ArticleSensors (Basel, Switzerland)2013
Lower limb wearable capacitive sensing and its applications to recognizing human gaits.
Article in Sensors (Basel, Switzerland), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 26 citations in OpenAlex.
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- Gait Recognition for Lower Limb Exoskeletons Based on Interactive Information Fusion.Applied bionics and biomechanics · 2022Review
- Design of a Purely Mechanical Sensor-Controller Integrated System for Walking Assistance on an Ankle-Foot Exoskeleton.Sensors (Basel, Switzerland) · 2019Article
- Multi-Axis Force Sensor for Human-Robot Interaction Sensing in a Rehabilitation Robotic Device.Sensors (Basel, Switzerland) · 2017Article
- Gait Phase Recognition for Lower-Limb Exoskeleton with Only Joint Angular Sensors.Sensors (Basel, Switzerland) · 2016Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working stability, adaptability to disturbance and locomotion mode recognition are carried out to validate the effectiveness of the proposed approach. Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated. With an event-dependent linear discriminant analysis classifier and feature selection procedure, four time-domain features are used for pattern recognition and satisfactory recognition accuracies (97:3% ± 0:5%, 97:0% ± 0:4%, 95:6% ± 0:9% and 97:0% ± 0:4% for four phases of one gait cycle respectively) are obtained. The accuracies are comparable with that from electromyography-based systems and inertial-based systems. The results validate the effectiveness of the proposed lower limb capacitive sensing approach in recognizing human normal gaits.
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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.