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An introduction to biosensors

This article looks at technologies for measuring biosignals, that is, activity within the body itself. Let's explore.
Microphone cables an stands on a persian carpet.
© Alexander Refsum Jensenius, University of Oslo

In this article, we will explore how it is possible to measure biosignals, that is activity within the body itself.

What are biosignals?

Sensors measuring biosignals are often also called physiological sensors. Most of these sensors share the same sensing principle, that of measuring electrical current in various parts of the body.

But since the biosignals vary considerably in strength throughout the body, the sensors are optimised differently:

  • Galvanic skin response (GSR) refers to changes in skin conductance and is often used on the fingers or in the palm of the hand. The GSR signal is highly correlated with emotional changes, and such sensors have been used to some extent in music research (see next video) as well as in music performance. A challenge with such signals is that may not be entirely straightforward to interpret, and elements like sweat may become an issue when worn for longer periods of time.
  • Electromyograms (EMG) is used to measure muscle activity and are particularly effective on the arms of musicians to pick up information about hand and finger motion. A challenge with EMG is to place the sensor(s) in a way such that they pick up the muscle activity properly.
  • Electrocardiograms (EKG) measure the electrical pulses from the heart and can be used to extract information about heart rate and heart rate variability. The latter has been shown to correlate with emotional state and has also been used in music research.
  • Electroencephalograms (EEG) are used to measure electrical pulses from the brain, using either a few sensors placed on the forehead or hats with numerous sensors included. Due to the weak brain signals, such sensors need to have strong amplifiers and are therefore also suspect to a lot of interference and noise. Nevertheless, such sensors have also been applied in both music analysis and performance.


© Alexander Refsum Jensenius, University of Oslo
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