Modelling group delay in electrophysiology electrodes for Internet of Things wearables

Wearable devices form a key part of the Internet of Things. As wearables are made smaller and more socially discrete, there is the potential for non-ideal effects to limit the performance of the overall system. Factors such as noise and comfort have been extensively studied previously. This paper investigates group delay as an understudied performance factor. We focus on devices for the collection of heart signals and brain signals via electrophysiology and determine bounds on the design of electrodes for future systems to ensure timing accuracy. Modelling the electrode-body contact system as a series resistor R<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</inf> and parallel resistor-capacitor tank (R<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf> and C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf>), we show that R<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf> has the greatest impact on the system group delay. For sampling frequencies of 200 Hz, 500 Hz, and 1 kHz, the maximum tolerable R<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf> before the group delay is larger than one sampling period is 560 kΩ, 200 kΩ and 100 kΩ respectively. These results can be used to help inform the design of future electrophysiology electrodes and data collection instrumentation, and Internet of Things deployments which rely on precise temporal information being collected on physiological parameters.