Project E: The eight-channel EMG armband
Eight electrodes around the forearm, a classifier, and hand gestures recognized from muscle activity. The wristband idea, and the most dependable 'control something with your nervous system' demo there is.
On this pageTwo weekends
One EMGElectromyography (EMG) Recording the electrical activity of muscles, hundreds of microvolts to millivolts, much larger than EEG. Related: Myoelectric prosthesisMyoelectric prosthesis An artificial limb controlled by EMG from the remaining muscles. , Electroencephalography (EEG)Electroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. . Glossary entry channel gave you a servo that follows a clench. Eight channels in a ring around the forearm give you a pattern: each gesture activates the muscles under some electrodesElectrode The conductor that turns ion currents in tissue into electron currents in a wire; its chemistry and contact quality set the noise you live with. Related: Silver/silver-chloride (Ag/AgCl)Silver/silver-chloride (Ag/AgCl) The standard electrode material for biopotentials, because its chemistry produces a stable, low-noise, low-drift interface with salty gel. , Electrode impedanceElectrode impedance How hard it is to push current through the skin-electrode contact, typically 5 to 50 kilohms with gel and megohms dry, higher at low frequencies. , Half-cell potentialHalf-cell potential The DC voltage that appears wherever a metal meets an electrolyte; two electrodes with different half-cell potentials produce an offset that can swamp the signal. . Glossary entry and not others, and a classifierClassifier An algorithm that assigns each trial a label, such as left hand or right hand, after being trained on labelled examples. Related: Linear discriminant analysis (LDA)Linear discriminant analysis (LDA) A simple, robust classifier that draws a straight boundary between classes; the workhorse of EEG decoding for two decades. , Support vector machine (SVM)Support vector machine (SVM) A classifier that finds the boundary with the widest margin between classes; strong on small datasets. , Cross-validationCross-validation Testing a model on data it never saw during training, repeatedly, so the reported accuracy means something. . Glossary entry can learn the patterns. Rest, fist, open hand, wrist flexion, wrist extension, pinch: six gestures, recognized in real time from a fabric band. This is what the commercial gesture wristbands do, it is the control principle of multi-grip prosthetic hands, and it is the gentlest possible introduction to the classification you will do on EEGElectroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. Related: Electrocorticography (ECoG)Electrocorticography (ECoG) Recording from electrodes placed on the surface of the brain under the skull, usually during epilepsy surgery evaluation; cleaner and sharper than EEG. , Magnetoencephalography (MEG)Magnetoencephalography (MEG) Recording the tiny magnetic fields produced by cortical currents with superconducting sensors in a shielded room; less blurred by the skull than EEG, and far more expensive. , Volume conductionVolume conduction The spreading of currents from a source through the conductive tissues of the head, which is why one source shows up on many electrodes and why scalp EEG is blurry. , Microvolt (µV)Microvolt (µV) One millionth of a volt. Scalp EEG is tens of microvolts; a AA battery is 1.5 million of them. . Glossary entry in Phase 3, because EMGElectromyography (EMG) Recording the electrical activity of muscles, hundreds of microvolts to millivolts, much larger than EEG. Related: Myoelectric prosthesisMyoelectric prosthesis An artificial limb controlled by EMG from the remaining muscles., Electroencephalography (EEG)Electroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity.. Glossary entry is large, clean, and cooperative.
A classifier trained on your gestures today gets 95 percent. You put the band on tomorrow, slightly rotated. What happens?
