Presentation on theme: "Advanced Biomechanics of Physical Activity (KIN 831)"— Presentation transcript:
1 Advanced Biomechanics of Physical Activity (KIN 831) Electromyography (EMG)Material included in this presentation is derived primarily from two sources:** Nigg, B. M. & Herzog, W. (1994). Biomechanics of the musculo-skeletal system. New York: Wiley & Sons* Winter, D.A. (1990). Biomechanical and motor control of human movement. (2nd ed.). New York: Wiley& Sons
2 Electromyography (EMG) Electro – electricalMyo – muscleGraphy – recordElectromyography – involves recording the electrical activity of muscleElectromyogram – electrical signal associated with the contraction of a muscle
3 Selected Historical Events Related to EMG Andreas Vesalius, “father of modern anatomy”, appearance and geography of dead muscle, 1555
4 Selected Historical Events Related to EMG William Croone, in De Ratione Motus Musculorum concluded from nerve section experiments that the brain must send a signal to the muscles to cause contraction, 1664Physiologists became excited over the phenomena produced by electrical stimulation of muscles, 1740
5 Selected Historical Events Related to EMG Albrecht von Haller ( ) summarized many of the earlier studies in his treatise on muscular irritability. Robert Whyatt ( ) reported clinical observations on a patient treated by electrotherapy.“Animal electricity” was proposed as a substitute for the “animal spirits” which earlier experiments believed to be the activating force in muscular movement.
6 Selected Historical Events Related to EMG Luigi Galvani ( ) studied the effects of atmospheric electricity upon dissected frog muscles. He concluded that the movement of the muscle was the result of its exterior negative charge uniting with the positive electricity which proceeded along the nerve (1786). Galvani’s Commentary on the Effects of Electricity on Muscular Motion (1791 or 1792) is probably the earliest statement of the presence of electrical potentials in nerve and muscle. He showed that electrical stimulation of muscular tissues produced contraction and force. He is considered the “father of experimental neurology.”
7 Galvani’s demonstrations of the effects of electricity on muscles of frogs and sheep (De viribus electricitatis in motu musculari commentarius, 1792)
8 Selected Historical Events Related to EMG “animal electricity” became the absorbing interest of the physiological world. The greatest name among the early students of the subject was Emil DuBois-Reymond ( ). He laid the foundation of modern electrophysiology. He was probably the first to discover and describe that contraction and force production of skeletal muscle were associated with electrical signals originating from the muscles (1849).
9 Selected Historical Events Related to EMG Guillaume Benjamin Amand Duchenne ( ) set out to classify the functions of individual muscles through electrical stimulation. He recognized the problem of attempting to isolate muscle contractions.
10 Duchenne’s book, Physiology des Movements (1865), has been acclaimed “one of the greatest books of all time.” He was probably the first to perform systematic investigations of muscular function using an electrical stimulation approach.
11 Guillaume Benjamin Amand Duchenne de Boulogne investigating the effect of electrical stimulation of the left frontalis muscle on one of his cooperative (prisoner) subjects
12 Selected Historical Events Related to EMG Wedinski (1880) demonstrated the existence of action currents in human muscle. Practical use had to await the invention of a sensitive string galvanometer (W. Einthoven ).
13 Selected Historical Events Related to EMG The physiological aspects of EMG were first discussed ( ) by H. Piper of GermanyE.D. Adrian, in an article in Lancet (1925, vol. 2, pp ) entitled “Interpretation of the Electromyogram” demonstrated for the first time that it was possible to determine the amount of activity in a human muscle at any stage of movement.
14 Selected Historical Events Related to EMG Toward the end of WWII, with marked improvement of electronic apparatus; anatomists, kinesiologists, and orthopedic surgeons began to make increasing use of EMG. The first study that gained wide acceptance was that of Inman, Saunders, and Abbott who reported their work on the movements of the shoulder region in “Observation on the Function of the Shoulder Joint” in the Journal of Bone and Joint Surgery (1944, vol. 26, pp. 1-30).
16 Selected Historical Events Related to EMG During the 1950’s and beyond , EMG for kinesiological studies became widespread.
17 EMG of normal gait??? Note the use of event markers in the foot.
18 Selected Historical Events Related to EMG John Basmajian ( ) wrote the bible of electromyography entitled Muscles Alive. He and Carlo De Luca summarized the existing knowledge and research on muscle function as revealed by EMG studies.
