Alexander von Lühmann

Alexander von Lühmann
Technische Universität Berlin | TUB · Department of Software Engineering and Theoretical Computer Science

Doctor of Engineering

About

31
Publications
17,207
Reads
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716
Citations
Citations since 2016
28 Research Items
713 Citations
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Introduction
AvL is Head of the Independent Research Group "Multimodal Biosensing" at BIFOLD, TU Berlin, and CSO at NIRx Medical Technology. He is also visiting researcher at the Boston University Neurophotonics Center. His research interests are in hybrid wearable brain-body imaging using diffuse optics (focus: fNIRS) and biopotentials (EEG). His research focuses on the design of multimodal diffuse optical instruments and multimodal signal processing towards neurotechnology applications outside of the lab.
Additional affiliations
January 2019 - present
Boston University
Position
  • PostDoc Position
September 2018 - December 2018
Technische Universität Berlin
Position
  • PostDoc Position
March 2017 - May 2017
University of Maryland, Baltimore County
Position
  • Researcher
Description
  • Visiting researcher at the Machine Learning for Signal Processing (MLSP) lab
Education
July 2014 - August 2018
Technische Universität Berlin
Field of study
  • Machine Learning & Biomedical Engineering
October 2011 - April 2014
Karlsruhe Institute of Technology
Field of study
  • Electrical Engineering and Information Technology
October 2008 - October 2011
Karlsruhe Institute of Technology
Field of study
  • Electrical Engineering and Informatiom Technology

