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Asynchronous Averaging of Gait Cycles for Classification of Gait and Device Modes [article]

Parinaz Kasebzadeh, Gustaf Hendeby, Fredrik Gustafsson
2019 arXiv   pre-print
The gait signature represents one full cycle of the human gait, and is suitable for off-line or on-line classification of the gait mode.  ...  The gait signatures enable a high classification rate for each step cycle.  ...  Then, based on the asynchronous averaging of the gait cycles, a unique signature for each scenario was estimated.  ... 
arXiv:1907.02329v2 fatcat:n6bafsq335gy3oaaylt6pf26pm

Lower Limb Wearable Capacitive Sensing and Its Applications to Recognizing Human Gaits

Enhao Zheng, Baojun Chen, Kunlin Wei, Qining Wang
2013 Sensors  
± 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.  ...  Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated.  ...  At last, the data of 40 gait cycles for each motion modes was acquired.  ... 
doi:10.3390/s131013334 pmid:24084122 pmcid:PMC3859067 fatcat:7mshgcnombhsxd2dutgckf7pvy

On the Design of a Wearable Multi-sensor System for Recognizing Motion Modes and Sit-to-stand Transition

Enhao Zheng, Baojun Chen, Xuegang Wang, Yan Huang, Qining Wang
2014 International Journal of Advanced Robotic Systems  
The overall motion mode recognition accuracy was 99.9% during the stance phase and 98.5% during the swing phase. For sit-to-stand transition recognition, the average accuracy was 99.9%.  ...  The system was built to measure both kinematic (tilt angles) and dynamic (ground contact forces) signals of human gaits.  ...  With a phase-dependent classifier, the average error accuracies of five locomotion modes for four phases were 19.6%, 12.6%, 5.2%, and 6.3%, respectively.  ... 
doi:10.5772/57788 fatcat:ecltdywi5vhqrl2a2fiuumql4q

Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton

Gang Du, Jinchen Zeng, Cheng Gong, Enhao Zheng, Musa L. Audu
2021 Applied Bionics and Biomechanics  
The average time delay during the transitions was 1897.9 ms (28.95% one gait cycle). The results were at the same level as the related studies.  ...  The average recognition accuracy was 92.46% for intrasubject crossvalidation and 93.16% for intersubject crossvalidation.  ...  Conflicts of Interest The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.  ... 
doi:10.1155/2021/6673018 fatcat:puz5vwxowzaqlaizkr2f4mmwzi

Gait Classification with Gait Inherent Attribute Identification from Ankle's Kinematics

Yogesh Singh, Vineet Vashista
2022 IEEE transactions on neural systems and rehabilitation engineering  
, demonstrate our proposed algorithm's potential as a high-level automatic switching framework in robotic gait interventions for multimodal walking.  ...  This association changes depending on the different gait patterns of day-to-day life.  ...  Classification of walking modes is essential for the effective administration of intervention through robotic devices.  ... 
doi:10.1109/tnsre.2022.3162035 pmid:35324446 fatcat:jmrzhy3wlfhl3hjcx5p3lfe43u

A wearable capacitive sensing system with phase-dependent classifier for locomotion mode recognition

Enhao Zheng, Baojun Chen, Qining Wang, Kunlin Wei, Long Wang
2012 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)  
The proposed system includes two rings as sensing front-ends of body capacitance, two sensing circuits for processing the signals and the gait event detection system.  ...  Locomotion mode recognition is one of the most important aspects for the control of motion rehabilitation systems, e.g. lower-limb prostheses and exoskeletons.  ...  It is one of the main advantages of this kind of sensors used for human motion mode recognition. [4] used AM-FM model for gait pattern classification based on accelerometry data.  ... 
doi:10.1109/biorob.2012.6290721 fatcat:tvqs76fglrdxtixlzckig5zd54

Trunk and hip muscle activity in early walkers with and without cerebral palsy – A frequency analysis

Laura A. Prosser, Samuel C.K. Lee, Mary F. Barbe, Ann F. VanSant, Richard T. Lauer
2010 Journal of Electromyography & Kinesiology  
Functional principal component analysis (PCA) revealed that IMNF was significantly higher in the CP group throughout the gait cycle for all muscles.  ...  A time-frequency pattern was generated using the continuous wavelet transform and instantaneous mean frequency (IMNF) was calculated at each interval of the gait cycle.  ...  Acknowledgments The authors thank Steve Capella and Jenny Lee for assistance with data collection, and Diana Deshefy, DPT, Samuel Pierce, PT, PhD and Erin Sheeder, DPT for assistance with participant recruitment  ... 
doi:10.1016/j.jelekin.2010.04.005 pmid:20472460 pmcid:PMC2914128 fatcat:ekcubdwf4bgevedsrj2o6exk3m

EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots

Madiha Tariq, Pavel M. Trivailo, Milan Simic
2018 Frontiers in Human Neuroscience  
All applications' key features and their interaction with the environment are reviewed for the EEG-based activity mode recognition, and presented in form of a table.  ...  Each sub layer of the BCI operator is discussed in detail, highlighting the feature extraction, classification and execution methods employed by the various systems.  ...  ACKNOWLEDGMENTS Authors acknowledge the financial support received for this research provided by RMIT University Ph.D. International Scholarship (RPIS).  ... 
doi:10.3389/fnhum.2018.00312 pmid:30127730 pmcid:PMC6088276 fatcat:us3lwc23uvh47javazpf4ynm3y