19 Copper screen cage to inhibit noise in the EMG signal
20 Typical multifactorial gait-recording showing: Angular accelerometer on the left legVertical accelerometerHorizontal accelerometerStrain gauge tensiometer on left gastrocnemiusEMG of left gastrocnemius
21 Electromyography is a seductive muse because it provides an easy access to physiological processes that cause the muscle to generate force, produce movement and accomplish the countless functions which allow us to interact with the world around us. The current state of Surface Electromyography is enigmatic. It provides many important and useful applications, but it has many limitations which must be understood, considered and eventually removed so that the discipline is more scientifically based and less reliant on the art of use. To its detriment, electromyography is too easy to use and consequently too easy to abuse. C. J. De Luca, 1993
22 Schematic Representation of a Recording an EMG Signal from a Single Muscle Fiber Measure of changes in electrical potential across the muscle fiberAt rest, potential ≈ -90mvWith sufficient stimulation potential inside cell rises to ≈ 30-40mvChange in potential (fiber action potential) can be recordedAction potentials from multiple fibers in a motor unit are simultaneously recordedSignal from depolarization of a motor unit is called motor unit action potential
23 Electrophysiology of Muscle Contraction Motor unit action potential (muap) – change in electrical potential across the muscle fiber membranes when a motor unit is stimulated beyond a critical thresholdElectrodes placed inside (indwelling) or on the surface of a muscle record the algebraic sum of all muap’s transmitted along muscle fibers that reach the electrodesMotor units far away from the electrode have their muap attenuated (i.e., are smaller)Motor units of a muscle are controlled by motor neurons activating them at their motor end plates
24 Electrophysiology of Muscle Contraction End plate potential (EPP) – depolarization of post synaptic membraneEPP that reach a threshold initiate action potential in muscle fiber membraneDepolarization of the transverse tubular system and sarcoplasmic reticulum results in a depolarization wavealong the direction of the muscle fibersEMG records the depolarization and subsequent repolarization
25 Two Categories of Electrodes 1. By placement of electrode:SurfaceIndwelling (needle)
28 Comparison between Recording Areas of Two Types of Surface Electrodes
29 Indwelling (needle)Steps in making a bipolar fine-wire electrode (Basmajian and Stecko, 1962)
30 Surface vs. Indwelling Electrodes Non-invasiveDetect average activity of superficial muscles and give more reproducible resultsMetal (silver/silver chloride) disk or barMay be subject to cross-talk (EMG signals from motor units of other muscles near byIndwellingInvasiveUsed to detect EMG signal from small muscles and deep musclesFine hypodermic needle with insulated wire conductorsMay be subject to cross-talk
31 Preparation of Skin for Surface Electrodes Reduce electrical impedance of skinShave the areaApply rubbing alcohol or abrasives to remove dead skin and oilsUse electrode gel and pressure, adhesive tapes and/or elastic bands to affix electrode to skin
32 Categories of Electrodes 2. By electrode configuration:Monopolar – records difference in voltage relative to groundBipolar – two contacts to measure electrical potential, each relative to a common ground, most common electrode typeMultipolar
33 Biphasic SignalSignal associated with single electrode and ground
34 Triphasic SignalSignal associated with voltage difference when two electrodes are used at one site
36 Factors Affecting EMG Signal Propagation velocity of wave front (≈ 4m/s)Fatigue results in decreased propagation velocityDistance between electrodesDepth of muscle fibers being recordedElectrode surface areaLarger surface area longer duration of muapsurface electrodes record longer muap than indwelling electrodes (≈ 3-20ms)Size of muscle fibers being recordedLarger fibers have larger signals
