EMG signal analysis for online estimation of a joint angle validated through human kinematic

Valentini, Riccardo; Michieletto, Stefano; Toffano, Federico; Spolaor, Fabiola; Sawacha, Z.; Pagello, Enrico

doi:10.1016/j.gaitpost.2015.07.034

Cited by 3 publications

(3 citation statements)

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“…Therefore, it is crucial to properly choose the mother wavelet for obtaining good results. Previous studies [17] [19] showed good results for both accuracy and time by using the db2 mother wavelet from the Daubechies family for representing the input EMGs. Finally, a synthesis function extracted a single value representative of the whole window.…”

Section: A Signal Preprocessingmentioning

confidence: 99%

Subject Independent EMG Analysis by Using Low-Cost Hardware

Stival

Michieletto

Pagello³

2018

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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Thanks to the increasing interest on robotics prosthetic devices controlled by means of physiological signals, a continuously increasing number of solutions are proposed. Usually the proposed solutions are very expensive and created ad-hoc for the final user. For this reason, a large part of the possible users can not afford this kind of technology. Furthermore, the software adaptation to the user is time consuming and physically stressing for the subject. The paper presents a low cost prosthesis framework, which covers the three fundamental aspects of a rehabilitation system, i.e. the prosthesis, the sensors used to record the physiological signals, and the software connecting the two previous points. To reduce the costs we chose a 3D printed prosthetic hand from an opensource project. We recorded Electromyography (EMG) signals from the subjects' muscles by using a low cost armband, a allin-one solution easy to wear and remove. The EMG signals are preprocessed in order to be used online, and they are used to train a probabilistic model for classification purposes. Furthermore, the model is built on data from different subjects, in order to develop a subject-independent framework, which can be used by any subject, with no need of draining training phases. We test the goodness of our solution with a leave-oneout approach by classifying three different hand grasps. Finally, the 3D printed hand reproduces the movement performed by the subject. Data were recorded from four different subjects, each of them repeating the selected movements five times, and we obtained an overall accuracy of 76.8%.

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Section: A Signal Preprocessingmentioning

confidence: 99%

Subject Independent EMG Analysis by Using Low-Cost Hardware

Stival

Michieletto

Pagello³

2018

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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“…With the further development of technology, the combination of human posture estimation algorithm and depth image is becoming closer and closer. However, the depth image of traditional human posture estimation algorithm is generally nonlinear data, which have a large amount of redundant information, which will lead to huge problems in the data reliability of human motion model [12,13]. e sports training system is mainly developed under the action of multi-disciplinary integration.…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of Motion Training System Assisted by Human Posture Estimation Algorithm

Dang

Dong

et al. 2022

Scientific Programming

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With the rapid development of computer technology and electronic information technology, the sports training system no longer depends on the traditional algorithm for operation support, and various advanced posture algorithms are emerging. At the same time, it also further optimizes the intelligence and accuracy of the sports training algorithm. As an advanced algorithm combined with virtual reality technology, human posture estimation algorithm plays an obvious role in optimizing the effect of sports training. This paper will design a motion training system based on the optimized and improved human posture trajectory algorithm, use the depth image correlation theory to solve the problem of non-Gaussian noise crosstalk in the depth image of the traditional human posture algorithm in principle, improve the accurate feature extraction of the depth image by the algorithm, and solve the problem of human feature redundancy, so as to further improve the accuracy of the establishment of a single human model; on the problem of multi-person posture estimation algorithm, this paper proposes a high-resolution multi-person posture high-precision network model and adds the focus mechanism. Based on this, this paper realizes the high-precision and high-speed modeling of multi-person posture, so as to provide an accurate model for the multi-person function of sports training system and improve the efficiency of the algorithm. In the experimental part, this paper takes tennis as a typical case to design the sports training system and experiments based on the system designed in this paper. The experimental results show that the system under the proposed algorithm has obvious advantages in accuracy and training effect.

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“…Most studies on sEMG-based joint angle estimation to control the prostheses and exoskeleton systems mainly aim to obtain a better off-line estimation performance according to algorithm improvement in feature extraction and estimation process [12], [13], [14], [15]. Some methods can achieve a extremely good estimation performance (higher than 95% accuracy) [16].…”

Section: Introductionmentioning

confidence: 99%