Electromyography ESS 5314-001 Lecture 8 Reading: Robertson et al. Ch 8 EMG: Techniques and Considerations • EMG Pathway: What are we measuring? MUAP Tissue Skin Filter Electrolyte Interference Noise Electrode Noise Leads Noise Amplifier Band Pass A/D Noise Filter Electrodes • 2 Basic Categories – Indwelling • Study activation of a single motor unit • Needle • Fine Wire – Surface • Study composite action of multiple motor units Surface Electrodes • Single Differential • Double Differential • Pre-Amplified Δ Raw Signal Characteristics • Contains frequency components in the range of 5 to 2000 Hz • Most signal power is between 20 – 200 Hz for surface EMG – With some frequencies up to 1000 Hz • What are the implications for EMG sampling rate selection? Bio-Amplifier Considerations • Input Impedance – Greater value means less resistance and less signal attenuation. • Gain – Ratio of output to input voltage (100 to 10,000 Hz) – Set to maximize voltage range • Frequency Response – Should amplify all frequency components equally and linearly (bandwidth 10 to 1000 Hz) • Common Mode Rejection Ratio – Ability of system to eliminate signal (noise) common to all active terminals (10,000:1 = 80 dB) System Recommendations Differential Electrode Configuration • Detection Surfaces – 2 parallel bars, each 1.0 cm (L) x 1-2 mm (W) – Spacing between bars is 1.0 cm apart • Frequency Bandwidth of 20-500 Hz • Common Mode Rejection Ratio > 80 dB • Noise < 2 μV RMS (20-500 Hz) • Input Impedance > 100 MΩ - C. De Luca (1997) Artefact and Noise • Cable movement artefact • Electrode movement artefact • ECG signal • Muscle cross talk • Hum (electrical ~ 60 Hz) Skin Preparation Recommendations • Clean skin with alcohol (definitely) • Shave hair (only excess) • Lightly abrade skin (? - with sandpaper) • Use electrode electrolyte (gel, paste, cream) – Often built in with newer electrodes Electrode Placement • Muscle Belly • Avoid tendon and lateral edge of muscle • Align electrodes parallel with muscle fibers • Proximity to motor point or innervation zone – Place electrode on midline of muscle belly midway between tendon and nearest innervation zone Reliability • Inter-Day – 0.60 to 0.81 – For both sub-maximal and maximal tasks – Not very reliable between days, thus questionable repeated trials data reliability • Intra-Day – 0.64 to 0.91 for maximal contractions – 0.78 to 0.95 for sub-maximal contractions – Better – thus try repeated measures in same day ** Keep electrodes in place – do not remove between trial sessions Magnitude of Signal • Maximum of 5 μV range at skin • Gain should be set to maximize range of A/D • Convert raw Volts of A/D to mV measured at skin Scaled EMG = (Unscaled EMG)(1/gain)(1000 mV/V) = (Unscaled EMG)(1000)(1/gain) Power Spectrum and Sampling • Significant signal power between 20-200 Hz – Note: movement artifact lies in frequencies below 10 Hz • Shannon’s Sampling Theorem – Sample at least 2 times highest power in signal • Thus, sample at 2000 Hz (if you can) Signal Processing Amplitude Root Mean Square (Value) Raw Linear Envelop (Curve) EMG Rectified EMG (Curve) Integrated (Value) Post Processing of EMG Data • Rectify • Filter – Low pass linear envelop (~ 3 Hz cutoff) – Band pass filter (10 – 20 Hz, signal passes between) – Integrated EMG (IEMG) • Normalize • Determining onset and offset of muscle activation Signal Processing Raw EMG Signal Processing Full Wave Rectified REMG = |raw EMG| Signal Processing Linear Envelop Butterworth 2nd order, cutoff = 2 Hz Signal Processing Linear Envelop Butterworth 2nd order, cutoff = 3 Hz Signal Processing Linear Envelop Butterworth 2nd order, cutoff = 10 Hz Filtering – Bandpass Filter Bandpass Filter Cutoffs 10 and 20 Hz Keeps EMG signal between 10 and 20 Hz (i.e., it passes through the