Publications

Publications (31)
Article
Full-text available
Objective: For the further development of the fields of telemedicine, neurotechnology and Brain-Computer Interfaces (BCI), advances in hybrid multimodal signal acquisition and processing technology are invaluable. Currently, there are no commonly available hybrid devices combining bio-electrical and bio-optical neurophysiological measurements (her...
Conference Paper
Full-text available
Objective: In medical applications, neuroscience and brain-computer interface research, bimodal acquisition of brain activity using Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS) is at the moment achieved by combining separate commercial devices. We have investigated quantitatively whether dedicated hybrid systems e...
Article
Full-text available
In the analysis of functional Near-Infrared Spectroscopy (fNIRS) signals from real-world scenarios, artifact rejection is essential. However, currently there exists no gold-standard. Although a plenitude of methodological approaches implicitly assume the presence of latent processes in the signals, elaborate Blind-Source-Separation methods have rar...
Article
Full-text available
For the robust estimation of evoked brain activity from functional Near Infrared Spectroscopy (fNIRS) signals, it is crucial to reduce nuisance signals from systemic physiology and motion. The current best practice incorporates short separation (SS) fNIRS measurements as regressors in a General Linear Model (GLM). However, several challenging signa...
Conference Paper
Full-text available
Wearables and machine learning have opened up a new field of research, the Neuroscience of the Everyday World. We present our recent contributions to fNIRS instrumentation (ninjaNirs and ninjaCap) and multimodal analysis (BLISSA2RD and GLM with tCCA).
Preprint
Full-text available
Short-separation regression (SS) and diffuse optical tomography (DOT) image reconstruction, two widely adopted methods in functional near-infrared spectroscopy (fNIRS), have been demonstrated to individually facilitate the separation of brain activation and physiological signals, with further improvement by using both sequentially. Motivated by the...
Preprint
Full-text available
When analyzing complex scenes, humans often focus their attention on an object at a particular spatial location. The ability to decode the attended spatial location would facilitate brain computer interfaces for complex scene analysis. Here, we investigated functional near-infrared spectroscopy's (fNIRS) capability to decode audio-visual spatial at...
Article
Full-text available
Significance: Functional near-infrared spectroscopy (fNIRS) is a noninvasive technique for measuring hemodynamic changes in the human cortex related to neural function. Due to its potential for miniaturization and relatively low cost, fNIRS has been proposed for applications, such as brain-computer interfaces (BCIs). The relatively large magnitude...
Poster
Full-text available
We propose an image reconstruction algorithm that performs short separation (SS) generalized linear model (GLM) and image reconstruction simultaneously.
Article
Functional Near-Infrared Spectroscopy (fNIRS) assesses human brain activity by noninvasively measuring changes of cerebral hemoglobin concentrations caused by modulation of neuronal activity. Recent progress in signal processing and advances in system design, such as miniaturization, wearability and system sensitivity, have strengthened fNIRS as a...
Article
Full-text available
Besides passive recording of brain electric or magnetic activity, also non-ionizing electromagnetic or optical radiation can be used for real-time brain imaging. Here, changes in the radiation’s absorption or scattering allow for continuous in vivo assessment of regional neurometabolic and neurovascular activity. Besides magnetic resonance imaging...
Article
Full-text available
The application of functional near-infrared spectroscopy (fNIRS) in the neurosciences has been expanding over the last 40 years. Today, it is addressing a wide range of applications within different populations and utilizes a great variety of experimental paradigms. With the rapid growth and the diversification of research methods, some inconsisten...
Article
Full-text available
Within a decade, single trial analysis of functional Near Infrared Spectroscopy (fNIRS) signals has gained significant momentum, and fNIRS joined the set of modalities frequently used for active and passive Brain Computer Interfaces (BCI). A great variety of methods for feature extraction and classification have been explored using state-of-the-art...
Thesis
Full-text available
In neuroscience and related fields, progress in instrumentation, computational power, and signal processing methods continuously provide novel and increasingly powerful tools toward the investigation of brain activity in real-time and everyday environments. Research into real-life and application-oriented, non-invasive neurotechnology bears a numbe...
Article
Full-text available
We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided...
Article
Full-text available
We provide an open access dataset for hybrid brain-computer interfaces (BCIs) using electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we conducted two BCI experiments (left versus right hand motor imagery; mental arithmetic versus resting state). The dataset was validated using baseline signal analysis methods, with whic...
Conference Paper
Full-text available
Brain-computer interfaces are now entering real-life environments. Particular hybrid systems using more than one input signal, e.g. electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), offer a broad spectrum of applications in basic research and clinical neuroscience. Here, we provide an overview of recent EEG-electrode a...
Conference Paper
Full-text available
Stroke can be defined as a sudden onset of neurological deficits caused by a focal injury to the central nervous system from a vascular cause. In ischemic stroke (~87% of all strokes) and transient ischemic attack (TIA), the blood vessel carrying blood to the brain is blocked causing deficit in the glucose supply – the main energy source. Here, neu...
Conference Paper
Full-text available
Introduction: The increasing computational capacity and miniaturization of modern microprocessors in wearable computers and smartphones pushes the trend towards mobile body sensors and telemedicine. In contrast, brain activity assessments and Brain Computer Interfaces (BCI) are only slowly leaving static, lab based domains. At the same time, an inc...
Conference Paper
Full-text available
Over the last decade, the range of Brain-Computer Interface applications has substantially been enlarged by combining BCI with other physiological or technical signals. Also, comparatively new technologies like functional Near-Infrared Spectroscopy (fNIRS) joined the modality set used for multi-modal BCI or for the enhancement of EEG based BCI. To...
Research
Full-text available
As a result of the loss of the active movement of the upper extremity, for example, by a spinal cord injury, patients lose the major part of their autonomy and of their quality of life. This leads to a life-long dependency on caregivers. Within the BMBF-funded project OrthoJacket, a modular, active orthosis for the upper extremity is developed. In...
Article
Full-text available
Brain-Computer Interfaces (BCIs) and neuroergonomics research have high requirements regarding robustness and mobility. Additionally, fast applicability and customization are desired. Functional Near-Infrared Spectroscopy (fNIRS) is an increasingly established technology with a potential to satisfy these conditions. EEG acquisition technology, curr...
Patent
Full-text available
Capacitive sensor system for measurement of electromagnetic bio-signals, has two capacitive sensors which are provided for measurement of bioelectric field, and for detecting relative movement of two relatively movable elements
Article
Full-text available
As a result of the loss of the active movement of the upper extremity, for example, by a spinal cord injury, patients lose the major part of their autonomy and of their quality of life. This leads to a life-long dependency on caregivers. Within the BMBF-funded project OrthoJacket, a modular, active orthosis for the upper extremity is developed. In...

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Projects

Project (1)
Project
Development of multimodal Instrumentation and signal processing methods for robustification of neurotechnology applications: BCI and Monitoring under out of lab conditions. Using fNIRS, EEG and other physiological auxiliary signals.