Mixed-signal template-based reduction scheme for stimulus artifact removal in electrical stimulation

Simultaneous electrical stimulation and recording are used to gain insights into the function of neuronal circuitry. However, artifacts produced by the electrical stimulation pulses prevent the recording of neural responses during, and a short period after, the stimulation duration. In this work, we...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Medical & biological engineering & computing 2013-04, Vol.51 (4), p.449-458
Hauptverfasser: Nguyen, Thi Kim Thoa, Musa, Silke, Eberle, Wolfgang, Bartic, Carmen, Gielen, Georges
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Simultaneous electrical stimulation and recording are used to gain insights into the function of neuronal circuitry. However, artifacts produced by the electrical stimulation pulses prevent the recording of neural responses during, and a short period after, the stimulation duration. In this work, we describe a mixed-signal recording topology with template subtraction for removing the artifact during the stimulation pulse. Emulated artifacts generated from a lumped electrical circuit model and experimental artifacts in cardiac cell cultures are used to evaluate the topology. The simulations show that delays between the emulated artifact and its estimated compensation template represent the largest error source of the analog template subtraction. The quantization error appears like random noise and determines the threshold level for the action potential detection. Simulations show that removal of the artifacts is possible, allowing the detection of action potentials during the stimulation pulsing period, even for high-amplitude saturating artifacts. Measurement results with artifacts elicited in cardiac cell cultures show feasible applications of this topology. The proposed topology therefore promisingly opens up a previously unavailable detection window for improving the analysis of the neuronal activity.
ISSN:0140-0118
1741-0444
DOI:10.1007/s11517-012-1013-6