herremans
Traditional physical therapy methods require significant time from trained medical staff, which is costly for clinics and hospitals, and often leave patients bored and unmotivated to complete their exercises. We offer a prototype for a motion-detection and music game to inspire greater engagement and adherence from patients undergoing physical therapy exercises for rehabilitation or strengthening. The game is customizable based on the patient's needs, dynamically reacts to the patient's performance in real-time, and may be used with or without the guidance of a medical professional.
{"title":"Music and motion-detection: A game prototype for rehabilitation and strengthening in the elderly","authors":"Kat R. Agres, Dorien Herremans","doi":"10.1109/ICOT.2017.8336097","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336097","url":null,"abstract":"Traditional physical therapy methods require significant time from trained medical staff, which is costly for clinics and hospitals, and often leave patients bored and unmotivated to complete their exercises. We offer a prototype for a motion-detection and music game to inspire greater engagement and adherence from patients undergoing physical therapy exercises for rehabilitation or strengthening. The game is customizable based on the patient's needs, dynamically reacts to the patient's performance in real-time, and may be used with or without the guidance of a medical professional.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130206167","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336090
Ming-Hsiang Su, Chung-Hsien Wu, Kun-Yi Huang, Qian-Bei Hong, H. Wang
In clinical diagnosis of mood disorder, depression is one of the most common psychiatric disorders. There are two major types of mood disorders: major depressive disorder (MDD) and bipolar disorder (BPD). A large portion of BPD are misdiagnosed as MDD in the diagnostic of mood disorders. Short-term detection which could be used in early detection and intervention is thus desirable. This study investigates microscopic facial expression changes for the subjects with MDD, BPD and control group (CG), when elicited by emotional video clips. This study uses eight basic orientations of motion vector (MV) to characterize the subtle changes in microscopic facial expression. Then, wavelet decomposition is applied to extract entropy and energy of different frequency bands. Next, an autoencoder neural network is adopted to extract the bottleneck features for dimensionality reduction. Finally, the long short term memory (LSTM) is employed for modeling the long-term variation among different mood disorders types. For evaluation of the proposed method, the elicited data from 36 subjects (12 for each of MDD, BPD and CG) were considered in the K-fold (K=12) cross validation experiments, and the performance for distinguishing among MDD, BPD and CG achieved 67.7% accuracy.
{"title":"Exploring microscopic fluctuation of facial expression for mood disorder classification","authors":"Ming-Hsiang Su, Chung-Hsien Wu, Kun-Yi Huang, Qian-Bei Hong, H. Wang","doi":"10.1109/ICOT.2017.8336090","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336090","url":null,"abstract":"In clinical diagnosis of mood disorder, depression is one of the most common psychiatric disorders. There are two major types of mood disorders: major depressive disorder (MDD) and bipolar disorder (BPD). A large portion of BPD are misdiagnosed as MDD in the diagnostic of mood disorders. Short-term detection which could be used in early detection and intervention is thus desirable. This study investigates microscopic facial expression changes for the subjects with MDD, BPD and control group (CG), when elicited by emotional video clips. This study uses eight basic orientations of motion vector (MV) to characterize the subtle changes in microscopic facial expression. Then, wavelet decomposition is applied to extract entropy and energy of different frequency bands. Next, an autoencoder neural network is adopted to extract the bottleneck features for dimensionality reduction. Finally, the long short term memory (LSTM) is employed for modeling the long-term variation among different mood disorders types. For evaluation of the proposed method, the elicited data from 36 subjects (12 for each of MDD, BPD and CG) were considered in the K-fold (K=12) cross validation experiments, and the performance for distinguishing among MDD, BPD and CG achieved 67.7% accuracy.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129877178","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336113
Shih-Huang Chen, Chun-Hung Richard Lin, Wen-Kai Liu, Jui-Yang Tsai
This paper proposes a novel semi-supervised classification method of petrol and diesel passenger cars using OBD data and support vector machine (SVM) algorithm. The proposed method first develops a classification rule of petrol and diesel passenger cars based on vehicle speed as well as engine RPM obtained from the on-board diagnostic (OBD) data with specific passenger car identification number (ID). Then the proposed method could primarily label petrol or diesel to the passenger car with specific ID using the classification rule. Next this paper apply support vector machine to create a classification model of petrol and diesel passenger cars based on the primary classification results, and to perform refined classification tasks. Experimental results show the correctness of the proposed semi-supervised petrol and diesel passenger car classification method can achieve 1.5% calibration rate from more than 35,000 real OBD data. The proposed method has the potential of applying to internet of vehicle (IoV) and to improve on-road CO2 emission estimation.