Drops a lot. Rotating the band by one electrodeElectrode The conductor that turns ion currents in tissue into electron currents in a wire; its chemistry and contact quality set the noise you live with. Related: Silver/silver-chloride (Ag/AgCl)Silver/silver-chloride (Ag/AgCl) The standard electrode material for biopotentials, because its chemistry produces a stable, low-noise, low-drift interface with salty gel. , Electrode impedanceElectrode impedance How hard it is to push current through the skin-electrode contact, typically 5 to 50 kilohms with gel and megohms dry, higher at low frequencies. , Half-cell potentialHalf-cell potential The DC voltage that appears wherever a metal meets an electrolyte; two electrodes with different half-cell potentials produce an offset that can swamp the signal. . Glossary entry moves every muscle’s signal to a different channel, and a classifierClassifier An algorithm that assigns each trial a label, such as left hand or right hand, after being trained on labelled examples. Related: Linear discriminant analysis (LDA)Linear discriminant analysis (LDA) A simple, robust classifier that draws a straight boundary between classes; the workhorse of EEG decoding for two decades. , Support vector machine (SVM)Support vector machine (SVM) A classifier that finds the boundary with the widest margin between classes; strong on small datasets. , Cross-validationCross-validation Testing a model on data it never saw during training, repeatedly, so the reported accuracy means something. . Glossary entry that learned “fist means channels 2 and 3” has no idea. This is the single biggest problem in wearable EMGElectromyography (EMG) Recording the electrical activity of muscles, hundreds of microvolts to millivolts, much larger than EEG. Related: Myoelectric prosthesisMyoelectric prosthesis An artificial limb controlled by EMG from the remaining muscles. , Electroencephalography (EEG)Electroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. . Glossary entry and it is why every commercial band has a calibrationCalibration The session at the start of BCI use in which the decoder is trained on this person, today, because brains and electrodes drift. Related: Transfer learningTransfer learning Using data from other people or other days to shorten calibration for a new user. . Glossary entry gesture. You will meet the same problem, worse, with EEGElectroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. Related: Electrocorticography (ECoG)Electrocorticography (ECoG) Recording from electrodes placed on the surface of the brain under the skull, usually during epilepsy surgery evaluation; cleaner and sharper than EEG. , Magnetoencephalography (MEG)Magnetoencephalography (MEG) Recording the tiny magnetic fields produced by cortical currents with superconducting sensors in a shielded room; less blurred by the skull than EEG, and far more expensive. , Volume conductionVolume conduction The spreading of currents from a source through the conductive tissues of the head, which is why one source shows up on many electrodes and why scalp EEG is blurry. , Microvolt (µV)Microvolt (µV) One millionth of a volt. Scalp EEG is tens of microvolts; a AA battery is 1.5 million of them. . Glossary entry in Phase 3.
Parts
| Part | Where | Qty | Approx. |
|---|---|---|---|
| Disposable snap ECG electrodes, bag of 50 3M Red Dot, $11.40 for fifty. Clip the alligator leads onto the snap studs rather than buying leads; a set of four 3.5 mm snap leads is $9.99 if you want them tidy. | Amazon | 1 | $12 |
| ESP32 DevKit (or Raspberry Pi Pico) For streaming from the ADS1299 board over USB later. Either board works; pick one ecosystem and learn it. | Amazon, Adafruit, SparkFun | 1 | $9 |
| 3D printing access (campus makerspace) or a Bambu A1 mini Free on campus after the safety certification, which is the right answer for almost everyone. Buying your own is $299 and is worth it by Phase 2 only if you print weekly. | Marriott Library or Lassonde makerspace; Bambu Lab if buying | 1 | free |
| Eight reusable snap electrode pads and a fabric armband $7.99 for twenty reusable TENS pads with 3.5 mm snaps, plus elastic and hook-and-loop for the band. The reusable pads lose adhesion after a few dozen applications; disposable ECG electrodes give cleaner contact per session. | Amazon | 1 | $12 |
| Total (prices drift; treat as a ceiling) | $33 | ||
The band
Eight electrodesElectrode The conductor that turns ion currents in tissue into electron currents in a wire; its chemistry and contact quality set the noise you live with. Related: Silver/silver-chloride (Ag/AgCl)Silver/silver-chloride (Ag/AgCl) The standard electrode material for biopotentials, because its chemistry produces a stable, low-noise, low-drift interface with salty gel. , Electrode impedanceElectrode impedance How hard it is to push current through the skin-electrode contact, typically 5 to 50 kilohms with gel and megohms dry, higher at low frequencies. , Half-cell potentialHalf-cell potential The DC voltage that appears wherever a metal meets an electrolyte; two electrodes with different half-cell potentials produce an offset that can swamp the signal. . Glossary entry evenly spaced around the thickest part of the forearm, a hand’s width below the elbow, held by a stretchy fabric band with the electrodesElectrode The conductor that turns ion currents in tissue into electron currents in a wire; its chemistry and contact quality set the noise you live with. Related: Silver/silver-chloride (Ag/AgCl)Silver/silver-chloride (Ag/AgCl) The standard electrode material for biopotentials, because its chemistry produces a stable, low-noise, low-drift interface with salty gel. , Electrode impedanceElectrode impedance How hard it is to push current through the skin-electrode contact, typically 5 to 50 kilohms with gel and megohms dry, higher at low frequencies. , Half-cell potentialHalf-cell potential The DC voltage that appears wherever a metal meets an electrolyte; two electrodes with different half-cell potentials produce an offset that can swamp the signal. . Glossary entry sewn or snapped in. Bipolar