Embedded BCI Rehabilitation System for Stroke
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摘要
In stroke rehabilitation,rehabilitation equipments can help with the training.But traditional equipments are not convenient to carry,which limits patients to use related rehabilitation techniques.To solve this kind of problem,a new embedded rehabilitation system based on brain computer interface(BCI)is proposed in this paper.The system is based on motor imagery(MI)therapy,in which electroencephalogram(EEG)is evoked by grasping motor imageries of left and right hands,then collected by a wearable device.The EEG is transmitted to a Raspberry Pie processing unit through Bluetooth and decoded as the instructions to control the equipment extension.Users experience the limb movement through the visual feedback so as to achieve active rehabilitation.A pilot study shows that the user can control the movement of the rehabilitation equipment through his mind,and the equipment is convenient to carry.The study provides a new way to stroke rehabilitation.
In stroke rehabilitation,rehabilitation equipments can help with the training.But traditional equipments are not convenient to carry,which limits patients to use related rehabilitation techniques.To solve this kind of problem,a new embedded rehabilitation system based on brain computer interface(BCI)is proposed in this paper.The system is based on motor imagery(MI)therapy,in which electroencephalogram(EEG)is evoked by grasping motor imageries of left and right hands,then collected by a wearable device.The EEG is transmitted to a Raspberry Pie processing unit through Bluetooth and decoded as the instructions to control the equipment extension.Users experience the limb movement through the visual feedback so as to achieve active rehabilitation.A pilot study shows that the user can control the movement of the rehabilitation equipment through his mind,and the equipment is convenient to carry.The study provides a new way to stroke rehabilitation.
In stroke rehabilitation,rehabilitation equipments can help with the training.But traditional equipments are not convenient to carry,which limits patients to use related rehabilitation techniques.To solve this kind of problem,a new embedded rehabilitation system based on brain computer interface(BCI)is proposed in this paper.The system is based on motor imagery(MI)therapy,in which electroencephalogram(EEG)is evoked by grasping motor imageries of left and right hands,then collected by a wearable device.The EEG is transmitted to a Raspberry Pie processing unit through Bluetooth and decoded as the instructions to control the equipment extension.Users experience the limb movement through the visual feedback so as to achieve active rehabilitation.A pilot study shows that the user can control the movement of the rehabilitation equipment through his mind,and the equipment is convenient to carry.The study provides a new way to stroke rehabilitation.
引文
[1]Liu X,Bi S,Gao G,et al.The effect of brain movement-based rehabilitation training on motor plasticity in stroke patients[D].Beijing:Chinese People’s Liberation Army Medical College,2014.(in Chinese)
[2]Takahashi M,Gouko M,Ito K.Fundamental research about electroencephalogram(EEG)-functional electrical stimulation(FES)rehabilitation system[C]∥IEEE International Conference on Rehabilitation Robotics,IEEE,1945:316-321.
[3]Cheng M,Ren Y,Gao X.The key technology of rehabilitation robot based on brain[J].Robot Technique and Application,2003(4):45-48.(in Chinese)
[4]Webb J,Xiao Z G,Aschenbrenner K P,et al.Towards a portable assistive arm exoskeleton for stroke patient rehabilitation controlled through a brain computer interface[C]∥IEEE Ras&Embs International Conference on Biomedical Robotics and Biomechatronics,IEEE,2012:1299-1304.
[5]Fu Q,Chen W,Yu J et al.Effects of MI therapy on upper limb motor function of stroke patients with hemiplegia[J].Chinese Journal of Rehabilitation Medicine,2010,25(1):53-55.(in Chinese)
[6]Xu B,Peng S,Song A,et al.Upper-limbrehabilitation robot based on MI EEG[J].Robot,2011,33(3):307-313.(in Chinese)
[7]Daly J J,Cheng R,Rogers J,et al.Feasibility of a new application of noninvasivebrain computer interface(BCI):a case study of training for recovery of volitional motor control after stroke[J].Journal of Neurologic Physical Therapy,2009,33(4):203.
[8]He B,Gao S,Yuan H,et al.Brain-computer interfaces[M]∥Neural Engineering.New York:Springer,2013:600.
