Method Development for Synchronizing Processor Time of Accelerometer with Computer for Sensor-Equipped Health Measurements, by Marcus Holzschuher, Rebecca Heintz, Joseph Russell, Maria Lißner, Jeroen Bergmann and Anja Winkler, narrated in full by Joseph Russell, as presented at EMBC on 14 July 2025.

Full article available at: https://portal.findresearcher.sdu.dk/en/publications/method-development-for-synchronizing-processor-time-of-accelerome/

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This paper presents a method for the precise synchronization of inertial measurement unit (IMU) data with a computer system clock, using a motor-controlled turntable, to allow more accurate labelling of motion data. Using the case of human reaction time measurement, where motion is recorded as a response to a computer-controlled visual signal, this methodology proved capable of compensating for IMU clock drift and latency between systems, providing a robust and simple solution for applications in a wide range of IMU-sensor-equipped systems.

© 2025 by the authors.

Human Dead Reckoning Using a Particle Filter and Map Constraints, by Joseph Russell and Jeroen H.M. Bergmann, narrated in full by Joseph Russell, as published by Sensors on 2 June 2026, article 3500.

Full article available at: https://doi.org/10.3390/s26113500

This recording is part of an initiative by SDU's Biomedical Engineering Centre to improve the accessibility of scientific papers with human-narrated article readings. The text is read out in full in the same manner as a non-fiction unabridged audiobook, with the article displayed page-by-page on-screen for those wishing to see figures, equations and references (the video component is available on YouTube and Spotify).

This paper presents an approach for tracking a person’s position by integrating inertial measurement unit (IMU) sensor values, utilising a particle filter with known physical constraints, such as a map of the space. While such approaches are well established, the effect of constraint choice in the absence of observation measurements remains poorly understood. The effect of varying the tolerance of these constraints is investigated with data collected from a Movella DOT held by a human participant walking around a 100 m running track. In particular, the dimensions of the map are varied, along with the shape. Results showed (a) that it is viable to correct particle filter error without external sensor feedback, provided constraints are provided, with a mean error of 1.8 m, and (b) there is a minimum acceptable tolerance of map width around the edge of the true activity zone, in this case approximately 8 m, and that tightening the map boundary further than this can counterintuitively lead to reduced accuracy.

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© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.