面向孤独症辅助康复的交互机器人系统
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摘要
为解决孤独症儿童在康复训练过程中持续时间长、医疗费用高等问题,设计并实现了一种面向孤独症患儿的辅助康复医疗交互机器人系统。将机器人控制技术与情感计算相结合,设计了多模态人机交互的情感认知训练方式。提出了基于生理信号灵敏度因子的情感计算模型,根据径向基神经网络构建的一种基于多通道生理信号融合的灵敏度因子对康复认知训练过程进行修正。通过在北京市某社区孤独症儿童康复机构进行的实验测试,验证了该系统对辅助患者的康复治疗过程的可行性与有效性。
To solve the problem that children with autism have long duration and high medical expenses in the process of rehabilitation training,a human-computer interactive medical robot system for children with autism was designed and implemented.Through combining robot control technology with emotional computing,the multi-modal humancomputer interaction emotional cognitive training method was designed.An emotion calculation model based on physiological signal sensitivity factor was proposed.A sensitivity factor based on multi-channel physiological signal fusion was used to modify the rehabilitation cognitive training process based on Radial Basis Function Neural Network(RBF_NN).Through the field test in a rehabilitation institution for autistic children in a community in Beijing,the feasibility and effectiveness of the system's rehabilitation treatment for assisted patients was verified.
To solve the problem that children with autism have long duration and high medical expenses in the process of rehabilitation training,a human-computer interactive medical robot system for children with autism was designed and implemented.Through combining robot control technology with emotional computing,the multi-modal humancomputer interaction emotional cognitive training method was designed.An emotion calculation model based on physiological signal sensitivity factor was proposed.A sensitivity factor based on multi-channel physiological signal fusion was used to modify the rehabilitation cognitive training process based on Radial Basis Function Neural Network(RBF_NN).Through the field test in a rehabilitation institution for autistic children in a community in Beijing,the feasibility and effectiveness of the system's rehabilitation treatment for assisted patients was verified.
引文
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[3]KONSTANTINIDIS E I,LUNESKI A,FRANTZIDIS C A,et al.A proposed framework of an interactive semi-virtual environment for enhanced education of children with autism spectrum disorders[C]//Proceedings of the IEEE International Symposium on Computer-Based Medical Systems.Washinton,D.C.,USA:IEEE,2009:1-6.
[4]DE SILVA P,TADANO K,SAITO A,et al.The development of an assistive robot for improving the joint attention of autistic children[C]//Proceedings of the IEEE International Conference on Rehabilitation Robotics.Washinton,D.C.,USA:IEEE,2009:694-700.
[5]BRATEC S M,XIE X,SCHMID G,et al.Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses.[J].Neuroimage,2015,123(12):138-148.
[6]Xu Guozheng,Song Aiguo,Gao Xiang,et al.Robot-assisted clinical rehabilitation experiment based on anxiety emotion and hybrid control[J].Journal of Scientific Instrument,2017(10):2364-2372(in Chinese).[徐国政,宋爱国,高翔,等.基于焦虑情绪与混杂控制的机器人辅助临床康复实验[J].仪器仪表学报,2017(10):2364-2372.]
[7]SU Chong,LI Hongguang.Interactive evolutionary computing method based on affective learning agent[J].Computer Integrated Manufacturing Systems,2012,18(3):617-625(in Chinese).[宿翀,李宏光.基于情感学习智能体的交互式进化计算方法[J].计算机集成制造系统,2012,18(3):617-625.]
[8]SLOMAN A.Varieties of affect and the CogAff architecture schema[EB/OL].[2018-08-27].http://courses.media.mit.edu/2003spring/mas963/sloman-aisb01.pdf.
[9]RODRIGUES H R S,MASCARENHAS S,DIAS O J,et al.A process model of empathy for virtual agents[J].Interacting with Computers,2015,27(4):371.
[10]YANARU T,HIROTJA T,KIMURA N.An emotion-processing system based on fuzzy inference and its subjective observations[J].Information Sciences,1995,101(S3/S4):217-247.
[11]YANG H,PAN Z,LIU G.Comprehensive computational model of emotions[J].Journal of Computer Research&Development,2008,45(4):579-587.
[12]LU Fei,TIAN Guohui,LIU Guoliang,et al.A composed global localization system for service robot in intelligent space based on particle filter algorithm and WIFI fingerprint localization[J].Robot,2016,38(2):178-184(in Chinese).[路飞,田国会,刘国良,等.智能空间下基于WIFI指纹定位与粒子滤波的服务机器人复合全局定位系统设计[J].机器人,2016,38(2):178-184.]
[13]MOODY J.Learning with localized receptive fields[C]//Proceedings of the Connectionist Models Summer School,San Francisco,Cal.,USA:Morgan Kaufmonn Publication,1988.
[14]CANNON W B.The James-Lange theory of emotions:A critical examination and an alternative theory[J].The American journal of psychology,1927,39(4):106-124.
[15]PAPEZ J W.A proposed mechanism of emotion[J].Archives of Neurology&Psychiatry,1937,38(4):725-743.
[16]ANDREASSI J L,LEYH T S.Molecular functions of conserved aspects of the GHMP kinase family[J].Biochemistry,2004,43(46):14594-14601.
[17]PICARD R W,VYZAS E,HEALEY J.Toward machine emotional intelligence:Analysis of affective physiological state[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2001(10):1175-1191.
[18]KEARY A,WALSH P.How affective computing could complement and advance the quantified self[C]//Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine.Washington,D.C.,USA:IEEE,2015:24-31.
[19]GROSS J J.Emotion regulation:affective,cognitive,and social consequences[J].Psychophysiology,2002,39(3):281-291.
[20]JUDGE T A,HELLER D,MOUNT M K.Five-factor model of personality and job satisfaction:a meta-analysis[J].Journal of Applied Psychology,2002,87(3):530.
[21]TERRACCIANO A,MCCRAE R R,BRANT L J,et al.Hierarchical linear modeling analyses of the NEO-PI-R scales in the Baltimore Longitudinal study of aging[J].Psychology and Aging,2016,20(3):493.
[22]HARRIS L T.Invisible mind:flexible social cognition and dehumanization[M].Boston,Mass.,USA:MIT Press,2017.
[23]VANN S D.Dismantling the Papez circuit for memory in rats[J].Elife,2013,2(12):e00736.
[24]YU S N,CHENG J C.A wireless physiological signal monitoring system with integrated bluetooth and WIFI technologies[C]//Proceedings of the International Conference of the Engineering in Medicine&Biology Society,Berlin,Germany:Springer-Verlag,2005:2203.