This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named C...This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named Clarion)has been justified by,and validated against,psychological data,findings,and theoretical constructs.One important theoretical background for it is the dual-process theories,which led to its overall two-level structuring in a hybrid neuro-symbolic way.Furthermore,given the recent advances in AI and computing technology,LLMs are being incorporated into the model to better capture human intuition and instinct(and implicit processes in general),in order to further enhance Clarion.Integrating Clarion and LLMs can also help to develop AI systems that are more capable,more reliable,and more human-like.Overall,the paper advocates a multidisciplinary approach towards developing better models for cognitive science and for AI.展开更多
Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network con...Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.展开更多
The skill of robotic hand-eye coordination not only helps robots to deal with real time environment,but also afects the fundamental framework of robotic cognition.A number of approaches have been developed in the lite...The skill of robotic hand-eye coordination not only helps robots to deal with real time environment,but also afects the fundamental framework of robotic cognition.A number of approaches have been developed in the literature for construction of the robotic hand-eye coordination.However,several important features within infant developmental procedure have not been introduced into such approaches.This paper proposes a new method for robotic hand-eye coordination by imitating the developmental progress of human infants.The work employs a brain-like neural network system inspired by infant brain structure to learn hand-eye coordination,and adopts a developmental mechanism from psychology to drive the robot.The entire learning procedure is driven by developmental constraint： The robot starts to act under fully constrained conditions,when the robot learning system becomes stable,a new constraint is assigned to the robot.After that,the robot needs to act with this new condition again.When all the contained conditions have been overcome,the robot is able to obtain hand-eye coordination ability.The work is supported by experimental evaluation,which shows that the new approach is able to drive the robot to learn autonomously,and make the robot also exhibit developmental progress similar to human infants.展开更多
Consciousness research has been of great concern to philosophers, psychologists and neuroscientists in recent years. At the same time, consciousness has also attracted more and more interest of artificial intelligence...Consciousness research has been of great concern to philosophers, psychologists and neuroscientists in recent years. At the same time, consciousness has also attracted more and more interest of artificial intelligence （AI） researchers. In order to make more intelligent machines, many computing models of machine consciousness have been presented. Furthermore, self-consciousness has relevance to the level of intelligent functions. Hence, it is necessary to study self-consciousness in AI. This thesis, starting from biological consciousness, discusses some viewpoints of machine consciousness. Based on the discussions, we present a way to emulate self-consciousness and test this method via simulation experiments. Our results indicate that self-consciousness, which belongs to organisms, can he imitated by machines.展开更多
Cognitive functions are often studied using eventrelated potentials（ERPs）that are usually estimated by an averaging algorithm.Clearly,estimation of single-trial ERPs can provide researchers with many more details of...Cognitive functions are often studied using eventrelated potentials（ERPs）that are usually estimated by an averaging algorithm.Clearly,estimation of single-trial ERPs can provide researchers with many more details of cognitive activity than the averaging algorithm.A novel method to estimate single-trial ERPs is proposed in this paper.This method includes two key ideas.First,singular value decomposition was used to construct a matrix,which mapped singletrial electroencephalographic recordings（EEG）into a low-dimensional vector that contained little information from the spontaneous EEG.Second,we used the theory of compressed sensing to build a procedure to restore single-trial ERPs from this low-dimensional vector.ERPs are sparse or approximately sparse in the frequency domain.This fact allowed us to use the theory of compressed sensing.We verified this method in simulated and real data.Our method and dVCA（differentially variable component analysis）,another method of single-trial ERPs estimation,were both used to estimate single-trial ERPs from the same simulated data.Results demonstrated that our method significantly outperforms dVCA under various conditions of signal-to-noise ratio.Moreover,the single-trial ERPs estimated from the real data by our method are statistically consistent with the theories of cognitive science.展开更多
Sensory abnormalities are common in individuals with autism spectrum disorders (ASD) but are often difficult to assess using standard behavioral methods. Evoked potentials provide objective, non-invasive electrophysio...Sensory abnormalities are common in individuals with autism spectrum disorders (ASD) but are often difficult to assess using standard behavioral methods. Evoked potentials provide objective, non-invasive electrophysiological measures of neural sensory processing that could be useful for clinical and investigative studies of individuals with low-functioning autism who are unable to perform behavioral testing. Despite increased use, the reliability of sensory evoked potentials has not been established for individuals with low-functioning autism. Establishing reliability is important for validating the utility of sensory evoked potentials. In this study, we explored the feasibility of assessing the test-retest reliability of sensory evoked potentials using repeat recordings, acquired over 2.5- and 6-month intervals, from a minimally verbal adult with low-functioning autism. Repeat auditory and visual evoked potential recordings showed high test-retest reliability, with cross-correlation coefficients ≥ 0.80. This case demonstrates the feasibility of establishing test-retest reliability for individuals with low-functioning autism and supports the utility of sensory evoked potentials in clinical and investigative ASD studies.展开更多