pairs work best (each channel measures between two adjacent electrodesElectrode The conductor that turns ion currents in tissue into electron currents in a wire; its chemistry and contact quality set the noise you live with. Related: Silver/silver-chloride (Ag/AgCl)Silver/silver-chloride (Ag/AgCl) The standard electrode material for biopotentials, because its chemistry produces a stable, low-noise, low-drift interface with salty gel. , Electrode impedanceElectrode impedance How hard it is to push current through the skin-electrode contact, typically 5 to 50 kilohms with gel and megohms dry, higher at low frequencies. , Half-cell potentialHalf-cell potential The DC voltage that appears wherever a metal meets an electrolyte; two electrodes with different half-cell potentials produce an offset that can swamp the signal. . Glossary entry along the arm), but a monopolar arrangement referenced to an electrodeElectrode The conductor that turns ion currents in tissue into electron currents in a wire; its chemistry and contact quality set the noise you live with. Related: Silver/silver-chloride (Ag/AgCl)Silver/silver-chloride (Ag/AgCl) The standard electrode material for biopotentials, because its chemistry produces a stable, low-noise, low-drift interface with salty gel. , Electrode impedanceElectrode impedance How hard it is to push current through the skin-electrode contact, typically 5 to 50 kilohms with gel and megohms dry, higher at low frequencies. , Half-cell potentialHalf-cell potential The DC voltage that appears wherever a metal meets an electrolyte; two electrodes with different half-cell potentials produce an offset that can swamp the signal. . Glossary entry on the elbow is simpler and adequate. The bias electrodeElectrode The conductor that turns ion currents in tissue into electron currents in a wire; its chemistry and contact quality set the noise you live with. Related: Silver/silver-chloride (Ag/AgCl)Silver/silver-chloride (Ag/AgCl) The standard electrode material for biopotentials, because its chemistry produces a stable, low-noise, low-drift interface with salty gel. , Electrode impedanceElectrode impedance How hard it is to push current through the skin-electrode contact, typically 5 to 50 kilohms with gel and megohms dry, higher at low frequencies. , Half-cell potentialHalf-cell potential The DC voltage that appears wherever a metal meets an electrolyte; two electrodes with different half-cell potentials produce an offset that can swamp the signal. . Glossary entry goes on the wrist bone.
Configure the amplifier for EMGElectromyography (EMG) Recording the electrical activity of muscles, hundreds of microvolts to millivolts, much larger than EEG. Related: Myoelectric prosthesisMyoelectric prosthesis An artificial limb controlled by EMG from the remaining muscles. , Electroencephalography (EEG)Electroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. . Glossary entry: sample at 1000 per second, gainGain How many times an amplifier multiplies its input; 1000× turns 50 microvolts into 50 millivolts, enough for an ADC to see. Related: Instrumentation amplifierInstrumentation amplifier A precision differential amplifier with very high input impedance and high CMRR, built from three op-amps and sold as a single chip such as the INA128 or AD8232. . Glossary entry 12 or so (EMGElectromyography (EMG) Recording the electrical activity of muscles, hundreds of microvolts to millivolts, much larger than EEG. Related: Myoelectric prosthesisMyoelectric prosthesis An artificial limb controlled by EMG from the remaining muscles. , Electroencephalography (EEG)Electroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. . Glossary entry is bigger than EEGElectroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. Related: Electrocorticography (ECoG)Electrocorticography (ECoG) Recording from electrodes placed on the surface of the brain under the skull, usually during epilepsy surgery evaluation; cleaner and sharper than EEG. , Magnetoencephalography (MEG)Magnetoencephalography (MEG) Recording the tiny magnetic fields produced by cortical currents with superconducting sensors in a shielded room; less blurred by the skull than EEG, and far more expensive. , Volume conductionVolume conduction The spreading of currents from a source through the conductive tissues of the head, which is why one source shows up on many electrodes and why scalp EEG is blurry. , Microvolt (µV)Microvolt (µV) One millionth of a volt. Scalp EEG is tens of microvolts; a AA battery is 1.5 million of them. . Glossary entry), high-pass at 20 Hz and low-pass at 450 Hz in software.
Features, not raw samples
A classifierClassifier An algorithm that assigns each trial a label, such as left hand or right hand, after being trained on labelled examples. Related: Linear discriminant analysis (LDA)Linear discriminant analysis (LDA) A simple, robust classifier that draws a straight boundary between classes; the workhorse of EEG decoding for two decades. , Support vector machine (SVM)Support vector machine (SVM) A classifier that finds the boundary with the widest margin between classes; strong on small datasets. , Cross-validationCross-validation Testing a model on data it never saw during training, repeatedly, so the reported accuracy means something. . Glossary entry does not want a thousand samples a second per channel. It wants a handful of numbers that summarize a short window. The classic EMGElectromyography (EMG) Recording the electrical activity of muscles, hundreds of microvolts to millivolts, much larger than EEG. Related: Myoelectric prosthesisMyoelectric prosthesis An artificial limb controlled by EMG from the remaining muscles. , Electroencephalography (EEG)Electroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. . Glossary entry features, computed on each channel over a 200 millisecond window: root mean square amplitude, waveform length (the sum of absolute differences between successive samples), zero-crossing count, and slope-sign-change count. Eight channels times four features is a 32-number description of what your hand is doing right now.