[9]Hu J,Hou Z G,Chen Y X,et al.Lower limb rehabilitation robots and interactive control methods[J].Acta Automatica Sinica,2014,40(11):2377-2390.(in Chinese)
[10]Ying L I,Jia B.Design and implementation of serial port communication protocol based on state machine[J].Electronic Design Engineering,2012.(in Chinese)
[11]Lievesley R,Wozencroft M,Ewins D.The Emotiv EPOC neuroheadset:an inexpensive method of controlling assistive technologies using facial expressions and thoughts?[J].Journal of Assistive Technologies,2011,5(2):67-82.
[12]Tomida N,Tanaka T,Ono S,et al.Active data selection for MI EEG classification[J].Biomedical Engineering IEEE Transactions on,2015,62(2):458-67.
[13]Zhang Y N,Guo K,Kong W Z.Research and development of auxiliary rehabilitation system for lower limbs based on BCI[J].Journal of Hangzhou Dianzi University,2013,33(1):36-39.(in Chinese)
[14]Caria A,Weber C,Br9tz D,et al.Chronic stroke recovery after combined BCI training and physiotherapy:a case report[J].Psychophysiology,2011,48(4):578.
[15]Donati A R C,Solaiman S,Edgard M,et al.Long-term training with a brain-machine interface-based gait protocol induces partial neurological recovery in paraplegic patients[J].Scientific Reports,2016,6:30383.
[2]Takahashi M,Gouko M,Ito K.Fundamental research about electroencephalogram(EEG)-functional electrical stimulation(FES)rehabilitation system[C]∥IEEE International Conference on Rehabilitation Robotics,IEEE,1945:316-321.
[3]Cheng M,Ren Y,Gao X.The key technology of rehabilitation robot based on brain[J].Robot Technique and Application,2003(4):45-48.(in Chinese)
[4]Webb J,Xiao Z G,Aschenbrenner K P,et al.Towards a portable assistive arm exoskeleton for stroke patient rehabilitation controlled through a brain computer interface[C]∥IEEE Ras&Embs International Conference on Biomedical Robotics and Biomechatronics,IEEE,2012:1299-1304.
[5]Fu Q,Chen W,Yu J et al.Effects of MI therapy on upper limb motor function of stroke patients with hemiplegia[J].Chinese Journal of Rehabilitation Medicine,2010,25(1):53-55.(in Chinese)
[6]Xu B,Peng S,Song A,et al.Upper-limbrehabilitation robot based on MI EEG[J].Robot,2011,33(3):307-313.(in Chinese)
[7]Daly J J,Cheng R,Rogers J,et al.Feasibility of a new application of noninvasivebrain computer interface(BCI):a case study of training for recovery of volitional motor control after stroke[J].Journal of Neurologic Physical Therapy,2009,33(4):203.
[8]He B,Gao S,Yuan H,et al.Brain-computer interfaces[M]∥Neural Engineering.New York:Springer,2013:600.
[9]Hu J,Hou Z G,Chen Y X,et al.Lower limb rehabilitation robots and interactive control methods[J].Acta Automatica Sinica,2014,40(11):2377-2390.(in Chinese)
[10]Ying L I,Jia B.Design and implementation of serial port communication protocol based on state machine[J].Electronic Design Engineering,2012.(in Chinese)
[11]Lievesley R,Wozencroft M,Ewins D.The Emotiv EPOC neuroheadset:an inexpensive method of controlling assistive technologies using facial expressions and thoughts?[J].Journal of Assistive Technologies,2011,5(2):67-82.
[12]Tomida N,Tanaka T,Ono S,et al.Active data selection for MI EEG classification[J].Biomedical Engineering IEEE Transactions on,2015,62(2):458-67.
[13]Zhang Y N,Guo K,Kong W Z.Research and development of auxiliary rehabilitation system for lower limbs based on BCI[J].Journal of Hangzhou Dianzi University,2013,33(1):36-39.(in Chinese)
[14]Caria A,Weber C,Br9tz D,et al.Chronic stroke recovery after combined BCI training and physiotherapy:a case report[J].Psychophysiology,2011,48(4):578.
[15]Donati A R C,Solaiman S,Edgard M,et al.Long-term training with a brain-machine interface-based gait protocol induces partial neurological recovery in paraplegic patients[J].Scientific Reports,2016,6:30383.