Hybrid Deep-Learning Framework Based on Gaussian Fusion of Multiple Spatiotemporal Networks for Walking Gait Phase Recognition

Tao Zhen, Jian-lei Kong, Lei Yan
2020 Complexity  
Human gait phase detection is a significance technology for robotics exoskeletons control and exercise rehabilitation therapy.  ...  Inertial Measurement Units (IMUs) with accelerometer and gyroscope are convenient and inexpensive to collect gait data, which are often used to analyze gait dynamics for personal daily applications.  ...  Studies have shown that the swing phase accounts for 40% of the entire gait cycle, while the standing phase accounts for 60% of the entire gait cycle [34] .  ... 
doi:10.1155/2020/8672431 fatcat:x7eujr2iqrewliqh5e467xloaa

Learning Gait Parameters for Locomotion in Virtual Reality Systems [chapter]

Jingbo Zhao, Robert S. Allison
2018 Lecture Notes in Computer Science  
We provide an explanation for the variable performance of the participants based on the locomotion technique.  ...  Mechanical repositioning is a locomotion technique that uses a locomotion interface to cancel the displacement of a user for walking on the spot.  ...  A gait cycle has three important phases: the initial swing, the mid swing and the terminal swing [25] .  ... 
doi:10.1007/978-3-319-91863-1_5 fatcat:ec7z7iiwpbdv7g72nggz6in5ie

A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets and Challenges [article]

Chuanfu Shen, Shiqi Yu, Jilong Wang, George Q. Huang, Liang Wang
2022 arXiv   pre-print
Then deep learning for gait recognition is discussed from the perspective of deep representations and architecture with an in-depth summary.  ...  Following our proposed taxonomy with novelty, it can be beneficial for providing inspiration and promoting the perception of deep gait recognition.  ...  Gait Energy Image (GEI) [36] is the most popular one for its low computational cost and temporal robustness. GEI represents the average of the cyclic silhouettes.  ... 
arXiv:2206.13732v1 fatcat:cvat2gdvfrbubkhsfybpk7qvzm

Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review

Haroon Khan, Noman Naseer, Anis Yazidi, Per Kristian Eide, Hafiz Wajahat Hassan, Peyman Mirtaheri
2021 Frontiers in Human Neuroscience  
Imminent technical breakthroughs are expected using hybrid EEG-fNIRS-based BCI for gait to control assistive devices and Monitor neuro-plasticity in neuro-rehabilitation.  ...  Fusing EEG and fNIRS is a well-known and established methodology proven to enhance brain–computer interface (BCI) performance in terms of classification accuracy, number of control commands, and response  ...  In other applications, EEG signals are used to trigger robotic devices by continuous classification and asynchronous detection of lower limb movement (Liu et al., 2018) .  ... 
doi:10.3389/fnhum.2020.613254 pmid:33568979 pmcid:PMC7868344 fatcat:syxy7hu74fdj7e3azv7etcglya

A five-state P300-based foot lifter orthosis: Proof of concept

Matthieu Duvinage, Thierry Castermans, Rene Jimenez-Fabian, Thomas Hoellinger, Caty De Saedeleer, Mathieu Petieau, Karthik Seetharaman, Guy Cheron, Olivier Verlinden, Thierry Dutoit
2012 2012 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC)  
Furthermore, the CPG pattern frequency and magnitude can be adapted according to the specific gait behavior of the patient and his desired speed.  ...  This paper proves the concept of combining a human gait model based on a CPG and a classic but non-natural P300 BCI in order to consider the user's intent.  ...  The authors also thank Kevin Nis and Léandre Gohy for the SBC development and Sirris for the orthosis machining.  ... 
doi:10.1109/brc.2012.6222193 fatcat:7edcbmdmrfbtxmzjzd27oid2iu

Table of contents

2021 IEEE Sensors Journal  
Falk 520 Asynchronous Averaging of Gait Cycles for Classification of Gait and Device Modes ............................... ..........................................................................  ...  Scandurra 394 Impact Assessment of the Asynchronous Clocks Between Reference and User Receivers in Differential Pseudolite Navigation System ............................................................  ... 
doi:10.1109/jsen.2020.3039123 fatcat:ec5ehbrpxnaljgvork4tbo4mka

An Adaptive Hybrid Control Architecture for an Active Transfemoral Prosthesis

Aniket Mazumder, Edsko E. G. Hekman, Raffaella Carloni
2022 IEEE Access  
The daily usage of a prosthesis for people with an amputation consists of phases of intermittent and continuous walking patterns.  ...  For intermittent walking, an interpolation-based algorithm generates control signals for the ankle and knee joints, whereas, for continuous walking, the control signals are generated utilizing an adaptive  ...  ., Iceland, www.ossur.com) for providing the foot blade of the prosthesis and also would like to thank Vera G. M.  ... 
doi:10.1109/access.2022.3173348 fatcat:7gxgffouxfcijath47g33p4pnq
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