Types of Biosignals: EEG, ECG, EMG, and Beyond

"The body is a machine, and we must understand its currents if we are to understand its functions."_{- Émil du Bois-Reymond, pioneer in electrophysiology.}‍

Life, though rare in the universe, leaves behind unmistakable footprints—biosignals. These signals not only confirm the presence of life but also narrate what a living being is doing, feeling, or thinking. As technology advances, we are learning to listen to these whispers of biology. Whether it’s improving health, enhancing performance, or building Brain-Computer Interfaces (BCIs), understanding biosignals is key.
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Among the most studied biosignals are:

• Electroencephalogram (EEG) – from the brain
• Electrocardiogram (ECG) – from the heart
• Electromyogram (EMG) – from muscles
• Galvanic Skin Response (GSR) – from skin conductance

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These signals are foundational for biosignal processing, real-time monitoring, and interfacing the human body with machines. In this article we look at some of these biosignals and some fascinating stories behind them.

Electroencephalography (EEG): Listening to Brainwaves

In 1893, a 19 year old Hans Berger fell from a horse and had a near death experience. Little did he know that it would be a pivotal moment in the history of neurotechnology. The same day he received a telegram from his sister who was extremely concerned for him because she had a bad feeling. Hans Berger was convinced that this was due to the phenomenon of telepathy. After all, it was the age of radio waves, so why can’t there be “brain waves”? In his ensuing 30 year career telepathy was not established but in his pursuit, Berger became the first person to record brain waves.
When neurons fire together, they generate tiny electrical currents. These can be recorded using electrodes placed on the scalp (EEG), inside the skull (intracranial EEG), or directly on the brain (ElectroCorticogram). EEG signal processing is used not only to understand the brain’s rhythms but also in EEG-based BCI systems, allowing communication and control for people with paralysis. Event-Related Potentials (ERPs) and Local Field Potentials (LFPs) are specialized types of EEG signals that provide insights into how the brain responds to specific stimuli.

Electrocardiogram (ECG): The Rhythm of the Heart

The heart has its own internal clock which produces tiny electrical signals every time it beats. Each heartbeat starts with a small electrical impulse made by a special part of the heart called the sinoatrial (SA) node. This impulse spreads through the heart muscle and makes it contract, first the upper (atria) and then lower chambers (ventricles)  – that’s what pumps blood. This process produces voltage changes, which can be recorded via electrodes on the skin.

This gives rise to the classic PQRST waveform, with each component representing a specific part of the heart’s cycle. Modern wearables and medical devices use ECG signal analysis to monitor heart health in real time.

Fun fact: The waveform starts with “P” because Willem Einthoven left room for earlier letters—just in case future scientists discovered pre-P waves!  So, thanks to a cautious scientist, we have the quirky naming system we still follow today.

Electromyography (EMG): The Language of Movement

When we perform any kind of movement - lifting our arm, kicking our leg, smiling, blinking or even breathing- our brain sends electrical signals to our muscles telling them to contract. When these neurons, known as motor neurons fire they release electrical impulses that travel to the muscle, causing it to contract. This electrical impulse—called a motor unit action potential (MUAP)—is what we see as an EMG signal. So, every time we move, we are generating an EMG signal!

Medical Applications

Medically, EMG is used for monitoring muscle fatigue especially in rehabilitation settings  and muscle recovery post-injury or surgery. This helps clinicians measure progress and optimize therapy. EMG can distinguish between voluntary and involuntary movements, making it useful in diagnosing neuromuscular disorders, assessing stroke recovery, spinal cord injuries, and motor control dysfunctions.

Performance and Sports Science

In sports science, EMG can tell us muscle-activation timing and quantify force output of muscle groups. These are important factors to measure performance improvement in any sport. The number of motor units recruited and the synergy between muscle groups, helps us capture “mind-muscle connection” and muscle memory. Such things which were previously spoken off in a figurative manner can be scientifically measured and quantified using EMG. By tracking these parameters we get  a window into movement efficiency and athletic performance. EMG is also used for biofeedback training, enabling individuals to consciously correct poor movement habits or retrain specific muscles

Beyond medicine and sports, EMG is used for gesture recognition in AR/VR and gaming, silent speech detection via facial EMG, and next-gen prosthetics and wearable exosuits that respond to the user’s muscle signals. EMG can be used in brain-computer interfaces (BCIs), helping paralyzed individuals control digital devices or communicate through subtle muscle activity. EMG bridges the gap between physiology, behavior, and technology—making it a critical tool in healthcare, performance optimization, and human-machine interaction.

As biosignal processing becomes more refined and neurotech devices more accessible, we are moving toward a world where our body speaks—and machines understand. Whether it’s detecting the subtlest brainwaves, tracking a racing heart, or interpreting muscle commands, biosignals are becoming the foundation of the next digital revolution. One where technology doesn’t just respond, but understands.