The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive fun... more The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive function assessment system using the wireless sensor network and multimedia technologies. The system comprised (1) interaction devices, FCs and a workstation used as interactive tools for collecting and transferring data to the server, (2) a BG information management system responsible for managing the cognitive games and storing test results, and (3) a feedback system used for conducting the analysis of cognitive functions to assist caregivers in screening high risk groups with mild cognitive impairment. Three kinds of experiments were performed to evaluate the developed FC-based BG cognitive function assessment system. The experimental results showed that the Pearson correlation coefficient between the system's evaluation outcomes and the traditional Montreal Cognitive Assessment scores was 0.83. The average Technology Acceptance Model 2 score was close to six for 31 elderly subjects. Most subjects considered that the brain games are interesting and the FC human-machine interface is easy to learn and operate. The control group and the cognitive impairment group had statistically significant difference with respect to the accuracy of and the time taken for the brain cognitive function assessment games, including Animal Naming, Color Search, Trail Making Test, Change Blindness, and Forward / Backward Digit Span.
2012 4th International High Speed Intelligent Communication Forum, 2012
In recent years, increased awareness of health issues and environmental protection, and the intro... more In recent years, increased awareness of health issues and environmental protection, and the introduction of regulations regarding air quality, have created a demand for air quality monitoring technology. By combining wireless sensing technology and the ARIMA prediction model, an intelligent air quality monitoring system was constructed, which uses the ARIMA model to predict the carbon dioxide trend, thus providing capabilities
The purpose of this study is to build an indoor air quality monitoring system based on wireless s... more The purpose of this study is to build an indoor air quality monitoring system based on wireless sensor networks (WSNs) technology. The main functions of the system include (1) remote parameter adjustment and firmware update mechanism for the sensors to enhance the flexibility and convenience of the system, (2) sensor nodes are designed by referring to the IEEE 1451.4 standard. This way, sensor nodes can automatically adjust and be plug and play, and (3) calibration method to strength the measurement value's sensitivity and accuracy. The experimental results show that transmission speed improves 30% than Trickle, transmission volume reduced to 42% of the original volume, updating task in 5*5 network topology can be executed 1.79 times and power consumption reduced to 30%. When baseline drifts, we can use the firmware update mechanism to adjust the reference value. The way can reduce error percentage from 15% to 7%.
A GPU-based parallel computing framework for accelerating graph theoretical analyses Tsang-Chu Yu... more A GPU-based parallel computing framework for accelerating graph theoretical analyses Tsang-Chu Yu, Yi-Ping Chao, Li-Wei Kuo, Chung-Chih Lin, Shih-Yen Lin, Hengtai Jan, Claudia Metzler-Baddeley, and Derek Jones Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan, Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan, School of Psychology, Cardiff University, Cardiff, United Kingdom
Introduction Studies on brain structural and functional connectivity using modern neuroimaging me... more Introduction Studies on brain structural and functional connectivity using modern neuroimaging methods have caught great attention in neuroscience research. Among these methods, brain network analysis with graph theory has been increasingly employed to layout the connective characteristics between different cortical regions and provide a global view of how brain works internally. Although the brain network analysis is potentially useful and powerful, the connective characteristics highly depend on the definition of cortical regions (i.e. nodes in graph theory). Conventionally, the anatomically and functionally cortical parcellations, such as Automatic Anatomical Labeling (AAL) and Brodmann atlases, have been used in most previous studies. In order to investigate the brain networks at different scales, a number of recent studies have attempted to divide the cortical regions of a given brain atlas into smaller parcels at multiple levels of granularity [1-3]. Although these proposed me...
The goal of this study is to use wireless sensor technologies to develop a smart clothes service ... more The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the "very good signal" interval. The average of the QRS sensitivity and po...
2012 Third International Conference on Intelligent Control and Information Processing, 2012
ABSTRACT The purpose of this study is to use wireless sensing technologies to develop a cognitive... more ABSTRACT The purpose of this study is to use wireless sensing technologies to develop a cognitive function analysis system based on Montreal Cognitive Assessment (MoCA). The system consists of three parts: (1) Data acquisition: We have designed seven kinds of games to assess five-oriented capabilities including naming, attention, abstraction, delayed recall and orientation. System collects automatically all operation steps, error count and finish time when tester plays the game. (2) Data analysis: try to analyze the collected data and calculate the quantitative results of mental indicators. (3) Feedback system: to screen the high-risk group of degradation of cognitive function to start the care plan earlier. This system can not only assist long-term care institutions to create new social activities for elder person, but also train their cognitive abilities and reduce the risk of dementia.
International Journal of Distributed Sensor Networks, 2015
The aim of this study is to construct an intelligent wireless sensing and control system to addre... more The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy log...
Computational and mathematical methods in medicine, 2015
The goal of this study is to use wireless sensor technologies to develop a smart clothes service ... more The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the "very good signal" interval. The average of the QRS sensitivity and pos...