Collect, then train, then test honestly
Record each gesture for five seconds, rest for three, repeat five times per gesture. Label the windows. Train a linear discriminant analysisLinear discriminant analysis (LDA) A simple, robust classifier that draws a straight boundary between classes; the workhorse of EEG decoding for two decades. Related: ClassifierClassifier An algorithm that assigns each trial a label, such as left hand or right hand, after being trained on labelled examples.. Glossary entry classifierClassifier An algorithm that assigns each trial a label, such as left hand or right hand, after being trained on labelled examples. Related: Linear discriminant analysis (LDA)Linear discriminant analysis (LDA) A simple, robust classifier that draws a straight boundary between classes; the workhorse of EEG decoding for two decades. , Support vector machine (SVM)Support vector machine (SVM) A classifier that finds the boundary with the widest margin between classes; strong on small datasets. , Cross-validationCross-validation Testing a model on data it never saw during training, repeatedly, so the reported accuracy means something. . Glossary entry with scikit-learn; it is the standard for EMGElectromyography (EMG) Recording the electrical activity of muscles, hundreds of microvolts to millivolts, much larger than EEG. Related: Myoelectric prosthesisMyoelectric prosthesis An artificial limb controlled by EMG from the remaining muscles. , Electroencephalography (EEG)Electroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. . Glossary entry, it is fast, and it is very hard to overfit.
Then test it the honest way. Do not shuffle all the windows and hold out 20 percent; that puts windows from the same five-second recording into both training and test and gives you a number you cannot trust. Hold out whole repetitions: train on repetitions one to four, test on five. Then, the real test, take the band off, put it back on, record a fresh set, and test on that. Write down all three numbers. The gap between them is the most important thing you will learn in this project.
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.model_selection import GroupKFold, cross_val_score
clf = LinearDiscriminantAnalysis()
# X: windows × 32 features, y: gesture labels, groups: repetition index
scores = cross_val_score(clf, X, y, groups=groups, cv=GroupKFold(n_splits=5))
print(scores.mean()) # within-session, honest split by repetitionClose the loop
Stream windows, compute features, predict, and show the predicted gesture on screen with a 300 millisecond majority vote to stop it flickering. Then map gestures to something: a robot hand, a game, the volume on your laptop. Latency should be under half a second or it feels wrong.
- Build the band and confirm eight clean channels on the plotter: rest is flat, fist lights up the channels on the inside of the arm.
- Write the feature extractor and check it on a single clench: RMS rises, zero crossings fall.
- Record the six gestures, five repetitions each, with labels.
- Train LDALinear discriminant analysis (LDA) A simple, robust classifier that draws a straight boundary between classes; the workhorse of EEG decoding for two decades. Related: ClassifierClassifier An algorithm that assigns each trial a label, such as left hand or right hand, after being trained on labelled examples. . Glossary entry. Report accuracy three ways: shuffled windows (the wrong way, for comparison), grouped by repetition, and on a fresh session after re-donning the band.
- Run it live with a majority vote. Time the latency.
- Save the confusion matrix and the three accuracies. Note which gestures confuse each other and why (wrist extension and open hand share muscles).
Where this leads
Every idea here reappears in Phase 3 with EEGElectroencephalography (EEG) Recording the brain's electrical activity from electrodes on the scalp, a few tens of microvolts of blurred, summed cortical activity. Related: Electrocorticography (ECoG)Electrocorticography (ECoG) Recording from electrodes placed on the surface of the brain under the skull, usually during epilepsy surgery evaluation; cleaner and sharper than EEG. , Magnetoencephalography (MEG)Magnetoencephalography (MEG) Recording the tiny magnetic fields produced by cortical currents with superconducting sensors in a shielded room; less blurred by the skull than EEG, and far more expensive. , Volume conductionVolume conduction The spreading of currents from a source through the conductive tissues of the head, which is why one source shows up on many electrodes and why scalp EEG is blurry. , Microvolt (µV)Microvolt (µV) One millionth of a volt. Scalp EEG is tens of microvolts; a AA battery is 1.5 million of them. . Glossary entry, where the signals are a thousand times smaller and the cross-session problem is worse. Read classification done honestly next; you have just felt every one of its warnings. In Phase 5 this band becomes a controller for a real user or the front end of a silent speech interface.