This paper considers the design of iterative receivers for space-frequencyblock-coded orthogonal frequency division multiplexing (SFBC-OFDM) systems in unknown wirelessdispersive fading channels. An iterative joint ch...This paper considers the design of iterative receivers for space-frequencyblock-coded orthogonal frequency division multiplexing (SFBC-OFDM) systems in unknown wirelessdispersive fading channels. An iterative joint channel estimation and symbol detection algorithm isderived. In the algorithm, the channel estimator performs alternately in two modes. During thetraining mode, the channel state information (CSI) is obtained by a discrete-Fourier-transform-basedchannel estimator and the noise variance and covariance matrix of the channel response is estimatedby the proposed method. In the data transmission mode, the CSI and transmitted data is obtainediteratively. In order to suppress the error propagation caused by a random error in identifyingsymbols, a simple error propagation detection criterion is proposed and an adaptive training schemeis applied to suppress the error propagation. Both theoretical analysis and simulation results showthat this algorithm gives better bit-error-rate performance and saves the overhead of OFDM systems.展开更多
In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts ...In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.展开更多
Clinical Study and automatic diagnosis of electrocardiogram(ECG)data always remain a challenge in diagnosing cardiovascular activities.The analysis of ECG data relies on various factors like morphological features,cla...Clinical Study and automatic diagnosis of electrocardiogram(ECG)data always remain a challenge in diagnosing cardiovascular activities.The analysis of ECG data relies on various factors like morphological features,classification techniques,methods or models used to diagnose and its performance improvement.Another crucial factor in themethodology is howto train the model for each patient.Existing approaches use standard training model which faces challenges when training data has variation due to individual patient characteristics resulting in a lower detection accuracy.This paper proposes an adaptive approach to identify performance improvement in building a training model that analyze global trainingmethodology against an individual training methodology and identifying a gap between them.We provide our investigation and comparative study on these methods and model with standard classification techniques with basic morphological features and Heart RateVariability(HRV)thatmay aid real time application.This approach helps in analyzing and evaluating the performance of different techniques and can suggests adoption of a best model identification with efficient technique and efficient attribute set for real-time systems.展开更多
Objective: Qi Gong is a mind-and-body intervention to improve health and relieve disease conditions,which has been practiced for thousands of years. Lack of quantitative measures to monitor the quality and progress of...Objective: Qi Gong is a mind-and-body intervention to improve health and relieve disease conditions,which has been practiced for thousands of years. Lack of quantitative measures to monitor the quality and progress of Qi Gong practice has hindered the high-quality study to evaluate its health benefits.Methods: To develop such quantitative measures, vital sign changes in Qi Gong meditation practice of a single individual were monitored for 5 years by wearable devices.Results: This retrospective and exploratory analysis revealed significant changes in blood oxygen saturation, pulse rate, respiration rate, and perfusion index in response to Qi Gong practice and physiological adaptation to its long-term training. Among the physiological changes in vital signs, a physiological state with a significant 2-fold increase in pulse-respiration rate ratio was detected during Qi Gong meditation while the ratios were maintained at 4 under resting, sleeping, and mild cycling conditions.Conclusion: This is an inaugural report of a five-year longitudinal observation of this kind. Once validated in a well-designed cohort study, these non-invasive and easily obtained vital signs may be used as biomarkers to assess the adherence to breathing control during Qi Gong practice and can be applied to quantify the quality of Qi Gong practice in clinical trials with Qi Gong intervention.展开更多
The existing fixed gait lower limb rehabilitation robots perform a predetermined walking trajectory for patients,ignoring their residual muscle strength.To enhance patient participation and safety in training,this pap...The existing fixed gait lower limb rehabilitation robots perform a predetermined walking trajectory for patients,ignoring their residual muscle strength.To enhance patient participation and safety in training,this paper aims to develop a lower limb rehabilitation robot with adaptive gait training capability relying on human–robot interaction force measurement.Firstly,a novel lower limb rehabilitation robot system with several active and passive driven joints is developed,and 2 face-to-face mounted cantilever beam force sensors are employed to measure the human–robot interaction forces.Secondly,a dynamic model of the rehabilitation training robot is constructed to estimate the driven forces of the human lower leg in a completely passive state.Thereafter,based on the theoretical moment from the dynamics and the actual joint interaction force collected by the sensors,an adaptive gait adjustment method is proposed to achieve the goal of adapting to the wearer’s movement intention.Finally,interactive experiments are carried out to validate the effectiveness of the developed rehabilitation training robot system.The proposed rehabilitation training robot system with adaptive gaits offers great potential for future highquality rehabilitation training,e.g.,improving participation and safety.展开更多
China's brain-computer interface trials unlock new frontiers in neurotechnology With a tiny,coin-sized device implanted in his brain,one 37-year-old man,who lost all four limbs in a horrific high-voltage accident ...China's brain-computer interface trials unlock new frontiers in neurotechnology With a tiny,coin-sized device implanted in his brain,one 37-year-old man,who lost all four limbs in a horrific high-voltage accident 13 years ago,can now type messages,send texts and even play video games using nothing but his thoughts.The miracle was achieved after a brain-computer interface(BCI)operation and three weeks of adaptive training.展开更多
A stronger canonical model was developed to improve the performance of automatic pronunciation evaluations. Three different strategies were investigated with speaker adaptive training to normalize variations among spe...A stronger canonical model was developed to improve the performance of automatic pronunciation evaluations. Three different strategies were investigated with speaker adaptive training to normalize variations among speakers, minimum phone error training to identify easily confused phones and maximum likelihood linear regression （MLLR） adaptation to compensate for accent variations between native and non-native speakers. The three schemes were combined to improve the correlation coefficient between machine scores and human scores from 0.651 to 0.679 on the sentence level and from 0.788 to 0.822 on the speaker level.展开更多
文摘This paper considers the design of iterative receivers for space-frequencyblock-coded orthogonal frequency division multiplexing (SFBC-OFDM) systems in unknown wirelessdispersive fading channels. An iterative joint channel estimation and symbol detection algorithm isderived. In the algorithm, the channel estimator performs alternately in two modes. During thetraining mode, the channel state information (CSI) is obtained by a discrete-Fourier-transform-basedchannel estimator and the noise variance and covariance matrix of the channel response is estimatedby the proposed method. In the data transmission mode, the CSI and transmitted data is obtainediteratively. In order to suppress the error propagation caused by a random error in identifyingsymbols, a simple error propagation detection criterion is proposed and an adaptive training schemeis applied to suppress the error propagation. Both theoretical analysis and simulation results showthat this algorithm gives better bit-error-rate performance and saves the overhead of OFDM systems.
