ArticleNature communications2020
A wearable motion capture device able to detect dynamic motion of human limbs.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.
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Who cites it
54 citing papers in PubMed, 1 synthesis or guideline pooled it, 192 citations in OpenAlex.
- A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults.Sensors (Basel, Switzerland) · 2022Pooled it
- 1-D Collocated Dual-Gradient Sensory Fibers for Comprehensive Sensing and Decoding of Complex Human Motion and Physiology.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Synchrony Vision: An RGB-D Sensor-Based System for Real-Time Monitoring and Event-Level Analysis of Interpersonal Motion Synchrony.Sensors (Basel, Switzerland) · 2026Article
- A Tightly Coupled Multibody Dynamics and Multi-Sensor Fusion Algorithm for Simultaneous Kinematics and Kinetics Estimation.Sensors (Basel, Switzerland) · 2026Article
- Human motion recognition and prediction using loose cloth.Nature communications · 2026Article
- Ultrasensitive multi-degree-of-freedom piezoionic sensor via synergistic hydrogel-ion interactions.Nature communications · 2025Article
- Wearable technologies for assisted mobility in the real world.Nature communications · 2025Review
- Wearable Sensors for Precise Exercise Monitoring and Analysis.Biosensors · 2025Review
- Continuous biosignal acquisition beyond the limit of epidermal turnover.Materials horizons · 2025Review
- Enhancing Grasping Function with a Thermoresponsive Ionogel Adhesive Glove for Patients with Rheumatic Diseases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Materials and device strategies to enhance spatiotemporal resolution in bioelectronics.Nature reviews. Materials · 2025Article
- Closed-loop rehabilitation of upper-limb dyskinesia after stroke: from natural motion to neuronal microfluidics.Journal of neuroengineering and rehabilitation · 2025Review
- Multibody kinematics optimization for motion reconstruction of the human upper extremity using potential field method.Scientific reports · 2025Article
- Full Body-Worn Textile-Integrated Nanomaterials and Soft Electronics for Real-Time Continuous Motion Recognition Using Cloud Computing.ACS applied materials & interfaces · 2025Article
- Triboelectric Bending Sensors for AI-Enabled Sign Language Recognition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Fabric-Based Flexible Pressure Sensor Arrays with Ultra-Wide Pressure Range for Lower Limb Motion Capture System.Research (Washington, D.C.) · 2025Article
- Thoraco-abdominal biomechanical model and dual-layer control method for soft robotic system with application to respiratory assistance.Frontiers in bioengineering and biotechnology · 2025Article
- Hypersensitive meta-crack strain sensor for real-time biomedical monitoring.Science advances · 2024Article
- A New Measure for Quantifying Four-Limb Coordination of Human Gait Based on Mobility Sensors.Sensors (Basel, Switzerland) · 2024Article
- Motion capture-based evaluation of lower chopstick stability.Journal of physical therapy science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Limb motion capture is essential in human motion-recognition, motor-function assessment and dexterous human-robot interaction for assistive robots. Due to highly dynamic nature of limb activities, conventional inertial methods of limb motion capture suffer from serious drift and instability problems. Here, a motion capture method with integral-free velocity detection is proposed and a wearable device is developed by incorporating micro tri-axis flow sensors with micro tri-axis inertial sensors. The device allows accurate measurement of three-dimensional motion velocity, acceleration, and attitude angle of human limbs in daily activities, strenuous, and prolonged exercises. Additionally, we verify an intra-limb coordination relationship exists between thigh and shank in human walking and running, and establish a neural network model for it. Using the intra-limb coordination model, dynamic motion capture of human lower limbs including thigh and shank is tactfully implemented by a single shank-worn device, which simplifies the capture device and reduces cost. Experiments in strenuous activities and long-time running validate excellent performance and robustness of the wearable device in dynamic motion recognition and reconstruction of human limbs.
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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.