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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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DATASET_SDALLE

Human Activity Recognition (HAR) dataset for lower limb rehabilitation devices
Authors: Abdellatif Hamed IBRAHIM, Ahmed; Atef El-Khoreby, Mohamed; Kamal Moawad, Azza; Hussien Issa, Hanady; Ismail Fawaz, Shereen; Ibrahim Awad, Mohammed; Khaled Farouk, Mohamed;
Abstract

The goal of this research is to capture and record precise lower-body muscle activity during activities such as walking, jumping, and stair navigation, all with the aim of designing a lower-limb exoskeleton to enhance mobility and rehabilitation. This dataset is collected from 9 healthy subjects. SDALLE DAQ system is used for data collection with the inclusion of EMG and IMU sensors. Data has been extracted from the following muscles: (Rectus Femoris, Vastus Medialis, Vastus Lateralis, and Semitendinosus muscles on both the left and right sides). The intended activities are walking, jogging, stairs up and stairs down This dataset is collected as part of the work done on the research project "Development of a Smart Data Acquisition system for Lower Limb Exoskeletons (SDALLE)" which is funded by Information Technology Industry Development Agency (ITIDA) – Information Technology Academia Collaboration (ITAC) program named grant CFP243/PRP.

Keywords

Activities of Daily Living/classification, Deep Learning, Wearable Robotics, Human Activity Recognition, Activities of Daily Living, EMG Sensors, IMU sensors

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average