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Are you planning a research project using EEG/ECG data?
We offer everything that comes after the raw data acquisition. Including cleaning, feature extraction, and data analysis.
Fast and cost-effectively.
For companies in the EU, CH, US, and all over the world.
We have developed modular feature extraction software with a portfolio of clinically validated and experimental EEG and ECG markers.
If you are looking for specific features, we are looking forward to discussing them in detail. Our current flagship markers are the following:
EEG vigilance
EEG-vigilance is an established biomarker in depression. Depressed patients have been shown to have a slower decline in vigilance over time. The predictive value of EEG vigilance for treatment outcomes using SSRIs and SNRIs has been shown in different studies, including the largest study using EEG in depression (iSPOT trial, Olbrich et al. 2016, >1000 patients). EEG-vigilance as a treatment prediction marker has recently been validated in a separate dataset (Cheng et al. 2021)
EEG alpha peak frequency
EEG alpha peak frequency has been shown to be a predictor of treatment outcomes for treatment with Sertraline (Arns et al., 2015, Van der Vinne et al., 2021). Furthermore, evidence that treatment using an rTMS protocol with 1 Hz stimulation over the rDLPFC can be more effective than treatment using a 10 Hz protocol over the lDLPFC if the APF differs significantly from 10 Hz (Corlier et al., 2019, Roelofs et al., 2021).
EEG alpha asymmetry
EEG alpha asymmetry has been developed as a diagnostic marker for depression. However, recently it has been shown that the asymmetry of the EEG-alpha power in frontal regions is a predictor of treatment outcome for SSRI treatment in female patients (Van der Vinne et al., 2019; Van der Vinne et al., 2021). These results have been replicated in an independent dataset (Ip et al., 2021).
Heart Rate variability markers
The heart rate variability markers are derived from the ECG data. The markers include time domain measures such as heart rate and SDNN (standard deviation of consecutive R-peaks) and frequency domain measures such as the low frequency power (LF), high frequency power (HF) and the normalized ratio between LF and HF. The HRV markers inform on the activity of the autonomic nervous system and allow differentiation between the parasympathetic and sympathetic activity. HRV markers have been shown to be predictive in two randomized trials on ketamine in depression (Meyer er al., 2021). HRV markers also allow to predict the treatment outcome for SNRI treatment (Olbrich et al., 2016).
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