{"title":"The semi-supervised classification of petrol and diesel passenger cars based on OBD and support vector machine algorithm","authors":"Shih-Huang Chen, Chun-Hung Richard Lin, Wen-Kai Liu, Jui-Yang Tsai","doi":"10.1109/ICOT.2017.8336113","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336113","url":null,"abstract":"This paper proposes a novel semi-supervised classification method of petrol and diesel passenger cars using OBD data and support vector machine (SVM) algorithm. The proposed method first develops a classification rule of petrol and diesel passenger cars based on vehicle speed as well as engine RPM obtained from the on-board diagnostic (OBD) data with specific passenger car identification number (ID). Then the proposed method could primarily label petrol or diesel to the passenger car with specific ID using the classification rule. Next this paper apply support vector machine to create a classification model of petrol and diesel passenger cars based on the primary classification results, and to perform refined classification tasks. Experimental results show the correctness of the proposed semi-supervised petrol and diesel passenger car classification method can achieve 1.5% calibration rate from more than 35,000 real OBD data. The proposed method has the potential of applying to internet of vehicle (IoV) and to improve on-road CO2 emission estimation.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123020335","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336074
Fan Bu, Yan Wu
The use of robots has been proposed as promising human assistants in accomplishing tasks that are otherwise too tough or dangerous to be executed by human alone. As robots in different forms have their differentiating strengths, a system that uses a combination of these robots can be more robust and resilient in achieving its mission. For example, UAVs can be used to quickly explore an unknown environment while ground robots can be used to navigate through the environment, clearing obstacles and potential dangers for human to enter. In this work, we design a unifying framework to allow human to control and accomplish an exploration mission using heterogeneous robot types. A prototype system is implemented using the Google Tango to control an UAV and a wheeled robot for the human to perform environment mapping. Preliminary experiments have been carried out to study the feasibility of the system.
{"title":"Towards a human-robot teaming system for exploration of environment","authors":"Fan Bu, Yan Wu","doi":"10.1109/ICOT.2017.8336074","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336074","url":null,"abstract":"The use of robots has been proposed as promising human assistants in accomplishing tasks that are otherwise too tough or dangerous to be executed by human alone. As robots in different forms have their differentiating strengths, a system that uses a combination of these robots can be more robust and resilient in achieving its mission. For example, UAVs can be used to quickly explore an unknown environment while ground robots can be used to navigate through the environment, clearing obstacles and potential dangers for human to enter. In this work, we design a unifying framework to allow human to control and accomplish an exploration mission using heterogeneous robot types. A prototype system is implemented using the Google Tango to control an UAV and a wheeled robot for the human to perform environment mapping. Preliminary experiments have been carried out to study the feasibility of the system.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124499761","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336081
A. Argha, B. Celler
This paper presents findings on patient compliance in the recently completed Commonwealth Scientific and Industrial Research Organization (CSIRO) trial of home monitoring for chronic disease management carried out at several locations along the east coast of Australia. Subjects in this project had a principal diagnosis of Chronic Obstructive Pulmonary Disease (COPD), Coronary Artery Disease (CAD), Hypertensive Diseases (HD), Congestive Heart Failure (CHF), Diabetes or Asthma. All had been admitted to hospital at least once in the previous year. A number of vital signs, determined by the patient's condition, were monitored on average for 302 days. No statistically significant reduction in compliance was found over time. However, the compliance rates of patients monitored in hospital settings relative to those monitored in community settings were significantly higher for spirometry, body weight and body temperature, and the compliance rates for blood pressure, ECG and pulse oximetry were significantly higher in male relative to female subjects. No statistical differences were observed between rates of compliance for younger patients group (≤ 70 years old) and older patient group (> 70).
{"title":"Analysis of the compliance with the measurement protocols scheduled in a telemonitoring system","authors":"A. Argha, B. Celler","doi":"10.1109/ICOT.2017.8336081","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336081","url":null,"abstract":"This paper presents findings on patient compliance in the recently completed Commonwealth Scientific and Industrial Research Organization (CSIRO) trial of home monitoring for chronic disease management carried out at several locations along the east coast of Australia. Subjects in this project had a principal diagnosis of Chronic Obstructive Pulmonary Disease (COPD), Coronary Artery Disease (CAD), Hypertensive Diseases (HD), Congestive Heart Failure (CHF), Diabetes or Asthma. All had been admitted to hospital at least once in the previous year. A number of vital signs, determined by the patient's condition, were monitored on average for 302 days. No statistically significant reduction in compliance was found over time. However, the compliance rates of patients monitored in hospital settings relative to those monitored in community settings were significantly higher for spirometry, body weight and body temperature, and the compliance rates for blood pressure, ECG and pulse oximetry were significantly higher in male relative to female subjects. No statistical differences were observed between rates of compliance for younger patients group (≤ 70 years old) and older patient group (> 70).","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115507256","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336100
Bo-Hao Su, Shih-Pang Tseng, Jhing-Fa Wang, J. Huang
This paper presents the based-on question answering system for spoken dialogue. Utilizing sentence similarity to calculate the score and finding the corresponding sentence are main parts. When the corpus is insufficient, the usergenerated answer is generated form Free Talk. In our system, the ASR transcription is processed through Chinese Knowledge and Information Processing (CKIP) Chinese words segmentation system. Then, filtering the command sentences through human machine interface, remaining normal sentences are passed the dialogue system, and normal sentences are vectorized through preprocess bag of word. All sentences of corpus have been preprocessed and vectorized in vector space model, then, input sentence is calculated by sentence similarity with vector space model. In order to make system more enjoyable, we adapt image recognition to record the round emotions. According to the round emotions, to response the emotion conversation.