基金Project(61175128) supported by the National Natural Science Foundation of ChinaProject(2008AA040203) supported by the National High Technology Research and Development Program of ChinaProject(QC2010009) supported by the Natural Science Foundation of Heilongjiang Province,China
文摘In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.
基金The authors extend their appreciation to King Saud University for funding this work through Researchers Supporting Project Number(RSP-2021/387),King Saud University,Riyadh,Saudi Arabia.
文摘Clinical Study and automatic diagnosis of electrocardiogram(ECG)data always remain a challenge in diagnosing cardiovascular activities.The analysis of ECG data relies on various factors like morphological features,classification techniques,methods or models used to diagnose and its performance improvement.Another crucial factor in themethodology is howto train the model for each patient.Existing approaches use standard training model which faces challenges when training data has variation due to individual patient characteristics resulting in a lower detection accuracy.This paper proposes an adaptive approach to identify performance improvement in building a training model that analyze global trainingmethodology against an individual training methodology and identifying a gap between them.We provide our investigation and comparative study on these methods and model with standard classification techniques with basic morphological features and Heart RateVariability(HRV)thatmay aid real time application.This approach helps in analyzing and evaluating the performance of different techniques and can suggests adoption of a best model identification with efficient technique and efficient attribute set for real-time systems.
文摘Objective: Qi Gong is a mind-and-body intervention to improve health and relieve disease conditions,which has been practiced for thousands of years. Lack of quantitative measures to monitor the quality and progress of Qi Gong practice has hindered the high-quality study to evaluate its health benefits.Methods: To develop such quantitative measures, vital sign changes in Qi Gong meditation practice of a single individual were monitored for 5 years by wearable devices.Results: This retrospective and exploratory analysis revealed significant changes in blood oxygen saturation, pulse rate, respiration rate, and perfusion index in response to Qi Gong practice and physiological adaptation to its long-term training. Among the physiological changes in vital signs, a physiological state with a significant 2-fold increase in pulse-respiration rate ratio was detected during Qi Gong meditation while the ratios were maintained at 4 under resting, sleeping, and mild cycling conditions.Conclusion: This is an inaugural report of a five-year longitudinal observation of this kind. Once validated in a well-designed cohort study, these non-invasive and easily obtained vital signs may be used as biomarkers to assess the adherence to breathing control during Qi Gong practice and can be applied to quantify the quality of Qi Gong practice in clinical trials with Qi Gong intervention.
基金supported in part by the National Natural Science Foundation of China under Grants 62373353,and 62033013in part by Youth Innovation Promotion Association CAS(2019138).
文摘The existing fixed gait lower limb rehabilitation robots perform a predetermined walking trajectory for patients,ignoring their residual muscle strength.To enhance patient participation and safety in training,this paper aims to develop a lower limb rehabilitation robot with adaptive gait training capability relying on human–robot interaction force measurement.Firstly,a novel lower limb rehabilitation robot system with several active and passive driven joints is developed,and 2 face-to-face mounted cantilever beam force sensors are employed to measure the human–robot interaction forces.Secondly,a dynamic model of the rehabilitation training robot is constructed to estimate the driven forces of the human lower leg in a completely passive state.Thereafter,based on the theoretical moment from the dynamics and the actual joint interaction force collected by the sensors,an adaptive gait adjustment method is proposed to achieve the goal of adapting to the wearer’s movement intention.Finally,interactive experiments are carried out to validate the effectiveness of the developed rehabilitation training robot system.The proposed rehabilitation training robot system with adaptive gaits offers great potential for future highquality rehabilitation training,e.g.,improving participation and safety.
文摘China's brain-computer interface trials unlock new frontiers in neurotechnology With a tiny,coin-sized device implanted in his brain,one 37-year-old man,who lost all four limbs in a horrific high-voltage accident 13 years ago,can now type messages,send texts and even play video games using nothing but his thoughts.The miracle was achieved after a brain-computer interface(BCI)operation and three weeks of adaptive training.
基金Supported by the National High-Tech Research and Development (863) Program of China (No. 2008AA01Z118)
文摘A stronger canonical model was developed to improve the performance of automatic pronunciation evaluations. Three different strategies were investigated with speaker adaptive training to normalize variations among speakers, minimum phone error training to identify easily confused phones and maximum likelihood linear regression （MLLR） adaptation to compensate for accent variations between native and non-native speakers. The three schemes were combined to improve the correlation coefficient between machine scores and human scores from 0.651 to 0.679 on the sentence level and from 0.788 to 0.822 on the speaker level.
