Bioelectric Signals & Devices Part 1: EEG & Brain-Machine Interface

Transcription

1 Bioelectric Signals & Devices Part 1: EEG & Brain-Machine Interface Hsiao-Lung Chan Dept Electrical Engineering Chang Gung University

2 Biopotential signals From BH.Brown, Medical Physics and Biomedical Engineering, IOP Publishing Ltd, Biopotentials 2

3 Biopotentials 3

4 Origin of biopotentials Na + Cl - Extracellular domain Phospholipid bilayer Intracellular domain K + Biopotentials 4

5 Passive channels Selective permeable membrane Cl - K+ Na+ Outside (+) A - Cl - K+ Na+ Inside (-) Biopotentials 5

6 Resting potential of a membrane premeable to one ion (e.g. K + ) drift K+ K+ K+ Cl - Na+ Outside (+) diffusion A - K+ d[ K ] J K ( diffusion) D dx K+ K+ Na+ Cl - J K ( drift) Z[ K ] Inside (-) dv dx D: diffusion constant, Z: ion valence, [K + ]: ion concentration, μ: mobility, v & -dv/dx : voltage & electrical field across the membrane Biopotentials 6

7 Resting potential from one ion (cont.) J K J K ( diffusion) J K ( drift) D d[ K dx ] Z[ K ] dv dx At equilibrium, J K = 0, the Nernst equation is derived as E K v i v o RT nf [ K ln [ K [ K ln [ K ] ] o i ] ] o i (V) at 37 0 C (body temp erature) v i & v o : voltages outside and inside the membrane n: valance of K + R: universal gas constant T: absolute temperature in K F: Faraday constant Biopotentials 7

8 Resting potential from mutliple ions Goldman equation At equilibrium E RT F ln P P K K [ K [ K ] ] o i P P Na Na [ Na [ Na ] ] o i P P Cl Cl [ Cl [ Cl ] ] i o P M : permeability coefficient of membrane for a particular ion species M Biopotentials 8

9 Resting potential from mutliple ions RT/F The resting potential is -60 mv Biopotentials 9

10 Action potential Na Outside cell Plasma membrane Inside cell Na Resting phase K + 3 Repolarizing phase K + Na + Na Depolarizing phase K + 4 Undershoot phase K + Membrane potential (mv) t Biopotentials 10

11 Action potential Biopotentials 11

12 Active channel: sodium-potassium pump Remove 3 Na + for every 2 k + outside K+ Na+ inside K+ Na+ M. Bear et al, Neuroscience: exploring the brain, Lippincott Williams & Wilkins, Biopotentials 12

13 Cerebrum (Frontal,Parietal,Temporal and Occipital lobes) From JJ Carr, Introduction to Biomedical Equipment Technology, Prentice-Hall, Biopotentials 13

14 Brain Cerebrum ( 大腦 ) Thalamus ( 丘腦 ) Sensory and motor system Human behaviors... Hypothalamus ( 丘腦下部 ) Autonomic nervous system Temperature regulation Water and electrolyte balance Behavior response to emotion Endocrine control Sexual response... Medulla Oblongata ( 延腦 ) Vital centers that regulates heart rate, respiratory rate, blood pressure, blood vessel, etc. Cerebellum ( 小腦 ) Coordinating skeletal muscles and impulses from cerebral cortex M. Bear et al, Neuroscience: exploring the brain, Lippincott Williams & Wilkins, Biopotentials 14

15 Electroencephalogram (EEG) M. Bear et al, Neuroscience: exploring the brain, Lippincott Williams & Wilkins, Biopotentials 15

16 Biologocal neuron Biopotentials 16

17 Axon ( 軸突 ) to synapse ( 突觸 ) via neurotransmitter Biopotentials 17

18 Simplified synapse in biologocal neuron Biopotentials 18

19 Electroencephalogram (EEG) rhythms Biopotentials 19

20 EEG changes in sleep Biopotentials 20

21 EEG waveform recorded from one patient under sevoflurane in different states LZ complexity awake state intermediate state asleep state Biopotentials 21

22 Lempel-Ziv complexity Biopotentials 22

23 Estimation of depth of anesthesia by EEG/AEP EEG monitoring Audio evoked potential monitoring Biopotentials 23

24 EEG spikes or abnormal waveform in epilepsy John G. Webster, Medical Instrumentation, application and design, 3rd Ed., Houghton Mifflin, Biopotentials 24

25 EEG electrode placement Biopotentials 25

26 Multichannel EEG recodeings: Neuroscan TM Biopotentials 26

27 Monopolar measurements Biopotentials 27

28 Bipolar measuremesnts Biopotentials 28

29 Monopolar montage Epilepsy spikes Biopotentials 29

30 Bipolar montage Epilepsy spikes Biopotentials 30

31 Control robotic arms using braincomputer interface Belle, a monkey in Brain Machine Interface study Articles from Scientific American, Nature, Biopotentials 31

32 Tetraplegia (Quadiplegia) Cervical (neck) injuries usually result in four limb paralysis. Injuries above the C4 level may require a ventilator or electrical implant for the person to breathe.

33 Cortical neuroprothesis Biopotentials 33

34 From primates to humans Miguel Nicolelis et al, Duke University Scientific American 2002, Nature Review Neuroscience BrainGate Collaboration Brown University, Nature 2012

35 Belle s 600-mile reach Beneath the cap, each of four plastic connectors fed an array of fine microwires into cortex. As Belle saw lights shine suddenly, she decided to move a joystick left or right. The microwires detected electrical signals produced by activated neurons and relayed the signals to a Harvey box. Control Robots with the Mind Scientific American 2002

36 The Harvey box amplified the neural signals. A computer predicted the trajectory that Belle s arm would take and converted that information into commands. These commands were used to control a robot arm in a room across the hall and another robot in a laboratory hundreds of miles away. Both robot arms moved in synchrony with Belle s own limb. Biopotentials 36

37 The BrainGate neural interface system (Brown University) An implanted microelectrode array Biopotentials 37

38 Raster plot Action potentials recorded from motor cortex Each bar indicates neuronal firing at a given moment Time Biopotentials 38

39 Control computer cursor by thinking (The BrainGate in 2006) Biopotentials 39

40 Reach for and grasp objects using robotic arms controlled by brain activity A 58-year-old woman, paralyzed by a stroke for almost 15 years uses her thoughts to control a robotic arm, grasp a bottle of coffee, serve herself a drink, and return the bottle to the table. BrainGate Collaboration Brown University, Nature 2012

41 A vision of future A neurochip would amplify arrays of microwires implanted in motor cortex, convert the thoughts into a train of radio-frequency signals, and send them to a backpack computer. The computer would convert the signals into motor commands for stimulating muscle nerves to move arm controlling a wheelchair or a robotic arm Control Robots with the Mind Scientific American 2002

42 Reference John Enderle, Susan Blanchard, Joseph Bronzino, Introduction to Biomedical Engineering, Academic Press, John G. Webster, Bioinstrumentation, John Wiley & Sons, John G. Webster, Medical Instrumentation, application and design, 3 rd Ed., Houghton Mifflin, BH.Brown, RH.Smallwood, DC.Barber, PV.Lawford, and DR.Hose, Medical Physics and Biomedical Engineering, IOP Publishing Ltd, Joseph J. Carr, John M. Brown, Introduction to Biomedical Equipment Technology, Pearson Education, F.M. Ham, I. Kostanic, Principle of Neurocomputing for Science & Engineering, McGraw Hill, Biopotentials 42