filter unattenuated) Signal Processing Integrated T IEMG = ∫ t │EMG(t)│dt Signal Processing Root Mean Square (RMS) T RMS = (1/T · ∫ t EMG(t)2 dt) ½ Normalized EMG Norm EMG = EMG / max(EMG during norm trial) • Normalization Trial – MVIC (isometric - concentric) – MVEC (eccentric) – Max EMG during other strength trial – Max EMG during task trial – Max EMG during task trial or MVIC (whichever is greater) • Ultimately trying to find the greatest possible EMG and relate the EMG during the trial to that max (% of max EMG possible). But this needs to be done consistently. Normalization Techniques • % MVC – Isometric (%MVIC) • % MVC – Isokinetic or Isotonic • % Maximum functional reading • % Average functional reading Signal Processing Temporal Variables Burst Muscle Firing Onset Duration Sequence Raw EMG Offset Burst Co-Contraction Frequency Signal Processing Illustration of Temporal Values Onset Offset Duration Onset and Offset Determination • Dual Threshold Method – Filtered rectified EMG must pass a certain threshold combination before it is considered active (on) – likewise for offset (off) – Ex. 4% and 7% • EMG “burst” must achieve 7% normalized activity to be considered active (on) • Time of onset occurs at the point (during the burst) at which the normalized EMG crossed 4%. Dual Threshold Onset Method Normalized Rectified EMG 1.0 0.8 0.6 0.4 0.2 0.07 0.04 Important Considerations • Process your normalization trial EMG exactly as you process your trial EMG. – Sample rate – Rectification – Filter or Integrate • Rectify before filtering and/or integrating • Normalize EMG trial data uniquely for each muscle tested • Determine activation onset and offset from normalized or integrated data. EMG and Muscle Function • Fatigue – Increased EMG amplitude – Decrease in motor unit firing rate (frequency) – More synchronous firing • Coordination – Sequencing and co-contraction • Force – Linear and non-linear relations EMG-Force Relation EMD EMD Muscle Force EMG 400 ms References • De Luca (1997) • Nigg & Herzog (1996) • Danty & Norman (1987) • Soderberg & Cook (1984) • Winter (1990) – Chapter 8 Data Collection • 4 muscles monitored – Tibialis Anterior – Gastrocnemius – Rectus Femoris (or other quadriceps muscle) – Biceps Femoris (or other hamstrings muscle) • In processing, we will normalize EMG against MVIC and max EMG during task to see difference • Specific Tasks TBA – 2 to 5 trials each task, best will be exported and used in assignment. – Vertical Jump, Biodex Trials (Isometric, Isokinetic) EMG Matlab Assignment • Separate Assignment Handout with details • Load EMG data • Rectify all data and plot an example (raw vs rectified) • Find max amplitudes for each muscle during trial EMG data • Filter data for one trial EMG (this can be in excel or matlab – your choice) and compare results: – Low pass linear envelop (cutoff 3Hz) – Bandpass (cutoffs 10 and 20 Hz) – IEMG (mean peak IEMG for the 3 squats and jumps) – Plot these results for comparison (either on same graph or subplotted) with raw rectified. • One plot per muscle. Or plot results from only one muscle • Normalize the rectified, filtered EMG (treat trial and norm trial data the same) for a Biodex and Jump trial and compare – To MVIC for each muscle (or the muscle we have isometric data on). – To max EMG occurring in the trial – Plot for comparison • Compare results for different filters using subplots – Low pass linear envelop – Bandpass – IEMG – RMS EMG Reminders • 3rd and final critique due next week • Assignments 1, 2 & 4 due by next week at latest • Assignment 3 due before Thanksgiving • Assignments 4 & 5 due by last day of classes (Dec. 3) • Project Presentations are Nov. 13 and 20th. • Written Projects are due by last day of classes • No final exam for this course.