Dataset for Multi-Sensor Analysis of Kinetics and Kinematics of Healthy Adults during Activities of Daily Living (ADL)

DOI:10.4121/3a5923e1-bf6b-4825-bc43-2a73bb7006cd.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/3a5923e1-bf6b-4825-bc43-2a73bb7006cd

Datacite citation style

Castellaz, Alessandro; Wouda, Frank (2025): Dataset for Multi-Sensor Analysis of Kinetics and Kinematics of Healthy Adults during Activities of Daily Living (ADL). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/3a5923e1-bf6b-4825-bc43-2a73bb7006cd.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset was collected to study the biomechanics of healthy adults during common Activities of Daily Living (ADLs). Data were acquired simultaneously from three wearable sensing systems:


- Inertial Measurement Units (IMUs), Movella MVN Link

- Pressure insoles, Moticon

- Force shoes, Xsens ForceShoe


In total, data from 6 healthy participants were recorded while performing the following movements:


- Timed Up and Go (TUG) Test

- Free Walking (FW)

- Stairs Ascending and Descending (SAD)

- Treadmill Walking – Slow (TS)

- Treadmill Walking – Fast (TF)


This multimodal dataset allows for the development and validation of algorithms for kinematic and kinetic analysis of human motion, with a focus on estimating ground reaction forces (GRF) using wearable sensors.

History

  • 2025-09-17 first online, published, posted

Publisher

4TU.ResearchData

Format

MATLAB/ .m, .mat text/ .txt README/ .md metadata/ .csv

Organizations

University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Biomedical Signals and Systems (BSS)

DATA

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