Background:Within the dual stream model for language,the bilateral dorsal superior temporal gyrus(STG)is associated with spectro-temporal analysis while the mid-post superior temporal sulcus is associated with pro ces...Background:Within the dual stream model for language,the bilateral dorsal superior temporal gyrus(STG)is associated with spectro-temporal analysis while the mid-post superior temporal sulcus is associated with pro cessing of higher-level phonological codes.However,the true lateralization of functions needed for phonological discrimination at the word level remains unsettled.The aim of the present work was to determine if individuals with acute stroke primarily involving the left STG and middle temporal gyrus(MTG)demonstrated poorer discrimination(d’)between phonologically related words in a word-picture verification task than those with left hemisphere lesions outside the temporal lobe and compared to those with right hemisphere stroke.The latter would support a left bias and provide an estimate of the magnitude.Methods:One hundred fourteen individuals with acute stroke completed both acute magnetic resonance imaging and a word-picture verification task with phonological and semantic foils.Eighty-nine participants had left hemisphere stroke(51 included the temporal lobe).Twenty participants had right hemisphere stroke(14 included the temporal lobe).Five participants with bilateral stroke were included(3 included the bilateral temporal lobes).Quantile regression was performed controlling for overall lesion volume,age,and sex.Results:While more than half of patients performed the task well,patients with left temporal lobe lesions were more likely to perform poorly.Conclusions:These results confirm a role for the left superior temporal lobe,including the STG,in phonological processing during word recognition,and indicate that a subset of individuals(<50%)have varying degrees of left bias in discrimination of phonologically similar words in the STG.展开更多
CANDECOMP/PARAFAC(CP) tensor factorization is an efficient technique for incomplete tensor-data processing through capturing the multilinear latent factors. Based on the incorporate a sparsity-inducing prior over mult...CANDECOMP/PARAFAC(CP) tensor factorization is an efficient technique for incomplete tensor-data processing through capturing the multilinear latent factors. Based on the incorporate a sparsity-inducing prior over multiple latent factors and appropriate hyper-priors over all hyper-parameters, a Bayesian-based hierarchical probabilistic CP factorization model could be formed. By this way, the rank of the incomplete tensor can be determined automatically. In this paper, we explored the tensor completion method in processing incomplete multidimensional electroencephalogram(EEG) and magnetic resonance imaging(MRI) clinical data. The empirical results indicated that the Bayesian CP tensor factorization of incomplete data method can effectively recover EEG signal with missing data and denoised the noisy MRI data.展开更多
A novel method based on machine learning is developed to estimate event-related potentials from single trial electroencephalography. This paper builds a basic framework using classification and an optimization model b...A novel method based on machine learning is developed to estimate event-related potentials from single trial electroencephalography. This paper builds a basic framework using classification and an optimization model based on this framework for estimating event-related potentials. Then the SingleTrialEM algorithm is derived by introducing a logistic regression model, which could be obtained by training before SingleTrialEM is used, to instantiate the optimization model. The simulation tests demonstrate that the proposed method is correct and solid. The advantage of this method is verified by the comparison between this method and the Woody filter in simulation tests. Also, the cognitive test results are consistent with the conclusions of cognitive science.展开更多
Recent years have witnessed a rapid spread of multi-modality microblogs like Twitter and Sina Weibo composed of image, text and emoticon. Visual sentiment prediction of such microblog based social media has recently a...Recent years have witnessed a rapid spread of multi-modality microblogs like Twitter and Sina Weibo composed of image, text and emoticon. Visual sentiment prediction of such microblog based social media has recently attracted ever-increasing research focus with broad application prospect. In this paper, we give a systematic review of the recent advances and cutting-edge techniques for visual senti- ment analysis. To this end, in this paper we review the most recent works in this topic, in which detailed comparison as well as experimental evaluation are given over the cuttingedge methods. We further reveal and discuss the future trends and potential directions for visual sentiment prediction.展开更多
The pivot language approach for statistical machine translation(SMT) is a good method to break the resource bottleneck for certain language pairs. However, in the implementation of conventional approaches, pivotside c...The pivot language approach for statistical machine translation(SMT) is a good method to break the resource bottleneck for certain language pairs. However, in the implementation of conventional approaches, pivotside context information is far from fully utilized, resulting in erroneous estimations of translation probabilities. In this study, we propose two topic-aware pivot language approaches to use different levels of pivot-side context. The first method takes advantage of document-level context by assuming that the bridged phrase pairs should be similar in the document-level topic distributions. The second method focuses on the effect of local context. Central to this approach are that the phrase sense can be reflected by local context in the form of probabilistic topics, and that bridged phrase pairs should be compatible in the latent sense distributions. Then, we build an interpolated model bringing the above methods together to further enhance the system performance. Experimental results on French-Spanish and French-German translations using English as the pivot language demonstrate the effectiveness of topic-based context in pivot-based SMT.展开更多
