CN101057795A - Artificial hand using muscle electrical and electroencephalogram cooperative control and controlling method thereof - Google Patents
Artificial hand using muscle electrical and electroencephalogram cooperative control and controlling method thereof Download PDFInfo
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Abstract
The invention relates to an artificial hand controlled by myoelectric and brain, comprising myoelectric and brain electrode, myoelectric and brain signal treatment module, A/ D conversion data collection, myoelectric signal moving module identification and track prediction module, electrical artificial hand, touch and feel sensor, systematic feedback stimulation device, force and speed moderating module. The controlling method comprises following steps: collecting and enlarging myoelectric signal; collecting characteristic and identifying module; checking caught object condition, if the objection is not caught, a certain kind of physical stimulation signal will be sent to operator; checking brain information; outputting information to force and speed moderating module; output information controlling the electrical artificial hand. The invention overcomes limit of only taking myoelectric signal as signal source.
Description
Technical field
The present invention relates to a kind of substituent and control method thereof of staff, particularly a kind of prosthetic hand and control method thereof that adopts myoelectricity and brain electricity Collaborative Control.
Background technology
Since World War II, the prosthetic hand technology obtained remarkable development especially the myoelectric-controlled prosthesis hands obtained widely using.The myoelectric limb hands is a kind of person machine system who utilizes bio electricity control, by the information exchange that human body electromyographic signal and artificial limb carry out, and the opening and closing movement of control prosthetic hand.
The development of myoelectric limb hands has both at home and abroad had certain basis, as the automatic SUVA induction hands of German Otto Bock development, controls the grip and the opening and closing speed of prosthetic hand by the power of electromyographic signal, makes simple, the nature of grasping movement.Present myoelectric limb hands also has the feedback function of integrated multiple sensors, has sense of touch and sliding function of feeling as prosthetic hand, can the Self Adaptive Control grip grasp object.
In Chinese patent literature CN1582866A, disclosed a kind of tactile myoelectrical bionic electrically powered hand of being with, sense of touch organically combines with the myoelectricity control of doing evil through another person with doing evil through another person, make the control procedure of doing evil through another person receive the dual restriction of electromyographic signal and sensory signal, reached more satisfactory bionical control.
But only adopt electromyographic signal as the artificial limb signal source certain limitation to be arranged also: the manipulator works long hours, and muscle is easy to generate fatigue; The fatigue of muscle, the change of electrode position, physical ability fluctuation etc. all can make the eigenvalue of electromyographic signal change, and cause the reproducibility of the accuracy of control and information pattern bad; In addition, high amputation patient or when causing amyotrophy because of paralysis can not provide enough myoelectricity control informations.
Summary of the invention
Task of the present invention is to adopt the control of the way realization of electromyographic signal and evoked brain potential Collaborative Control to prosthetic hand, overcomes only with the limitation of electromyographic signal as the artificial limb signal source.
Adopt the prosthetic hand of myoelectricity and brain electricity Collaborative Control, electromyographic signal processing module, the collection of A/D translation data that comprises the power-collecting electrode that is contained on the residual arm, answers with electrode pair, finish identification of electromyographic signal motor pattern and trajectory predictions module by computer, export electronic prosthetic hand, the tactile and slip sense integrated transducer that control signal drives through drive circuit by pattern recognition and trajectory predictions module, it is characterized in that, also comprise:
The one system feedback stimulating apparatus that whether starts according to tactile and slip sense integrated transducer signal deciding;
Trigger the power-collecting electrode of brain electricity by stimulating apparatus;
The EEG Processing module of answering with electrode pair;
Brain electricity A/D translation data is gathered;
Strength and speed adjustment module that output signal links to each other with electronic prosthetic hand drive circuit.
Adopt the method for myoelectricity and brain electricity Collaborative Control prosthetic hand, comprise the following steps:
(1) system at first gathers electromyographic signal by processing module and amplifies;
(2) then electromyographic signal is carried out feature extraction and pattern recognition;
(3) the tactile and slip sense integrated transducer records the signal of the extracting situation of being grabbed object,
(4) grabbed thing when the signal reflection and do not grasp, the feedback stimulating apparatus is given the physical stimulation signal of manipulator's one definite form;
(5) power-collecting electrode of brain electricity detects the brain electric information that is brought out by the physical stimulation signal;
(6) EEG signals outputs to strength and speed adjustment module after the EEG Processing resume module;
(7) output signal of adjustment module is finished the further control to electronic hands.
