Analyzing the Effect of Badminton on Physical Health and Emotion Recognition on the account of Smart Sensors

Chang, Chun Yen; Chen, Kaihua; Cao, Jianjun; Wu, Qian; Chen, Hemu

doi:10.1155/2022/8349448

Cited by 3 publications

(5 citation statements)

References 21 publications

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“…They used the hand motion signals generated during writing to detect emotional states, but this is not friendly to longterm data monitoring under different writing habits. Chang et al [24] used intelligent inertial sensors to identify emotions during badminton movement, and sensors can respond to emotional changes, such as happiness, nausea, and sadness. However, with the increase of exercise time, the degree of physical fatigue affects the recognition effect of emotion.…”

Section: Related Workmentioning

confidence: 99%

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Attention‐based sensor fusion for emotion recognition from human motion by combining convolutional neural network and weighted kernel support vector machine and using inertial measurement unit signals

Zhao

Guo

Sun

et al. 2023

IET Signal Processing

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The remarkable development of human–computer interactions has created an urgent need for machines to be able to recognise human emotions. Human motions play a key role in emphasising and conveying emotions to meet the complexity of daily application scenarios, such as medical rehabilitation and social education. Therefore, this paper aims to explore hidden emotional states from human motions. Accordingly, we proposed a novel approach for emotion recognition using multiple inertial measurement unit (IMU) sensors worn on different body parts. First, the mapping relationship between emotion and human motion was established through fuzzy comprehensive evaluation, and data were collected for six emotional states: sleepy, bored, excited, tense, angry, and distressed. Second, the preprocessed data were used as input in a lightweight convolutional neural network to extract discriminative features. Third, an attention‐based sensor fusion module was developed to obtain the importance scores of each IMU sensor for generating a fused feature representation. In the recognition phase, we constructed a weighted kernel support vector machine (SVM) model with an auxiliary fuzzy function to improve the weight calculation method of kernel functions in a multiple kernel SVM. Finally, the results obtained are compared with those of similar state‐of‐the‐art studies, the proposed method showed a higher accuracy (99.02%) for the six emotional states mentioned above. These findings may promote the development of social robots with non‐verbal emotional communication capabilities.

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Section: Related Workmentioning

confidence: 99%

“…Chang et al. [24] used intelligent inertial sensors to identify emotions during badminton movement, and sensors can respond to emotional changes, such as happiness, nausea, and sadness. However, with the increase of exercise time, the degree of physical fatigue affects the recognition effect of emotion.…”

Section: Related Workmentioning

confidence: 99%

Attention‐based sensor fusion for emotion recognition from human motion by combining convolutional neural network and weighted kernel support vector machine and using inertial measurement unit signals

Zhao

Guo

Sun

et al. 2023

IET Signal Processing

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“…Research about factors influencing badminton athletes' performance at the international level underscores the sport's complexity, encompassing interrelated elements. Notably, studies by [1,2] emphasize physical factors such as strength, flexibility, and speed in chasing the shuttlecock. The technical and tactical aspects highlighted by [3,4], including mastery of basic techniques and strategic prowess, also prove crucial for success in competitive badminton.…”

Section: Introductionmentioning

confidence: 99%

Analysis of key factors affecting the achievement of badminton athletes at the international level: A systematic review

Ihsan,

Nasrulloh,

Nugroho

2024

Fiz Pol

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The achievement of badminton athletes at the international level is a complex result of various factors involving physical, technical, tactical, and psychological aspects, as well as environmental support. This study used a systematic review approach to understand the key factors that contribute to badminton athlete achievement. The purpose of this study was to detail and analyze the existing literature to identify the key factors that are significant in improving the performance of badminton athletes at the international level. The selection of articles was done through a thorough search in several significant databases, with strict inclusion criteria to ensure the relevance and quality of the research. Two independent researchers conducted the article selection process to minimize bias. Once the articles were selected, data analysis was undertaken to describe and categorize the key factors identified. The results of this systematic review revealed that physical factors such as general physical condition, strength, explosive power, flexibility, and speed significantly impact badminton athletes' performance. In addition, technical and tactical aspects, such as basic techniques, game tactics, and doubles, also play a crucial role. Psychological characteristics, including motivation, stress management, concentration, and social support, are also factors that cannot be ignored in achieving optimal performance. By detailing these key factors, this study provides an in-depth insight into the complexity of the determinants of badminton athletes' performance at the international level. The implications of these findings provide a basis for coaches and researchers to develop more effective and focused training strategies and stimulate further research to understand the interactions between these factors deeply. Thus, the results of this systematic review can make an essential contribution to the development of the world of training and coaching badminton athletes.

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“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

mentioning

confidence: 99%

mentioning

confidence: 99%

Retracted: Analyzing the Effect of Badminton on Physical Health and Emotion Recognition on the account of Smart Sensors

2023

Applied Bionics and Biomechanics

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Analyzing the Effect of Badminton on Physical Health and Emotion Recognition on the account of Smart Sensors

Cited by 3 publications

References 21 publications

Attention‐based sensor fusion for emotion recognition from human motion by combining convolutional neural network and weighted kernel support vector machine and using inertial measurement unit signals

Attention‐based sensor fusion for emotion recognition from human motion by combining convolutional neural network and weighted kernel support vector machine and using inertial measurement unit signals

Analysis of key factors affecting the achievement of badminton athletes at the international level: A systematic review

Retracted: Analyzing the Effect of Badminton on Physical Health and Emotion Recognition on the account of Smart Sensors

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