The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive fun... more The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive function assessment system using the wireless sensor network and multimedia technologies. The system comprised (1) interaction devices, FCs and a workstation used as interactive tools for collecting and transferring data to the server, (2) a BG information management system responsible for managing the cognitive games and storing test results, and (3) a feedback system used for conducting the analysis of cognitive functions to assist caregivers in screening high risk groups with mild cognitive impairment. Three kinds of experiments were performed to evaluate the developed FC-based BG cognitive function assessment system. The experimental results showed that the Pearson correlation coefficient between the system's evaluation outcomes and the traditional Montreal Cognitive Assessment scores was 0.83. The average Technology Acceptance Model 2 score was close to six for 31 elderly subjects. Most subjects considered that the brain games are interesting and the FC human-machine interface is easy to learn and operate. The control group and the cognitive impairment group had statistically significant difference with respect to the accuracy of and the time taken for the brain cognitive function assessment games, including Animal Naming, Color Search, Trail Making Test, Change Blindness, and Forward / Backward Digit Span.
2012 4th International High Speed Intelligent Communication Forum, 2012
In recent years, increased awareness of health issues and environmental protection, and the intro... more In recent years, increased awareness of health issues and environmental protection, and the introduction of regulations regarding air quality, have created a demand for air quality monitoring technology. By combining wireless sensing technology and the ARIMA prediction model, an intelligent air quality monitoring system was constructed, which uses the ARIMA model to predict the carbon dioxide trend, thus providing capabilities
The purpose of this study is to build an indoor air quality monitoring system based on wireless s... more The purpose of this study is to build an indoor air quality monitoring system based on wireless sensor networks (WSNs) technology. The main functions of the system include (1) remote parameter adjustment and firmware update mechanism for the sensors to enhance the flexibility and convenience of the system, (2) sensor nodes are designed by referring to the IEEE 1451.4 standard. This way, sensor nodes can automatically adjust and be plug and play, and (3) calibration method to strength the measurement value's sensitivity and accuracy. The experimental results show that transmission speed improves 30% than Trickle, transmission volume reduced to 42% of the original volume, updating task in 5*5 network topology can be executed 1.79 times and power consumption reduced to 30%. When baseline drifts, we can use the firmware update mechanism to adjust the reference value. The way can reduce error percentage from 15% to 7%.
A GPU-based parallel computing framework for accelerating graph theoretical analyses Tsang-Chu Yu... more A GPU-based parallel computing framework for accelerating graph theoretical analyses Tsang-Chu Yu, Yi-Ping Chao, Li-Wei Kuo, Chung-Chih Lin, Shih-Yen Lin, Hengtai Jan, Claudia Metzler-Baddeley, and Derek Jones Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan, Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan, School of Psychology, Cardiff University, Cardiff, United Kingdom
Introduction Studies on brain structural and functional connectivity using modern neuroimaging me... more Introduction Studies on brain structural and functional connectivity using modern neuroimaging methods have caught great attention in neuroscience research. Among these methods, brain network analysis with graph theory has been increasingly employed to layout the connective characteristics between different cortical regions and provide a global view of how brain works internally. Although the brain network analysis is potentially useful and powerful, the connective characteristics highly depend on the definition of cortical regions (i.e. nodes in graph theory). Conventionally, the anatomically and functionally cortical parcellations, such as Automatic Anatomical Labeling (AAL) and Brodmann atlases, have been used in most previous studies. In order to investigate the brain networks at different scales, a number of recent studies have attempted to divide the cortical regions of a given brain atlas into smaller parcels at multiple levels of granularity [1-3]. Although these proposed me...
The goal of this study is to use wireless sensor technologies to develop a smart clothes service ... more The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the "very good signal" interval. The average of the QRS sensitivity and po...
2012 Third International Conference on Intelligent Control and Information Processing, 2012
ABSTRACT The purpose of this study is to use wireless sensing technologies to develop a cognitive... more ABSTRACT The purpose of this study is to use wireless sensing technologies to develop a cognitive function analysis system based on Montreal Cognitive Assessment (MoCA). The system consists of three parts: (1) Data acquisition: We have designed seven kinds of games to assess five-oriented capabilities including naming, attention, abstraction, delayed recall and orientation. System collects automatically all operation steps, error count and finish time when tester plays the game. (2) Data analysis: try to analyze the collected data and calculate the quantitative results of mental indicators. (3) Feedback system: to screen the high-risk group of degradation of cognitive function to start the care plan earlier. This system can not only assist long-term care institutions to create new social activities for elder person, but also train their cognitive abilities and reduce the risk of dementia.
International Journal of Distributed Sensor Networks, 2015
The aim of this study is to construct an intelligent wireless sensing and control system to addre... more The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy log...
Computational and mathematical methods in medicine, 2015
The goal of this study is to use wireless sensor technologies to develop a smart clothes service ... more The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the "very good signal" interval. The average of the QRS sensitivity and pos...
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