TY  - JOUR
A1  - Rauch, Florian
A1  - Fuchs, Sonja
A1  - Friedrich, Alexandra
A1  - Sieh, Daniel
A1  - Krummenacher, Ivo
A1  - Braunschweig, Holger
A1  - Finze, Maik
A1  - Marder, Todd B.
T1  - Highly Stable, Readily Reducible, Fluorescent, Trifluoromethylated 9‐Borafluorenes
JF  - Chemistry – A European Journal
N2  - Three different perfluoroalkylated borafluorenes (\(^{F}\)Bf) were prepared and their electronic and photophysical properties were investigated. The systems have four trifluoromethyl moieties on the borafluorene moiety as well as two trifluoromethyl groups at the ortho positions of their exo‐aryl moieties. They differ with regard to the para substituents on their exo‐aryl moieties, being a proton \(^{F}\)Xyl\(^{F}\)Bf, \(^{F}\)Xyl: 2,6‐bis(trifluoromethyl)phenyl), a trifluoromethyl group (\(^{F}\)Mes\(^{F}\)Bf, \(^{F}\)Mes: 2,4,6‐tris(trifluoromethyl)phenyl) or a dimethylamino group (p‐NMe\(_{2}\)‐\(^{F}\)Xyl\(^{F}\)Bf, p‐NMe\(_{2}\)‐\(^{F}\)Xyl: 4‐(dimethylamino)‐2,6‐bis(trifluoromethyl)phenyl), respectively. All derivatives exhibit extraordinarily low reduction potentials, comparable to those of perylenediimides. The most electron‐deficient derivative \(^{F}\)Mes\(^{F}\)Bf was also chemically reduced and its radical anion isolated and characterized. Furthermore, all compounds exhibit very long fluorescent lifetimes of about 250 ns up to 1.6 μs; however, the underlying mechanisms responsible for this differ. The donor‐substituted derivative p‐NMe\(_{2}\)‐\(^{F}\)Xyl\(^{F}\)Bf exhibits thermally activated delayed fluorescence (TADF) from a charge‐transfer (CT) state, whereas the \(^{F}\)Mes\(^{F}\)Bf and FXylFBf borafluorenes exhibit only weakly allowed locally excited (LE) transitions due to their symmetry and low transition‐dipole moments.
KW  - borafluorenes
KW  - boron
KW  - EPR spectroscopy
KW  - fluorescence
KW  - heterocycles
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-218390
VL  - 26
IS  - 56
SP  - 12794
EP  - 12808
ER  - 
TY  - JOUR
A1  - Friedrich, Maximilian U.
A1  - Schneider, Erich
A1  - Buerklein, Miriam
A1  - Taeger, Johannes
A1  - Hartig, Johannes
A1  - Volkmann, Jens
A1  - Peach, Robert
A1  - Zeller, Daniel
T1  - Smartphone video nystagmography using convolutional neural networks: ConVNG
JF  - Journal of Neurology
N2  - Background
Eye movement abnormalities are commonplace in neurological disorders. However, unaided eye movement assessments lack granularity. Although videooculography (VOG) improves diagnostic accuracy, resource intensiveness precludes its broad use. To bridge this care gap, we here validate a framework for smartphone video-based nystagmography capitalizing on recent computer vision advances.

Methods
A convolutional neural network was fine-tuned for pupil tracking using > 550 annotated frames: ConVNG. In a cross-sectional approach, slow-phase velocity of optokinetic nystagmus was calculated in 10 subjects using ConVNG and VOG. Equivalence of accuracy and precision was assessed using the “two one-sample t-test” (TOST) and Bayesian interval-null approaches. ConVNG was systematically compared to OpenFace and MediaPipe as computer vision (CV) benchmarks for gaze estimation.

Results
ConVNG tracking accuracy reached 9–15% of an average pupil diameter. In a fully independent clinical video dataset, ConVNG robustly detected pupil keypoints (median prediction confidence 0.85). SPV measurement accuracy was equivalent to VOG (TOST p < 0.017; Bayes factors (BF) > 24). ConVNG, but not MediaPipe, achieved equivalence to VOG in all SPV calculations. Median precision was 0.30°/s for ConVNG, 0.7°/s for MediaPipe and 0.12°/s for VOG. ConVNG precision was significantly higher than MediaPipe in vertical planes, but both algorithms’ precision was inferior to VOG.

Conclusions
ConVNG enables offline smartphone video nystagmography with an accuracy comparable to VOG and significantly higher precision than MediaPipe, a benchmark computer vision application for gaze estimation. This serves as a blueprint for highly accessible tools with potential to accelerate progress toward precise and personalized Medicine.
KW  - digital medicine
KW  - nystagmus
KW  - eye movement disorders
KW  - videooculography
KW  - computer vision
KW  - telemedicine
KW  - precision medicine
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324526
VL  - 270
IS  - 5
ER  -