37 Preferred electrode location is between motor point (innervation zone) and the tendonous insertion.
38 Amplitude and frequency spectrum of EMG signal affected by electrode placement with respect to: A Myotendonous junctionB, C Edge of muscleDBCPreferred location:D Midline of belly between innervation zone and myotendonous junction - greatest amplitude detectedA
39 Factors to Consider in Recording EMG Signals EMG signal is summation of muap’sGoal is to have signals that are undistorted (linear amplification) and free of noise (biological – ECG, other muscles; man-made – power lines, machinery) and artifacts (false signals from electrodes and cabling – movement artifacts from touching electrodes or moving cables)Large signals 5-10 mV; small signals 100 V
40 Factors to Consider in Amplifying EMG Signals Amplifier gain – ratio of output voltage to input voltage (gain of 1000: 2 mV 2 V)Linear amplification over entire band widthDo not overdrive the amplifier system (large signals clipped off)Full range frequency response for amplifier should be fast enough to handle highest EMG frequenciesAmplifier input impedance –resistanceHigh so as not to attenuate the EMG signal*Report magnitudes of voltage as they are sensed at the electrodes; not amplified signal
42 Factors to Consider in Amplifying EMG Signals Frequency responseAmplify without attenuation all frequenciesFrequency spectrum of EMG signals from 5 to 2000 HzRecommended range for surface electrodes – 10 to 1000 HzRecommended range for indwelling electrodes – 20 to 2000 HzBandwidth of amplifier difference between upper and lower cutoff frequenciesPossible filtering of signals to avoid unwanted noise
43 Want frequencies of EMG signals to fall within range where all frequencies are linearly influenced by gain2000 Hz5 Hz
44 Power density spectrum – mathematical conversion of EMG signals from time to frequency domain for analysis of the frequency content of the signalHigher frequency content of indwelling electrodes because of closer spacing of electrodes and their closer proximity to active muscle fibersMost of EMG signal concentrated in band width between 20 and 200 HzProblem with power lines because frequency is in middle of band widthMovement artifact (0-10 Hz) can be filtered without adversely affecting desired EMG signal
46 Factors to Consider in Amplifying EMG Signals Common mode rejectionHuman body good conductor; acts as antenna to electromagnetic radiationWant to eliminate extraneous signalsUnwanted signals picked up simultaneously at two locations can be eliminated resulting in amplification of only difference in voltage associated with EMG signalDesired amplified signal = A[(Vhum + emg1) - (Vhum + emg2)] = A[emg1 – emg2]
50 Analog to Digital Conversion and Sampling an Analog Signal
51 Analog EMG signalDigital display of analog EMG signal sampled at 2 kHz
52 Sampling a 1 V, 1 Hz sinusoid at 10 Hz Recreating the sinusoid at 10 Hz
53 Sampling a 1 V, 1 Hz sinusoid at 2 Hz Recreating the sinusoid at 2 Hz
54 Sampling a 1 V, 1 Hz sinusoid at 4/3 Hz Recreating the sinusoid sampled at 4/3 yields a 1/3 Hz signal. The original 1 Hz signal is undersampled.
55 The Nyquist Frequency Signals should be sampled at no less than twice the original frequency.
56 Fourier decomposition of maup Original signal in redSuperimposed signal in blue is the mathematical summation of the 10 sinusoids aboveExact reconstruction would require an infinite number of sinusoids, but 10 provides appropriate accuracytimeSignal is in time domain because it expresses voltage as a function of time.
57 Signal of muap from previous slide is in the frequency domain because it describes amplitudes of the frequency contained in it.
58 Unprocessed EMG Signals Useful for determining:Onset and turn-off of muscle contractionPattern of contraction of musclesElectromechanical delay (EMD)
59 Why Process EMG Signals? Raw signals resemble noise (stochastic)Raw signals fluctuate around 0 voltage ( V over time 0) V over time for all EMG records are the same; no differentiationProcessed signals may be correlated to parameters of muscle contraction being studied (e.g., force, fatigue)
60 Processing EMG Signals in the Time Domain RectificationHalf wave – eliminate negative values; only positive signals are usedFull wave – absolute value of all signals usedPreferred because no information is eliminatedOften used in further processingSmoothingFiltering signal to eliminate selected frequenciesLow pass filter – allows low frequencies to pass untenanted, but removes most of the high frequenciesHigh pass filter – allows high frequencies to pass untenanted, but removes most of the low frequenciesWindow or notch filter
61 Some Common EMG Processing Absolute value of EMG signalFull wave rectified and low pass filterArea under voltage time curveArea under voltage time curve with time reset Area under voltage time curve with time reset
62 Examples of EMG Signal Processed in the Time Domain
63 Processing EMG Signals in the Time Domain IntegrationIntegration – measures the area under the volt-time curveIEMG =Reset at regular intervals of timeReset at regular intervals of pre-established area (Vsec)
64 Processing EMG Signals in the Time Domain Root Mean SquareFrequently used in studying muscular fatigueCalculationSum of squared raw data values of EMG signalDetermine mean of sumTake square root of the meanRMS =
65 Processing EMG Signals in the Frequency Domain Power density spectraFrequency domain important because frequency content of EMG signal shown to be reduced with fatiguePower density spectra of EMG signal obtained using Fast Fourier Transformation techniqueMean and median frequency, bandwidth, and peak power frequency examples of use of power density spectra
66 Example of EMG Signal Processed in the Frequency Domain Frequency spectrum of EMG signal detected from the tibialis anterior muscle during a constant force isometric contraction at 50% voluntary maximum.