{"title":"Based on sentence similarity and emotion conversation for spoken dialogue system","authors":"Bo-Hao Su, Shih-Pang Tseng, Jhing-Fa Wang, J. Huang","doi":"10.1109/ICOT.2017.8336100","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336100","url":null,"abstract":"This paper presents the based-on question answering system for spoken dialogue. Utilizing sentence similarity to calculate the score and finding the corresponding sentence are main parts. When the corpus is insufficient, the usergenerated answer is generated form Free Talk. In our system, the ASR transcription is processed through Chinese Knowledge and Information Processing (CKIP) Chinese words segmentation system. Then, filtering the command sentences through human machine interface, remaining normal sentences are passed the dialogue system, and normal sentences are vectorized through preprocess bag of word. All sentences of corpus have been preprocessed and vectorized in vector space model, then, input sentence is calculated by sentence similarity with vector space model. In order to make system more enjoyable, we adapt image recognition to record the round emotions. According to the round emotions, to response the emotion conversation.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127763507","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}
Group emotion refers to the emotions of a group of people in a specified space and time interval. It is the result of the interactions among the people and the environment. Group emotion is the group's dynamic processes, and can be seen as the sum of the individuals' emotional states. In practice, the group emotion detection has various applications, such as e-learning systems and video conferencing. In this paper, we proposed a the group emotion detector is based on the multi-level smile detection algorithm. According to the bottom-up view point, the group emotion is defined as the average of the smile degrees on this group of people. The whole system is implemented on the Raspberry Pi board for the compactness and mobility. The implementation shows this approach is with availability in practice. The experimental basically result shows the effectiveness of the Group Emotion Detector.
{"title":"Design and implementation of the image-based group emotion detector","authors":"Jui-Le Chen, Jun-Ying Chen, Sheng-Ting Huang, Qige Ye, Qi-Wen Gung, Shih-Pang Tseng","doi":"10.1109/ICOT.2017.8336102","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336102","url":null,"abstract":"Group emotion refers to the emotions of a group of people in a specified space and time interval. It is the result of the interactions among the people and the environment. Group emotion is the group's dynamic processes, and can be seen as the sum of the individuals' emotional states. In practice, the group emotion detection has various applications, such as e-learning systems and video conferencing. In this paper, we proposed a the group emotion detector is based on the multi-level smile detection algorithm. According to the bottom-up view point, the group emotion is defined as the average of the smile degrees on this group of people. The whole system is implemented on the Raspberry Pi board for the compactness and mobility. The implementation shows this approach is with availability in practice. The experimental basically result shows the effectiveness of the Group Emotion Detector.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133240377","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336085
Gwo-Giun Lee, Kuan-Wei Haung, Chi‐Kuang Sun, Y. Liao
Stem cell plays an important role in repairing destroyed tissues and keeping human healthy every day; and thus stem cell observation and detection are principle procedures before being analyzed by physicians. In this paper, we proposed a criterion of Computer-Aided Diagnosis (CAD) system to detect stem cells in the stratum basale based on cell segmentation algorithm and intrinsic characteristics of cells, which can provide consistent and accurate results for assisting the assessment of diagnosis. In addition, we utilize Convolutional Neural Networks (CNNs) to recognize basal cells and stem cells since CNN has excellent performance on processing abundant data. Actually, the procedure of acquiring biomedical images is too complicated to collect, hence hand-crafted initialization is adopted to overcome the issue of the lack of training data according to prior knowledge or the suggestion from medical doctors. The experimental results show that the accuracy of hand-crafted initialization is higher than random distribution kernels and the convergence time is shorter also since a better initial condition may lead to better results in optimization theory.
