M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition Architecture for Miniaturized EEG-NIRS-Based Hybrid BCI and Monitoring

Alexander Von Luhmann, Heidrun Wabnitz, Tilmann Sander, Klaus Muller

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

Objective: For the further development of the fields of telemedicine, neurotechnology, and brain-computer interfaces, advances in hybrid multimodal signal acquisition and processing technology are invaluable. Currently, there are no commonly available hybrid devices combining bioelectrical and biooptical neurophysiological measurements [here electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS)]. Our objective was to design such an instrument in a miniaturized, customizable, and wireless form. Methods: We present here the design and evaluation of a mobile, modular, multimodal biosignal acquisition architecture (M3BA) based on a high-performance analog front-end optimized for biopotential acquisition, a microcontroller, and our openNIRS technology. Results: The designed M3BA modules are very small configurable high-precision and low-noise modules (EEG input referred noise @ 500 SPS 1.39 μVpp, NIRS noise equivalent power NEP750 nm = 5.92 pWpp, and NEP850 nm = 4.77 pWpp) with full input linearity, Bluetooth, 3-D accelerometer, and low power consumption. They support flexible user-specified biopotential reference setups and wireless body area/sensor network scenarios. Conclusion: Performance characterization and in-vivo experiments confirmed functionality and quality of the designed architecture. Significance: Telemedicine and assistive neurotechnology scenarios will increasingly include wearable multimodal sensors in the future. The M3BA architecture can significantly facilitate future designs for research in these and other fields that rely on customized mobile hybrid biosignal modal biosignal acquisition architecture (M3BA), multimodal, near-infrared spectroscopy (NIRS), wireless body area network (WBAN), wireless body sensor network (WBSN).

Original languageEnglish
Article number7563870
Pages (from-to)1199-1210
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Volume64
Issue number6
DOIs
Publication statusPublished - 2017 Jun 1

Keywords

  • Electroencephalography (EEG)
  • hybrid brain-computer interface (BCI)
  • mobile
  • modular
  • multimodal
  • multimodal biosignal acquisition architecture (M3BA)
  • near-infrared spectroscopy (NIRS)
  • wireless body area network (WBAN)
  • wireless body sensor network (WBSN)

ASJC Scopus subject areas

  • Biomedical Engineering

Fingerprint Dive into the research topics of 'M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition Architecture for Miniaturized EEG-NIRS-Based Hybrid BCI and Monitoring'. Together they form a unique fingerprint.

  • Cite this