RETRACTED: Image recognition algorithm for exercise fatigue based on FPGA processor and motion image capture

Tang, Nana

doi:10.1016/j.micpro.2020.103756

Cited by 5 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, it can be seen from Figure 6 that although the acceleration and angular velocity curves of the three axes have obvious periodic variation laws, the periodicity of the y -axis acceleration is more prominent. Therefore, the subsequent analysis and identification are based on the y -axis acceleration data [ 18 ].…”

Section: Gymnastics Movement Recognition Systemmentioning

confidence: 99%

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

Zhou

2022

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

In order to track the limb movement trajectory of gymnasts, a method based on MEMS inertial sensor is proposed. The system mainly collects the acceleration and angular velocity data of 11 positions during gymnastics by constructing sensor network. Based on the two kinds of preprocessed data, the parameters such as sample mean, standard deviation, information entropy, and mean square error are calculated as classification features, the support vector machine (SVM) classification model is established, and the movements of six kinds of gymnastics are effectively recognized. The experimental results show that when the human body is doing gymnastics, the measured three-axis acceleration values are between -0.5 g~2.2 g, -1 g~2.8 g, and -1.8 g~1 g, respectively, and the static error range accounts for only 1.6%~2% of the actual measured data range. Therefore, it is considered that such static error has little effect on the accuracy of data feature extraction and action recognition, which can be ignored. It is proved that MEMS inertial sensor can effectively track the movement trajectory of gymnasts’ limbs.

show abstract

Section: Gymnastics Movement Recognition Systemmentioning

confidence: 99%

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

Zhou

2022

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

show abstract

“…Rego et al [56] has found that exercise is a good way to increase cognitive abilities. The study of Tang [57] notes that fatigue affects physical and cognitive performance. In another study [58], the authors concluded that dance therapy improved gait and cognitive function.…”

Section: Cognitive Abilities and Exercisementioning

confidence: 99%

The influence of visitors’ specific motor actions on the perception and evaluation of museum exhibits

Yermakova,

Iermakov,

Tomanek

et al. 2023

ppcs

View full text Add to dashboard Cite

Background and Study Aim. An important element in the system of museum activities are approaches to attracting visitors. Among these approaches, one can single out the dialogue of the museum with visitors through specially organized active motor actions. Such actions have certain parameters (the nature of physical activity and its age-appropriateness, intensity, duration, etc.), which can influence the perception and evaluation of exhibits and the decision of visitors to return to the museum. The purpose of the study is an attempt to explain how specially organized active motor actions of visitors affect the perception and evaluation of museum exhibits and getting satisfaction from visiting. Material and Methods. Publications from the Web of Science Core Collection (WoS) were selected as the source of information. The search was carried out using keywords that characterize the interaction of visitors with the subject-spatial environment of the museum. The VOSviewer program was used to analyze the relationships between documents retrieved from WoS. Results. It is argued that the sedentary behavior of visitors, typical for many museums, does not contribute to their involvement in the museum space and the creation of meaning in museums. It is noted that an important aspect in the organization of special motor actions of visitors is the orientation to their motivation and interpretation of movements in the museum exhibits. The optimal level of physical activity has been identified. It creates a comfortable feeling and contributes to an adequate perception of the exhibits and corresponds to the main mission of the museum. Conclusions. Specially organized motor actions form the maximum motivation for visitors to study the museum exhibits. Such movements carry a certain semantic character of the theme of the museum.

show abstract

“…Xie Zhi and others used the fusion K-means clustering method to process EEG signals. This method can fully consider individual differences and achieve an 80% recognition effect [ 9 ]. Kwok Tai Chui and others used the SVM algorithm to process EEG signals.…”

Section: Literature Reviewmentioning

confidence: 99%

Motion Fatigue State Detection Based on Neural Networks

Wang

Yang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Aiming at the problem of fatigue state detection at the back of sports, a cascade deep learning detection system structure is designed, and a convolutional neural network fatigue state detection model based on multiscale pooling is proposed. Firstly, face detection is carried out by a deep learning model MTCNN to extract eye and mouth regions. Aiming at the problem of eye and mouth state representation and recognition, a multiscale pooling model (MSP) based on RESNET is proposed to train the eye and mouth state. In real-time detection, the state of the eye and mouth region is recognized through the trained convolution neural network model. Finally, the athlete’s fatigue is determined based on PERCLOS and the proposed mouth opening and closing frequency (FOM). The experimental results show that in the training process, we set the batch_size = 100 and the initial learning rate = 0.01. When the evaluation index is no longer improved, the learning rate is reduced by 10 times to 0.001, and a total of 50 epochs are trained. The precision and recall of the system are high. Compared with the infrared image simulating the night state, the RGB image taken by the ordinary camera in the daytime has higher precision and recall. It is proven that the neural network has high detection accuracy, meets the real-time requirements, and has high robustness in complex environments.

show abstract

RETRACTED: Image recognition algorithm for exercise fatigue based on FPGA processor and motion image capture

Cited by 5 publications

References 20 publications

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

Tracking of Gymnast’s Limb Movement Trajectory Based on MEMS Inertial Sensor

The influence of visitors’ specific motor actions on the perception and evaluation of museum exhibits

Motion Fatigue State Detection Based on Neural Networks

Contact Info

Product

Resources

About