Above-mentioned stating in the step (1) in the collection to electromyographic signal amplified and filter function divides the level Four realization; The first order adopts instrumentation amplifier that the bio signal that collects is amplified tens of times; Passive double T trap circuit is adopted in the second level, and the resistance of circuit and electric capacity are through overmatching, and filtering 50Hz disturbs well; The third level is adopted high pass filter, the DC potential that the filtering polarization potential produces; The fourth stage adopts low pass filter, the filtering High-frequency Interference, and the cut-off frequency of EEG signals is arranged on 30Hz, and the cut-off frequency of electromyographic signal is located at 500Hz; This wave filter also can be used as the anti-repeatedly wave filter that mixes before the A/D conversion; From the security consideration of human body, in circuit, adopt the high-speed figure light-coupled isolation.
The feature extraction way and the LVQ network classifier that adopt wavelet packet and principal component neural networks to combine in the above-mentioned steps (2) carry out pattern recognition to experimenter's action.
Carry out signal extraction and pattern recognition to clenching fist, open up fist, arm inward turning, arm outward turning and five kinds of states of natural relaxation in the above-mentioned steps (2).
The mode of physical stimulation can be electricity irritation or vibration in the above-mentioned steps (4).
It only is the limitation of signal source with the electromyographic signal that the scheme of employing flesh brain electricity Collaborative Control has overcome effectively, evoked brain potential has been carried out further exploratory development, for prosthetic hand realizes that finishing more, more complicated action pattern provides valid approach, makes the function of prosthetic hand more approach staff.
Description of drawings
The Collaborative Control principle schematic of Fig. 1 myoelectricity, EEG signals;
Fig. 2 bio signal acquisition system;
The specific embodiment
System at first gathers electromyographic signal by processing module, and as shown in Figure 2, the amplification of acquisition system and filter function divide level Four to realize, the first order adopts instrumentation amplifier that the bio signal that collects is amplified tens of times.Passive double T trap circuit is adopted in the second level, and the resistance of circuit and electric capacity are through overmatching, and filtering 50Hz disturbs well.The third level is adopted high pass filter, the DC potential that the filtering polarization potential produces.The fourth stage adopts low pass filter, the filtering High-frequency Interference, and the cut-off frequency of EEG signals is arranged on 30Hz, and the cut-off frequency of electromyographic signal is located at 500Hz.This wave filter also can be used as the anti-repeatedly wave filter that mixes before the A/D conversion.From the security consideration of human body, in circuit, adopt the high-speed figure light-coupled isolation.
Then electromyographic signal is carried out feature extraction and pattern recognition, feature extraction way and LVQ network classifier that we adopt wavelet packet and principal component neural networks to combine carry out pattern recognition to experimenter's action.We allow the experimenter finish successively and clench fist, open up fist, arm inward turning, arm outward turning and five kinds of states of natural relaxation, prove by experiment, under the requirement of satisfying control in real time, adopt wavelet packet and principal component neural networks way of combining, feature extraction and pattern recognition process time are less than 100ms, the recognition accuracy height reaches 89.5%.
After carrying out pattern recognition, the Electric Machine Control prosthetic hand is finished every grasping movement, and the present invention introduces the tactile and slip sense pick off and evoked brain potential mainly is control performance and the bionic function that further improves prosthetic hand.The tactile and slip sense integrated transducer is used to feed back the extracting situation of being grabbed object, inform the operator by the form that stimulates, the manipulator discerns various stimulations, the different action command of the P300 brain potential that brings out thus mapping is adjusted the strength, speed of the positions that refer to, extracting etc. more, thereby realization is to the further control of prosthetic hand.
(Event-Related Potential, ERP) the P300 BEP in is the endogenous component that a kind of and cognitive relevant brain brings out ERPs to event related potential.When record, need not too many stacking fold, even the advantage that current potential just can occur, and have bringing out 1 time.Cause that the P300 current potential needs two kinds of stimulations at least, will stimulate to weave into stimulus sequence at random, wherein need the experimenter to note and the stimulation recognized is that (Target Stimulus TS), is small probability event to the target stimulation incident; The stimulation that occurs with big probability is non-target stimulation incident Non-Target Stimulus in addition, and NTS), the experimenter does not need this is reacted.After noting and recognize TS, the experimenter will cause the P300 ripple about 300ms.And probability is more little, and the P300 ripple is obvious more.
Plan utilizes the P300 current potential to realize accurate control to the multiple grasping movement of prosthetic hand.Adopt the body sense to stimulate and cause the P300 ripple, multiple different vibratory stimulation is carried out in the residual arm of human body position, corresponding to manipulator's difference action wish.Now establish the stimulation of n kind electric oscillation and be respectively T
1, T
2, K, T
nWhen the experimenter will carry out a certain action, (establish its corresponding electric oscillation stimulation and be T
x), the experimenter discerns the n kind stimulation of irregular appearance. and painstakingly note T
xLike this will be at T
xThe back occurs and the P300 ripple in the brain electricity, occurs, check and note the position that the P300 ripple occurs, correspond to corresponding stimulation, can identify experimenter's wish.