67 Power density spectrum of EMG signal obtained from Fast Fourier Transformation (FFT)
68 Mean and Median Frequencies Mean frequency – that frequency where the product of the frequency value and the amplitude of the spectrum is equal to the average of all such products throughout the complete spectrum; used mainly to monitor muscle fatigueMedian frequency – that frequency that divides the power density spectrum into two regions having the same amount of power; preferred for detecting muscle fatigueLess sensitive to signal noiseLess sensitive to aliasingMore often more sensitive to biochemical and physiological factors in muscle during sustained contractions
69 Meaning of EMG SignalsLogical to assume that EMG signals relate to biomechanical variables (e.g., muscle contraction force, muscle fatigue)Quandary: EMG signal is the result of many physiological, anatomical, and technical factors
70 Meaning of EMG Signals 5 cardinal questions Is the signal detected and recorded with maximum fidelity?How should signal be analyzed?Where does the detected signal originate? (cross talk, electrode placement on muscle)Is signal stationary?Where does the measured force originate? (influence of synergists and antagonists)
71 Relationships between EMG Signals and Biomechanical Variables - Force Qualitative relationship not questioned in scientific literature; quantitative nature hotly debatedQuantitative relationship difficult to showDifficulties measuring EMG and force of muscle contractionProblem with temporal disassociation of muscular contraction and EMG signal (EMD)
72 Relationships between EMG Signals and Biomechanical Variables – Force Isometric contractionCan eliminate problems with problems with measurement of force of contraction and EMGCan eliminate temporal dissociation by sampling in middle of steady state contractionDespite ability to eliminate or reduce problemsDifferent relations between force and EMG seenMuscle specific relationships with EMG?Force measured indirectly?Activity of antagonists or synergists?Signal processed differently in each studyLinear and non-linear relationships found
75 Rat MuscleSoleus – slow twitch, high aerobic, slow fatiguingExtensor digitorum longus – fast twitch, high glycolytic, fast fatiguing*Note dramatic delay of force time rise under same stimulation conditions
77 Relationships between EMG Signals and Biomechanical Variables – Force Dynamic contractions (concentric, eccentric, isokinetic)Few studies with unrestrained movementBecause of problems, most studies of isokinetic contractionConstant angular velocity constant velocity of muscle shorteningConstant angular velocity constant velocity of contractile element shorteningEMG amplitude associated with negative work considerably less than positive work
79 Relationships between EMG Signals and Biomechanical Variables –Fatigue Fatigue – “point” at which force of contraction can not be maintainedProblems in measuring fatigueWhich muscle is fatigued?Variable recruitment and utilization of motor unitsFatigue both psychological and physiological phenomena
80 Relationships between EMG Signals and Biomechanical Variables –Fatigue Fatigue is associated with a shift in the frequency spectrum of the EMG signals to lower frequenciesLower conduction velocities of some or all action potentialsSlower motor units remain active while faster motor units drop outMotor units tend to fire more synchronously
81 Diagrammatic explanation of spectral modification which occurs in EMG signal during sustained contractionsMuscle fatigue index is represented by the median frequency of the spectrum
83 Factors EMG Signal Inter-pretation Causative Intermediate DeterministicExtrinsicElectrodeConfigurationMotor pointMuscle edgeFiber orientationTendonIntrinsicNumber of active motor unitsMotor unit firing rate (synchronization)Fiber type Lactic acid (pH)Blood flowFiber diameterElectrode Fiber locationSubcutaneous tissueOther factorsDifferential electrode filterDetection volumeSuperpositionSignal crosstalkConduction velocitySpatial filteringNumber of active motor unitsMotor unit twitch forceMuscle fiber interactionsMotor unit firing rateNumber of motor units detectedMUAP amplitudeMUAP durationMUAP shapeRecruitment stabilityAmplitude (RMS/ARV)Spectral variables (median/mean frequency)Muscle fiber (net force/torque)Muscle activation (on/off)Muscle fatigueMuscle biochemistrySchematic of factors affecting EMG signal – influences and interactions, C.J. De Luca, 1993