Assessing learning effort with hand motion tracking methods

Rheem, Hansol; Becker, David V.; Craig, Scotty D.

doi:10.1002/acp.3784

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…The COVID-19 pandemic is the starting point for learning changes from three aspects: the media, teachers, and students who are indirectly required to adapt to conditions [9]- [11]. The readiness of educational institutions to deal with online learning during the COVID-19 pandemic is a differentiator in the expected quality of learning.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Integrated Learning Management Systems FLearn in Improving Learning Outcomes at Universities during Online Learning

Sanoto

Kusuma²,

Paseleng³

2023

intensif

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The problem in learning during the covid-19 pandemic is how the university implements effective online learning for students. In order to facilitate online learning to be more comprehensive and integrated, the development of an integrated learning system, namely the learning system in Flexibel Learning or Leaning management, is expected to increase the effectiveness of online learning. The research method in this study is a mixed-method research method with a sequential exploratory model. The research begins with a qualitative study to find the root of the problem and then continues with quantitative analysis to find the influence between variables. The study subjects were fourth-year students in the mathematics education study program. The study results show that the integration of the system facilitates the implementation of learning in the online learning process, but there are still obstacles, such as internet access and learning devices. In contrast, the regression test results show a significant influence between the integration of the learning system on student learning outcomes. The influence of learning system integration on learning achievement is 61.3%, and 38.7% is affected by other factors such as motivation, learning independence, student responsibility, and adequate internet access.

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Section: Introductionmentioning

confidence: 99%

The Effect of Integrated Learning Management Systems FLearn in Improving Learning Outcomes at Universities during Online Learning

Sanoto

Kusuma²,

Paseleng³

2023

intensif

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An approach to continuous hand movement recognition using SEMG based on features fusion

et al. 2022

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Hand gesture recognition based improved multi-channels CNN architecture using EMG sensors

Wei

Wen

et al. 2022

IFS

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With the continuous development of sensor and computer technology, human-computer interaction technology is also improving. Gesture recognition has become a research hotspot in human-computer interaction, sign language recognition, rehabilitation training, and sports medicine. This paper proposed a method of hand gestures recognition which extracts the time domain and frequency domain features from surface electromyography (sEMG) by using an improved multi-channels convolutional neural network (IMC-CNN). The 10 most commonly used hand gestures are recognized by using the spectral features of sEMG signals which is the input of the IMC-CNN model. Firstly, the third-order Butterworth low-pass filter and high-pass filter are used to denoise the sEMG signal. Secondly, effective sEMG signal segment from denoised signal is applied. Thirdly, the spectrogram features of different channels’ sEMG signals are merged into a comprehensive improved spectrogram feature which is used as the input of IMC-CNN to classify the hand gestures. Finally, the recognition accuracy of IMC-CNN model, three single channel CNN of IMC-CNN model, SVM, LDA, LCNN and EMGNET are compared. The experiment was carried out on the same dataset and the same computer. The experimental results showed that the recognition accuracy, sensitivity and accuracy of the proposed model reached 97.5%, 97.25% and 96.25% respectively. The proposed method not only has high average recognition accuracy on MYO collected dataset, but also has high average recognition accuracy on NinaPro DB5 dataset. Overall, the proposed model has more advantages in accuracy and efficiency than that of the comparison models.

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Assessing learning effort with hand motion tracking methods

Cited by 3 publications

References 40 publications

The Effect of Integrated Learning Management Systems FLearn in Improving Learning Outcomes at Universities during Online Learning

The Effect of Integrated Learning Management Systems FLearn in Improving Learning Outcomes at Universities during Online Learning

An approach to continuous hand movement recognition using SEMG based on features fusion

Hand gesture recognition based improved multi-channels CNN architecture using EMG sensors

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