We are equipped with the tactile and slip sense integrated transducer on thumb, forefinger and the middle finger of prosthetic hand, feedback signal produces evoked brain potential by vibratory stimulation, the control strategy that we attempt is as follows: based on the pattern recognition of electromyographic signal, as realizing the action of grasping, thumb, forefinger and middle finger motor are controlled motor respectively just to be changeed, and realizes the action of " closing ".When prosthetic hand touched object, the tactile and slip sense signal feedback was given human body, and the evoked brain potential pattern is opened, and whether each finger needs the action of " closing " by the evoked brain potential signal controlling again.When prosthetic hand grasps object generation slip, as forefinger the sliding signal feedback of feeling is arranged, stimulating apparatus produces judder, produce evoked brain potential,, continue control forefinger motor and just change again by pattern recognition to evoked brain potential, when confirming that object no longer slides, motor rotates and stops.Control method to other action pattern and each finger is all similar with it.
When prosthetic hand only need not the grasping object in order to finish certain gesture, we turn-offed EEG signals, only adopt these gestures are finished in the pattern recognition of electromyographic signal.
Claims (6)
1, adopts the prosthetic hand of myoelectricity and brain electricity Collaborative Control, electromyographic signal processing module, the collection of A/D translation data that comprises the power-collecting electrode that is contained on the residual arm, answers with electrode pair, finish identification of electromyographic signal motor pattern and trajectory predictions module by computer, export electronic prosthetic hand, the tactile and slip sense integrated transducer that control signal drives through drive circuit by pattern recognition and trajectory predictions module, it is characterized in that, also comprise:
The one system feedback stimulating apparatus that whether starts according to tactile and slip sense integrated transducer signal deciding;
Detection is triggered the power-collecting electrode of brain electricity by stimulating apparatus;
The EEG Processing module of answering with electrode pair;
Brain electricity A/D translation data is gathered;
Strength and speed adjustment module that output signal links to each other with electronic prosthetic hand drive circuit.
2, adopt the method for myoelectricity and brain electricity Collaborative Control prosthetic hand, comprise the following steps:
(1) system at first gathers electromyographic signal by processing module and amplifies;
(2) then electromyographic signal is carried out feature extraction and pattern recognition;
(3) the tactile and slip sense integrated transducer records the signal of the extracting situation of being grabbed object,
(4) grabbed thing when the signal reflection and do not grasp, the feedback stimulating apparatus is given the physical stimulation signal of manipulator's one definite form;
(5) power-collecting electrode of brain electricity detects the brain electric information that is brought out by the physical stimulation signal;
(6) EEG signals outputs to strength and speed adjustment module after the EEG Processing resume module;
(7) output signal of adjustment module is finished the further control to electronic hands.
3, as the method for employing myoelectricity as described in the claim 2 and brain electricity Collaborative Control prosthetic hand, it is characterized in that, in the collection to electromyographic signal in the described step (1), amplify and filter function divides the level Four realization; The first order adopts instrumentation amplifier that the bio signal that collects is amplified tens of times; Passive double T trap circuit is adopted in the second level, and the resistance of circuit and electric capacity are through overmatching, and filtering 50Hz disturbs well; The third level is adopted high pass filter, the DC potential that the filtering polarization potential produces; The fourth stage adopts low pass filter, the filtering High-frequency Interference, and the cut-off frequency of EEG signals is arranged on 30Hz, and the cut-off frequency of electromyographic signal is located at 500Hz; This wave filter also can be used as the anti-repeatedly wave filter that mixes before the A/D conversion; From the security consideration of human body, in circuit, adopt the high-speed figure light-coupled isolation.
4, as the method for employing myoelectricity as described in the claim 2 and brain electricity Collaborative Control prosthetic hand, it is characterized in that the feature extraction way and the LVQ network classifier that adopt wavelet packet and principal component neural networks to combine in the described step (2) carry out pattern recognition to experimenter's action.
5, as the method for employing myoelectricity as described in the claim 2 and brain electricity Collaborative Control prosthetic hand, it is characterized in that, carry out signal extraction and pattern recognition to clenching fist, open up fist, arm inward turning, arm outward turning and five kinds of states of natural relaxation in the described step (2).
6, as the method for employing myoelectricity as described in the claim 2 and brain electricity Collaborative Control prosthetic hand, it is characterized in that the mode of physical stimulation can be electricity irritation or vibration in the described step (4).
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| CNB2007100573713A CN100546553C (en) | 2007-05-18 | 2007-05-18 | Adopt the prosthetic hand and the control method thereof of myoelectricity and brain electricity Collaborative Control |
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