Purpose–The working hypothesis,on which this paper is built,is that it is advantageous to look at protocols of robot rehabilitation in the general context of human-robot interaction in haptic dyads.The purpose of thi...Purpose–The working hypothesis,on which this paper is built,is that it is advantageous to look at protocols of robot rehabilitation in the general context of human-robot interaction in haptic dyads.The purpose of this paper is to propose a new method to detect and evaluate an index of active participation(AC index),underlying the performance of robot-assisted movements.This is important for avoiding the slacking phenomenon that affects robot therapy.Design/methodology/approach–The evaluation of the AC index is based on a novel technique of assistance which does not use constant or elastic forces but trains of small force impulses,with amplitude adapted to the level of impairment and a frequency of 2 Hz,which is suggested by recent results in the field of intermittent motor control.A preliminary feasibility test of the proposed method was carried out during a haptic reaching task in the absence of visual feedback,for a group of five stroke patients and an equal group of healthy subjects.Findings–The AC index appears to be stable and sensitive to training in both populations of subjects.Originality/value–The main original element of this study is the proposal of the new AC index of voluntary control associated with the new method of pulsed haptic interaction.展开更多
文摘This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named Clarion)has been justified by,and validated against,psychological data,findings,and theoretical constructs.One important theoretical background for it is the dual-process theories,which led to its overall two-level structuring in a hybrid neuro-symbolic way.Furthermore,given the recent advances in AI and computing technology,LLMs are being incorporated into the model to better capture human intuition and instinct(and implicit processes in general),in order to further enhance Clarion.Integrating Clarion and LLMs can also help to develop AI systems that are more capable,more reliable,and more human-like.Overall,the paper advocates a multidisciplinary approach towards developing better models for cognitive science and for AI.
基金supported by the Guangzhou Municipal Key Discipline in Medicine(2021-2023)the Guangzhou High-level Clinical Key Specialty,the Guangzhou Research-oriented Hospital,the Innovative Clinical Technique of Guangzhou(2024-2026)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(grant number 2022A1515011567,2020A1515110565)the Guangzhou Science,Technology Planning Project(grant number 202201010714,202103000032)the National Natural Science Foundation of China(grant number 82471546)the Guangdong College Students Innovation and Entrepreneurship Training Project(grant number S202310570038)the Guangzhou Health Science and Technology Project(grant number 20231A010038)the Guangzhou Traditional Chinese Medicine and Integrated Traditional Chinese and Western Medicine Technology Project(grant number:20232A010013)the Science and Technology Plan Project of Guangzhou(2023A03J0842).
文摘Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.
基金supported by National Natural Science Foundation of China (No.6120333661273338 and 61003014)Major State Basic Research Development Program of China (973 Program)(No.2013CB329502)
文摘The skill of robotic hand-eye coordination not only helps robots to deal with real time environment,but also afects the fundamental framework of robotic cognition.A number of approaches have been developed in the literature for construction of the robotic hand-eye coordination.However,several important features within infant developmental procedure have not been introduced into such approaches.This paper proposes a new method for robotic hand-eye coordination by imitating the developmental progress of human infants.The work employs a brain-like neural network system inspired by infant brain structure to learn hand-eye coordination,and adopts a developmental mechanism from psychology to drive the robot.The entire learning procedure is driven by developmental constraint： The robot starts to act under fully constrained conditions,when the robot learning system becomes stable,a new constraint is assigned to the robot.After that,the robot needs to act with this new condition again.When all the contained conditions have been overcome,the robot is able to obtain hand-eye coordination ability.The work is supported by experimental evaluation,which shows that the new approach is able to drive the robot to learn autonomously,and make the robot also exhibit developmental progress similar to human infants.
基金supported by National Basic Research Program of China(973 program)(No.2013CB329502)National Natural Science Foundation of China(No.61273338)
文摘Consciousness research has been of great concern to philosophers, psychologists and neuroscientists in recent years. At the same time, consciousness has also attracted more and more interest of artificial intelligence （AI） researchers. In order to make more intelligent machines, many computing models of machine consciousness have been presented. Furthermore, self-consciousness has relevance to the level of intelligent functions. Hence, it is necessary to study self-consciousness in AI. This thesis, starting from biological consciousness, discusses some viewpoints of machine consciousness. Based on the discussions, we present a way to emulate self-consciousness and test this method via simulation experiments. Our results indicate that self-consciousness, which belongs to organisms, can he imitated by machines.
