ArticleScientific data2023
Surface electromyogram, kinematic, and kinetic dataset of lower limb walking for movement intent recognition.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gait analysis methods in people with spinal cord injury: a systematic review.Journal of neuroengineering and rehabilitation · 2026Pooled it
- GaitIntent: A Kinematic Dataset Focusing on Steady-State to Transitional Locomotion for Lower-Limb Motion Rehabilitation.Scientific data · 2026Article
- RTGNet: A Dual-Branch Network Integrating Recurrent Texture and Temporal Dynamics from sEMG for Lower-Limb Joint Angle Prediction.Sensors (Basel, Switzerland) · 2026Article
- Discovery of key surface electromyography features during walking for discerning high and low muscle mass using machine learning analysis.Scientific reports · 2026Article
- A Knee Rehabilitation Exercises Dataset for Postural Assessment using Wearable Devices.Scientific data · 2025Article
- Long duration multi-channel surface electromyographic signals during walking at natural pace: Data acquisition and analysis.PloS one · 2025Article
- Parameter identification and sensitivity analysis of a lower-limb musculoskeletal model.Frontiers in bioengineering and biotechnology · 2025Article
- AnkleImage - An ultrafast ultrasound image dataset to understand the ankle joint muscle contractility.Scientific data · 2024Article
- Phasor-Based Myoelectric Synergy Features: A Fast Hand-Crafted Feature Extraction Scheme for Boosting Performance in Gait Phase Recognition.Sensors (Basel, Switzerland) · 2024Article
- Mapping Method of Human Arm Motion Based on Surface Electromyography Signals.Sensors (Basel, Switzerland) · 2024Article
- Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models.Sensors (Basel, Switzerland) · 2024Article
- High-density EMG, IMU, kinetic, and kinematic open-source data for comprehensive locomotion activities.Scientific data · 2023Article
- Surface electromyogram, kinematic, and kinetic dataset of lower limb walking for movement intent recognition.Scientific data · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Surface electromyogram (sEMG) offers a rich set of motor information for decoding limb motion intention that serves as a control input to Intelligent human-machine synergy systems (IHMSS). Despite growing interest in IHMSS, the current publicly available datasets are limited and can hardly meet the growing demands of researchers. This study presents a novel lower limb motion dataset (designated as SIAT-LLMD), comprising sEMG, kinematic, and kinetic data with corresponding labels acquired from 40 healthy humans during 16 movements. The kinematic and kinetic data were collected using a motion capture system and six-dimensional force platforms and processed using OpenSim software. The sEMG data were recorded using nine wireless sensors placed on the subjects' thigh and calf muscles on the left limb. Besides, SIAT-LLMD provides labels to classify the different movements and different gait phases. Analysis of the dataset verified the synchronization and reproducibility, and codes for effective data processing are provided. The proposed dataset can serve as a new resource for exploring novel algorithms and models for characterizing lower limb movements.
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