ArticleFrontiers in neurorobotics2019
Stance and Swing Detection Based on the Angular Velocity of Lower Limb Segments During Walking.
Article in Frontiers in neurorobotics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness.Journal of neuroengineering and rehabilitation · 2023Pooled it
- Movement therapy in advanced heart failure assisted by a lightweight wearable robot: a feasibility pilot study.ESC heart failure · 2022Trial
- Measurement of Cognitive and Kinematic Adaptation in Exoskeleton-Assisted Locomotion: Validation of an XR-Based Framework.Sensors (Basel, Switzerland) · 2026Article
- Cerebellar tonic inhibition orchestrates the maturation of information processing and motor coordination.Experimental & molecular medicine · 2026Article
- Gait Analysis Using Walking-Generated Acceleration Obtained from Two Sensors Attached to the Lower Legs.Sensors (Basel, Switzerland) · 2025Article
- A Review of Gait Analysis Using Gyroscopes and Inertial Measurement Units.Sensors (Basel, Switzerland) · 2025Review
- Enhancing Wearable Gait Monitoring Systems: Identifying Optimal Kinematic Inputs in Typical Adolescents.Sensors (Basel, Switzerland) · 2023Article
- A Novel Gait Phase Recognition Method Based on DPF-LSTM-CNN Using Wearable Inertial Sensors.Sensors (Basel, Switzerland) · 2023Article
- Inertial-Sensor-Based Monitoring of Sample Entropy and Peak Frequency Changes in Treadmill Walking during Recovery after Total Knee Arthroplasty.Sensors (Basel, Switzerland) · 2023Article
- Simplified Markerless Stride Detection Pipeline (sMaSDP) for Surface EMG Segmentation.Sensors (Basel, Switzerland) · 2023Article
- Article
- Data-efficient human walking speed intent identification.Wearable technologies · 2023Article
- Rules-Based Real-Time Gait Event Detection Algorithm for Lower-Limb Prosthesis Users during Level-Ground and Ramp Walking.Sensors (Basel, Switzerland) · 2022Article
- Gait Trajectory Prediction on an Embedded Microcontroller Using Deep Learning.Sensors (Basel, Switzerland) · 2022Article
- Learning to walk with a wearable robot in 880 simple steps: a pilot study on motor adaptation.Journal of neuroengineering and rehabilitation · 2021Article
- Generation of Gait Events with a FSR Based Cane Handle.Sensors (Basel, Switzerland) · 2021Article
- Outside testing of wearable robots for gait assistance shows a higher metabolic benefit than testing on treadmills.Scientific reports · 2021Article
- A Multi-Information Fusion Method for Gait Phase Classification in Lower Limb Rehabilitation Exoskeleton.Frontiers in neurorobotics · 2021Article
- Gait Trajectory and Gait Phase Prediction Based on an LSTM Network.Sensors (Basel, Switzerland) · 2020Article
- Gait Phase Recognition Using Deep Convolutional Neural Network with Inertial Measurement Units.Biosensors · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lower limb exoskeletons require the correct support magnitude and timing to achieve user assistance. This study evaluated whether the sign of the angular velocity of lower limb segments can be used to determine the timing of the stance and the swing phase during walking. We assumed that stance phase is characterized by a positive, swing phase by a negative angular velocity. Thus, the transitions can be used to also identify heel-strike and toe-off. Thirteen subjects without gait impairments walked on a treadmill at speeds between 0.5 and 2.1 m/s on level ground and inclinations between -10 and +10°. Kinematic and kinetic data was measured simultaneously from an optical motion capture system, force plates, and five inertial measurement units (IMUs). These recordings were used to compute the angular velocities of four lower limb segments: two biological (thigh, shank) and two virtual that were geometrical projections of the biological segments (virtual leg, virtual extended leg). We analyzed the reliability (two sign changes of the angular velocity per stride) and the accuracy (offset in timing between sign change and ground reaction force based timing) of the virtual and biological segments for detecting the gait phases stance and swing. The motion capture data revealed that virtual limb segments seem superior to the biological limb segments in the reliability of stance and swing detection. However, increased signal noise when using the IMUs required additional rule sets for reliable stance and swing detection. With IMUs, the biological shank segment had the least variability in accuracy. The IMU-based heel-strike events of the shank and both virtual segment were slightly early (3.3-4.8% of the gait cycle) compared to the ground reaction force-based timing. Toe-off event timing showed more variability (9.0% too early to 7.3% too late) between the segments and changed with walking speed. The results show that the detection of the heel-strike, and thus stance phase, based on IMU angular velocity is possible for different segments when additional rule sets are included. Further work is required to improve the timing accuracy for the toe-off detection (swing).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.