基金supported by National Basic Research Development Program (973 program) of China (2012CB825500,2011CB707800)National Natural Science Foundation of China (31271168)Natural Science Foundation of Fujian Province, China (2011J01344)
文摘Cognitive functions are often studied using eventrelated potentials（ERPs）that are usually estimated by an averaging algorithm.Clearly,estimation of single-trial ERPs can provide researchers with many more details of cognitive activity than the averaging algorithm.A novel method to estimate single-trial ERPs is proposed in this paper.This method includes two key ideas.First,singular value decomposition was used to construct a matrix,which mapped singletrial electroencephalographic recordings（EEG）into a low-dimensional vector that contained little information from the spontaneous EEG.Second,we used the theory of compressed sensing to build a procedure to restore single-trial ERPs from this low-dimensional vector.ERPs are sparse or approximately sparse in the frequency domain.This fact allowed us to use the theory of compressed sensing.We verified this method in simulated and real data.Our method and dVCA（differentially variable component analysis）,another method of single-trial ERPs estimation,were both used to estimate single-trial ERPs from the same simulated data.Results demonstrated that our method significantly outperforms dVCA under various conditions of signal-to-noise ratio.Moreover,the single-trial ERPs estimated from the real data by our method are statistically consistent with the theories of cognitive science.
文摘Sensory abnormalities are common in individuals with autism spectrum disorders (ASD) but are often difficult to assess using standard behavioral methods. Evoked potentials provide objective, non-invasive electrophysiological measures of neural sensory processing that could be useful for clinical and investigative studies of individuals with low-functioning autism who are unable to perform behavioral testing. Despite increased use, the reliability of sensory evoked potentials has not been established for individuals with low-functioning autism. Establishing reliability is important for validating the utility of sensory evoked potentials. In this study, we explored the feasibility of assessing the test-retest reliability of sensory evoked potentials using repeat recordings, acquired over 2.5- and 6-month intervals, from a minimally verbal adult with low-functioning autism. Repeat auditory and visual evoked potential recordings showed high test-retest reliability, with cross-correlation coefficients ≥ 0.80. This case demonstrates the feasibility of establishing test-retest reliability for individuals with low-functioning autism and supports the utility of sensory evoked potentials in clinical and investigative ASD studies.
基金supported by National Institutes of Health/National Institute on Deafness and Other Communication Disorders(NIH/NIDCD)(Nos.P50 DC014664 and R01 DC05375)funded by NIH grant(No.1S10OD021648).
文摘Background:Within the dual stream model for language,the bilateral dorsal superior temporal gyrus(STG)is associated with spectro-temporal analysis while the mid-post superior temporal sulcus is associated with pro cessing of higher-level phonological codes.However,the true lateralization of functions needed for phonological discrimination at the word level remains unsettled.The aim of the present work was to determine if individuals with acute stroke primarily involving the left STG and middle temporal gyrus(MTG)demonstrated poorer discrimination(d’)between phonologically related words in a word-picture verification task than those with left hemisphere lesions outside the temporal lobe and compared to those with right hemisphere stroke.The latter would support a left bias and provide an estimate of the magnitude.Methods:One hundred fourteen individuals with acute stroke completed both acute magnetic resonance imaging and a word-picture verification task with phonological and semantic foils.Eighty-nine participants had left hemisphere stroke(51 included the temporal lobe).Twenty participants had right hemisphere stroke(14 included the temporal lobe).Five participants with bilateral stroke were included(3 included the bilateral temporal lobes).Quantile regression was performed controlling for overall lesion volume,age,and sex.Results:While more than half of patients performed the task well,patients with left temporal lobe lesions were more likely to perform poorly.Conclusions:These results confirm a role for the left superior temporal lobe,including the STG,in phonological processing during word recognition,and indicate that a subset of individuals(<50%)have varying degrees of left bias in discrimination of phonologically similar words in the STG.
