Intent based recognition of walking and ramp activities for amputee using sEMG based lower limb prostheses

Hussain, Tahir; Iqbal, Nadeem; Maqbool, Hafiz Farhan; Khan, Muhammad Shahid; Awad, Mohammed I.; Dehghani-Sanij, Abbas A.

doi:10.1016/j.bbe.2020.05.010

Cited by 33 publications

(17 citation statements)

References 47 publications

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“…By monitoring EMG patterns, prostheses can hierarchically adjust low-level autonomous control (e.g. finite state machine) to switch control based on recognized locomotion modes [ 2 , 4 , 29 , 76 , 77 ]. Essentially, supervisory EMG controllers are built upon autonomous locomotion-mode-dependent prosthesis control, where the joint mechanics in each mode are dominated by the low-level autonomous control.…”

Section: Literature Reviewmentioning

confidence: 99%

“…number of zero crossings, mean absolute value, and slope sign change) [ 26 , 29 , 80 , 90 ] and frequency domain (e.g. medium frequency [ 76 ], bi-spectrum [ 77 ]) features have been used previously. Additionally, adding autoregression coefficients for EMG features can account for potential signal degradation, fatigue, and motion artifacts [ 29 , 73 , 91 – 93 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The reported accuracy rate ranges from 75% to 99%. Usually task transition can be predicted accurately before the defined critical timings [ 26 , 77 , 92 , 93 ]. The most common classification error is between ramps and level-ground walking [ 29 , 92 , 102 ].…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions

et al. 2021

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Objective. Advanced robotic lower limb prostheses are mainly controlled autonomously. Although the existing control can assist cyclic movements during locomotion of amputee users, the function of these modern devices is still limited due to the lack of neuromuscular control (i.e. control based on human efferent neural signals from the central nervous system to peripheral muscles for movement production). Neuromuscular control signals can be recorded from muscles, called electromyographic (EMG) or myoelectric signals. In fact, using EMG signals for robotic lower limb prostheses control has been an emerging research topic in the field for the past decade to address novel prosthesis functionality and adaptability to different environments and task contexts. The objective of this paper is to review robotic lower limb Prosthesis control via EMG signals recorded from residual muscles in individuals with lower limb amputations. Approach. We performed a literature review on surgical techniques for enhanced EMG interfaces, EMG sensors, decoding algorithms, and control paradigms for robotic lower limb prostheses. Main results. This review highlights the promise of EMG control for enabling new functionalities in robotic lower limb prostheses, as well as the existing challenges, knowledge gaps, and opportunities on this research topic from human motor control and clinical practice perspectives. Significance. This review may guide the future collaborations among researchers in neuromechanics, neural engineering, assistive technologies, and amputee clinics in order to build and translate true bionic lower limbs to individuals with lower limb amputations for improved motor function.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions

et al. 2021

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“…At present, Chinese Wushu has not been included in the Olympic Games [ 9 ], and the reasons mainly include many types of Wushu, difficulty in determining the event, and the difficulty in scoring the competition. But even if Wushu is not included in the Olympic Games, its profound cultural heritage and accumulation always show its exuberant vitality.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion

Zhao

2021

Journal of Healthcare Engineering

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The developments of modern science and technology have significantly promoted the progress of sports science. Advanced technological methods have been widely used in sports training, which has not only improved the scientific level of training but also promoted the continuous growth of sports technology and competition results. Competitive Wushu routine is an important part of Chinese Wushu. The development trend of competitive Wushu routine affects the development of the whole Wushu movement. To improve the training effect of the Wushu routine using artificial intelligence, this paper employed fuzzy information processing and feature extraction technology to analyze the visual features in the process of Wushu competition. The deep neural network-based region segmentation method was employed for implicit feature extraction to examine the shape, texture, and other image features of Wushu routines and improve the recognition performance. The proposed feature extraction model achieved the highest average accuracy of 93.98% accuracy as compared to other contemporary algorithms. Finally, the model was evaluated to validate the superior performance of the proposed method in improving the decision-making ability and effective instruction ability of the martial arts routine competition.

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“…Wearable sensors work effectively in recording kinematic data, whereas various gait detectors have been developed under the combination of low-cost sensors. These gait detectors include manual switches [10,11], foot switches [10,11], shank inclinations [12], force-sensitive resistors [13], goniometers [14,15], gyroscopes [16], accelerometers, and electromyography (EMG) sensors [17][18][19][20]. These sensors could be used to detect the walking pattern and identify the gait phases.…”

Section: Introductionmentioning

confidence: 99%

Low‐Cost Multisensor Integrated System for Online Walking Gait Detection

Yan

Wei

et al. 2021

Journal of Sensors

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A three-dimensional motion capture system is a useful tool for analysing gait patterns during walking or exercising, and it is frequently applied in biomechanical studies. However, most of them are expensive. This study designs a low-cost gait detection system with high accuracy and reliability that is an alternative method/equipment in the gait detection field to the most widely used commercial system, the virtual user concept (Vicon) system. The proposed system integrates mass-produced low-cost sensors/chips in a compact size to collect kinematic data. Furthermore, an x86 mini personal computer (PC) running at 100 Hz classifies motion data in real-time. To guarantee gait detection accuracy, the embedded gait detection algorithm adopts a multilayer perceptron (MLP) model and a rule-based calibration filter to classify kinematic data into five distinct gait events: heel-strike, foot-flat, heel-off, toe-off, and initial-swing. To evaluate performance, volunteers are requested to walk on the treadmill at a regular walking speed of 4.2 km/h while kinematic data are recorded by a low-cost system and a Vicon system simultaneously. The gait detection accuracy and relative time error are estimated by comparing the classified gait events in the study with the Vicon system as a reference. The results show that the proposed system obtains a high accuracy of 99.66% with a smaller time error (32 ms), demonstrating that it performs similarly to the Vicon system in the gait detection field.

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Intent based recognition of walking and ramp activities for amputee using sEMG based lower limb prostheses

Cited by 33 publications

References 47 publications

Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions

Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions

Artificial Intelligence Auxiliary Algorithm for Wushu Routine Competition Decision Based on Feature Fusion

Low‐Cost Multisensor Integrated System for Online Walking Gait Detection

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