ArticleSensors (Basel, Switzerland)2020
Gait Segmentation Method Using a Plantar Pressure Measurement System with Custom-Made Capacitive Sensors.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- A toolbox for the identification of foot-floor contact sequences to analyze atypical gait cycles in a real-life scenario: application on patients after proximal femur fracture and healthy elderly.Journal of neuroengineering and rehabilitation · 2025Article
- Better Understanding Rehabilitation of Motor Symptoms: Insights from the Use of Wearables.Pragmatic and observational research · 2025Review
- Center of Pressure Measurement Accuracy via Insoles with a Reduced Pressure Sensor Number during Gaits.Sensors (Basel, Switzerland) · 2024Article
- Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare-A Survey.Sensors (Basel, Switzerland) · 2024Review
- Design, Analysis, and Development of Low-Cost State-of-the-Art Magnetorheological-Based Microprocessor Prosthetic Knee.Sensors (Basel, Switzerland) · 2024Article
- Dynamic Characterization of a Low-Cost Fully and Continuously 3D Printed Capacitive Pressure-Sensing System for Plantar Pressure Measurements.Sensors (Basel, Switzerland) · 2023Article
- Artificial intelligence enhanced sensors - enabling technologies to next-generation healthcare and biomedical platform.Bioelectronic medicine · 2023Review
- Electronic textiles: New age of wearable technology for healthcare and fitness solutions.Materials today. Bio · 2023Review
- Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities.Heliyon · 2023Review
- A Deep Learning Model for 3D Ground Reaction Force Estimation Using Shoes with Three Uniaxial Load Cells.Sensors (Basel, Switzerland) · 2023Article
- Smart Shoe Insole Based on Polydimethylsiloxane Composite Capacitive Sensors.Sensors (Basel, Switzerland) · 2023Article
- A 3D-Printed Capacitive Smart Insole for Plantar Pressure Monitoring.Sensors (Basel, Switzerland) · 2022Article
- Customized Textile Capacitive Insole Sensor for Center of Pressure Analysis.Sensors (Basel, Switzerland) · 2022Article
- Detection of Human Gait Phases Using Textile Pressure Sensors: A Low Cost and Pervasive Approach.Sensors (Basel, Switzerland) · 2022Article
- Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson's Populations.Sensors (Basel, Switzerland) · 2021Article
- The Design and Simulation of a 16-Sensors Plantar Pressure Insole Layout for Different Applications: From Sports to Clinics, a Pilot Study.Sensors (Basel, Switzerland) · 2021Article
- A Prosthetic Socket with Active Volume Compensation for Amputated Lower Limb.Sensors (Basel, Switzerland) · 2021Article
- Relationship between Plantar Pressure and Sensory Disturbance in Patients with Hansen's Disease-Preliminary Research and Review of the Literature.Sensors (Basel, Switzerland) · 2020Review
- Smart Socks and In-Shoe Systems: State-of-the-Art for Two Popular Technologies for Foot Motion Analysis, Sports, and Medical Applications.Sensors (Basel, Switzerland) · 2020Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gait analysis has been widely studied by researchers due to the impact in clinical fields. It provides relevant information on the condition of a patient's pathologies. In the last decades, different gait measurement methods have been developed in order to identify parameters that can contribute to gait cycles. Analyzing those parameters, it is possible to segment and identify different phases of gait cycles, making these studies easier and more accurate. This paper proposes a simple gait segmentation method based on plantar pressure measurement. Current methods used by researchers and clinicians are based on multiple sensing devices (e.g., multiple cameras, multiple inertial measurement units (IMUs)). Our proposal uses plantar pressure information from only two sensorized insoles that were designed and implemented with eight custom-made flexible capacitive sensors. An algorithm was implemented to calculate gait parameters and segment gait cycle phases and subphases. Functional tests were performed in six healthy volunteers in a 10 m walking test. The designed in-shoe insole presented an average power consumption of 44 mA under operation. The system segmented the gait phases and sub-phases in all subjects. The calculated percentile distribution between stance phase time and swing phase time was almost 60%/40%, which is aligned with literature reports on healthy subjects. Our results show that the system achieves a successful segmentation of gait phases and subphases, is capable of reporting COP velocity, double support time, cadence, stance phase time percentage, swing phase time percentage, and double support time percentage. The proposed system allows for the simplification of the assessment method in the recovery process for both patients and clinicians.
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