基金supported by the JSPS KAKENHI,Japan(Grant Nos.17K00326 and 18K04178)the National Natural Science Foundation of China(Grant Nos.61773129,61633010)the JST CREST,Japan(Grant No.JPMJCR1784)。
文摘CANDECOMP/PARAFAC(CP) tensor factorization is an efficient technique for incomplete tensor-data processing through capturing the multilinear latent factors. Based on the incorporate a sparsity-inducing prior over multiple latent factors and appropriate hyper-priors over all hyper-parameters, a Bayesian-based hierarchical probabilistic CP factorization model could be formed. By this way, the rank of the incomplete tensor can be determined automatically. In this paper, we explored the tensor completion method in processing incomplete multidimensional electroencephalogram(EEG) and magnetic resonance imaging(MRI) clinical data. The empirical results indicated that the Bayesian CP tensor factorization of incomplete data method can effectively recover EEG signal with missing data and denoised the noisy MRI data.
基金supported by the National Natural Science Foundation of China (Grant No. 30670669)National Basic Research Program of China (Grant No. 2007CB947703)+1 种基金Natural Science Foundation of Fujian Province (Grant No. 2011J01344)Science and Technology Development Foundation of Fuzhou University (Grant No. 2009-XQ-25)
文摘A novel method based on machine learning is developed to estimate event-related potentials from single trial electroencephalography. This paper builds a basic framework using classification and an optimization model based on this framework for estimating event-related potentials. Then the SingleTrialEM algorithm is derived by introducing a logistic regression model, which could be obtained by training before SingleTrialEM is used, to instantiate the optimization model. The simulation tests demonstrate that the proposed method is correct and solid. The advantage of this method is verified by the comparison between this method and the Woody filter in simulation tests. Also, the cognitive test results are consistent with the conclusions of cognitive science.
文摘Recent years have witnessed a rapid spread of multi-modality microblogs like Twitter and Sina Weibo composed of image, text and emoticon. Visual sentiment prediction of such microblog based social media has recently attracted ever-increasing research focus with broad application prospect. In this paper, we give a systematic review of the recent advances and cutting-edge techniques for visual senti- ment analysis. To this end, in this paper we review the most recent works in this topic, in which detailed comparison as well as experimental evaluation are given over the cuttingedge methods. We further reveal and discuss the future trends and potential directions for visual sentiment prediction.
基金Project supported by the National High-Tech R&D Program of China(No.2012BAH14F03)the National Natural Science Foundation of China(Nos.61005052 and 61303082)+2 种基金the Re-search Fund for the Doctoral Program of Higher Education of China(No.20120121120046)the Natural Science Foundation of Fujian Province of China(No.2011J01360)the Funda-mental Research Funds for the Central Universities,China(No.2010121068)
文摘The pivot language approach for statistical machine translation(SMT) is a good method to break the resource bottleneck for certain language pairs. However, in the implementation of conventional approaches, pivotside context information is far from fully utilized, resulting in erroneous estimations of translation probabilities. In this study, we propose two topic-aware pivot language approaches to use different levels of pivot-side context. The first method takes advantage of document-level context by assuming that the bridged phrase pairs should be similar in the document-level topic distributions. The second method focuses on the effect of local context. Central to this approach are that the phrase sense can be reflected by local context in the form of probabilistic topics, and that bridged phrase pairs should be compatible in the latent sense distributions. Then, we build an interpolated model bringing the above methods together to further enhance the system performance. Experimental results on French-Spanish and French-German translations using English as the pivot language demonstrate the effectiveness of topic-based context in pivot-based SMT.
基金Istituto Italiano di Tecnologia,RBCS department,Marie Curie Integration Grant FP7-PEOPLE-2012-CIG-334201(REMAKE)ACIRAS(Ausili CIbernetici Riabilitativi per la diagnosi e la valutazione quantitativa della disabilitamotoria dell’Arto Superiore nei bambini e negli adulti)Project,Regione Liguria,W911QY-12-C-0078 Project DoD,USA“Consequences of Loading on Postural-Focal Dynamics.”。
文摘Purpose–The working hypothesis,on which this paper is built,is that it is advantageous to look at protocols of robot rehabilitation in the general context of human-robot interaction in haptic dyads.The purpose of this paper is to propose a new method to detect and evaluate an index of active participation(AC index),underlying the performance of robot-assisted movements.This is important for avoiding the slacking phenomenon that affects robot therapy.Design/methodology/approach–The evaluation of the AC index is based on a novel technique of assistance which does not use constant or elastic forces but trains of small force impulses,with amplitude adapted to the level of impairment and a frequency of 2 Hz,which is suggested by recent results in the field of intermittent motor control.A preliminary feasibility test of the proposed method was carried out during a haptic reaching task in the absence of visual feedback,for a group of five stroke patients and an equal group of healthy subjects.Findings–The AC index appears to be stable and sensitive to training in both populations of subjects.Originality/value–The main original element of this study is the proposal of the new AC index of voluntary control associated with the new method of pulsed haptic interaction.
