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Julius Welzel

Publications and source records attributed to Julius Welzel.

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A portable solution for simultaneous human movement and mobile EEG acquisition: readiness potential for basketball free-throw shooting

Advances in wireless electroencephalography (EEG) technology promise to record brain-electrical activity in everyday situations. To better understand the relationship between brain activity and natural behavior, it is necessary to monitor human movement patterns. Here, we present a pocketable setup consisting of two smartphones to simultaneously capture human posture and EEG signals. We asked 26 basketball players to shoot 120 free throws each. First, we investigated whether our setup allows us to capture the readiness potential (RP) that precedes voluntary actions. Second, we investigated whether the RP differs between successful and unsuccessful free-throw attempts. The results confirmed the presence of the RP over fronto-central channels, with significant negative deflection at channel Cz, from -400 to 0 ms before movement onset ($M$ $\pm$ $SE$: -6.54 $\pm$ 2.26 to -13.52 $\pm$ 2.42 $\mu$V; $z$ = -2.53 to -3.92; FDR-corrected $p$ = 0.049 to 0.003; $r$ = 0.50 to 0.77). However, the amplitude of the RP was not related to shooting success (all FDR-corrected $p$ > 0.05; maximum mean $R^2$ = 0.047, i.e., 4.7% explained variance). Preliminary exploratory pose analysis conducted offline indicated the presence of participant-specific variations in posture between successful and unsuccessful shots in 38.5% of participants (10/26), with 4.5% explained variance (maximum mean landmark $R^2$ = 0.045). We conclude that a highly portable, low-cost and lightweight acquisition setup, consisting of two smartphones and a head-mounted wireless EEG amplifier, is sufficient to monitor complex human movement patterns and associated brain dynamics outside the laboratory.

cs.NE

UNISEP: A Unified Sensor Placement Framework for Human Motion Capture and Wearables

The proliferation of wearable sensors and monitoring technologies has created a need for standardized sensor placement protocols. While existing standards like the Surface Electromyography for Non-Invasive Assessment of Muscles (SENIAM) recommendations for electromyography (EMG) and the 10-20 system for electroencephalography (EEG) address modality-specific applications, no comprehensive framework spans different sensing modalities and applications. We present the Unified Sensor Placement (UNISEP) framework to facilitate reproducible handling of human movement and physiological data across various systems and research domains. The framework provides a method to describe coordinate systems and placement protocols based on anatomical landmarks, and is designed to complement existing data-sharing standards such as the Brain Imaging Data Structure (BIDS) and Hierarchical Event Descriptors (HED). Even during its proposal stage, the UNISEP approach has been adopted by the EMG-BIDS extension (BIDS version 1.11.0), confirming the community need for a unified, machine-readable sensor placement framework. The UNISEP framework facilitates consistency, reproducibility, and interoperability in applications ranging from lab-based clinical biomechanics to continuous health monitoring in everyday life.

q-bio.QM