{"title":"Stem cell detection based on Convolutional Neural Network via third harmonic generation microscopy images","authors":"Gwo-Giun Lee, Kuan-Wei Haung, Chi‐Kuang Sun, Y. Liao","doi":"10.1109/ICOT.2017.8336085","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336085","url":null,"abstract":"Stem cell plays an important role in repairing destroyed tissues and keeping human healthy every day; and thus stem cell observation and detection are principle procedures before being analyzed by physicians. In this paper, we proposed a criterion of Computer-Aided Diagnosis (CAD) system to detect stem cells in the stratum basale based on cell segmentation algorithm and intrinsic characteristics of cells, which can provide consistent and accurate results for assisting the assessment of diagnosis. In addition, we utilize Convolutional Neural Networks (CNNs) to recognize basal cells and stem cells since CNN has excellent performance on processing abundant data. Actually, the procedure of acquiring biomedical images is too complicated to collect, hence hand-crafted initialization is adopted to overcome the issue of the lack of training data according to prior knowledge or the suggestion from medical doctors. The experimental results show that the accuracy of hand-crafted initialization is higher than random distribution kernels and the convergence time is shorter also since a better initial condition may lead to better results in optimization theory.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126048506","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336104
Mingrui Zeng, S. Liou
This design program aims to develop a healthy APP for modern users. Drawing on the design framework combined hedonic and eudemonic well-being, we developed an APP integrates Mindfulness and Flourishing training program from clinical psychologist and portable bio-detector devises for feedback, in which provide self-practice for reducing the negative emotion (mindfulness) and increasing the positive emotion (flourishing). Using user experiences test and existing marketing survey, we elaborated the previous MFI conceptual framework and advance our design in (the four major components). This prototype can contribute as comprehensive framework as self-train healthy APP with bio-psychological and behavioral feedback. For the future development, we will advance this MFI with field experiment with integrating the bio-detectors. We also have programs of marketing research for cultural with different healthy philosophy and life style.
{"title":"Mindfulness and flourishing interface (MFI): An APP prototype for hedonic and eudemonic wellbeing","authors":"Mingrui Zeng, S. Liou","doi":"10.1109/ICOT.2017.8336104","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336104","url":null,"abstract":"This design program aims to develop a healthy APP for modern users. Drawing on the design framework combined hedonic and eudemonic well-being, we developed an APP integrates Mindfulness and Flourishing training program from clinical psychologist and portable bio-detector devises for feedback, in which provide self-practice for reducing the negative emotion (mindfulness) and increasing the positive emotion (flourishing). Using user experiences test and existing marketing survey, we elaborated the previous MFI conceptual framework and advance our design in (the four major components). This prototype can contribute as comprehensive framework as self-train healthy APP with bio-psychological and behavioral feedback. For the future development, we will advance this MFI with field experiment with integrating the bio-detectors. We also have programs of marketing research for cultural with different healthy philosophy and life style.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130635715","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}
Pub Date : 2017-12-01DOI: 10.1109/ICOT.2017.8336119
Quang D. D. Nguyen, An D. Le, Bao Q. Pham, Hien M. Nguyen
Human brain functional connectivity can be reliably studied with the aid of 1MRI technology. Brain functional network decomposition can be solved by available methods such as Independent Component Analysis (ICA) with independence constraint, Morphological Component Analysis with KSVD dictionary update (MCA-KSVD) with sparsity constraint on spatial components, or constraint-free method PowerFactorization (PF) that has not been applied and known to the fMRI community so far. In the quest for finding methods that are effective for analyzing 1MRI functional networks, this study investigates the effects of various constraints used in the ICA MCA-KSVD and PF methods on the resulting decomposed networks. The observed mutual effects of independence and extreme sparsity constraints experimentally suggest that there is a connection between the two constraints. Specifically, the sparsity constraint in extreme case yields spatially independent components.
{"title":"Effects of regularizaron constraints on FMRI brain network source decomposition","authors":"Quang D. D. Nguyen, An D. Le, Bao Q. Pham, Hien M. Nguyen","doi":"10.1109/ICOT.2017.8336119","DOIUrl":"https://doi.org/10.1109/ICOT.2017.8336119","url":null,"abstract":"Human brain functional connectivity can be reliably studied with the aid of 1MRI technology. Brain functional network decomposition can be solved by available methods such as Independent Component Analysis (ICA) with independence constraint, Morphological Component Analysis with KSVD dictionary update (MCA-KSVD) with sparsity constraint on spatial components, or constraint-free method PowerFactorization (PF) that has not been applied and known to the fMRI community so far. In the quest for finding methods that are effective for analyzing 1MRI functional networks, this study investigates the effects of various constraints used in the ICA MCA-KSVD and PF methods on the resulting decomposed networks. The observed mutual effects of independence and extreme sparsity constraints experimentally suggest that there is a connection between the two constraints. Specifically, the sparsity constraint in extreme case yields spatially independent components.","PeriodicalId":297245,"journal":{"name":"2017 International Conference on Orange Technologies (ICOT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125701389","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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