Real-time ECG signal acquisition and monitoring for sports competition process oriented to the Internet of Things

Lv, Wu; Guo, Jiujun

doi:10.1016/j.measurement.2020.108359

Cited by 11 publications

(5 citation statements)

References 26 publications

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“…According to the research paper of Wu Lv and Jiujun Guo (2021), the synthesis of the technological support with regard to the Sensorization of Things involves intelligent sensor technology such as working on the body i.e., touch, movement; signals i.e., heat, electricity; measurement i.e., motion, temperature, heat, vibration, noise, moisture, density, volume, weight, pressure, acceleration, direction, speed, distance; and function i.e., wearables, smart home, smart city (Lv & Guo, 2021). Mariana Jacob Rodrigues et al (2020) stated that intelligent sensor technology includes the following: working on the body i.e., eye, sound, movement, brain, signals i.e., thermal, electricity; and measurement i.e., motion, light, vibration, noise, air, moisture, density, pressure, acceleration, speed, distance (Rodrigues et al, 2020).…”

Section: The Results Of the Synthesis Of Technological Support For The Sensorization Of Thingsmentioning

confidence: 99%

“…According to Wu Lv and Jiujun Guo (2021) the Sensorization of Things ecosystem is an intelligent sensor technology ecosystem made up of the following: sensor devices i.e., fixed, mobile, wearable, sensor node, smart intelligent; objects i.e., human, material; technology i.e., internet, IoT, sensor, real time, software; networks and connections i.e., wireless, communication, analog/digital; data and attributes i.e., medical health information, physiology, ECG, respiration, blood pressure, temperature, movement, light; and functions i.e., collect data, inspection, location, receive and send data, processing, compile and analyze data (Lv & Guo, 2021). Mariana Jacob Rodrigues et al (2020) describes an intelligent sensor technology ecosystem as follows: sensor device i.e., fixed, wearable, mobile, sensor node, smart intelligent; object i.e., organizer, institute, material; technology i.e., internet, IoT, sensor, real time, software; networks and connections i.e., wireless, RFID, communication, analog/digital; data and attributes i.e., medical health information, ECG, respiration, blood pressure, temperature, movement, light; and functions i.e.,remote tracking, collect data, inspection, location, control, decisions, receive and send data, processing, compile and analyze data (Rodrigues et al, 2020).…”

Section: The Results Of the Synthesis Of The Sensorization Of Things Ecosystemmentioning

confidence: 99%

“…One function was a real-time physiological signal from a body such as ECG, respiration, blood pressure and body temperature. The second function was to transmit signal data wirelessly to a nearby or remote terminal (Lv & Guo, 2021). Mariana Jacob Rodrigues et al (2020) stated that the intelligent sensor technology refers to a smart sensor system that combined with an Internet of Things technology to help improve the quality of life.…”

Section: Sensorization Of Things (Sot)mentioning

confidence: 99%

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Sensorization of Things Intelligent Technology for Sport Science to Develop an Athlete’s Physical Potential

Sattaburuth¹,

Wannapiroon²

2021

HES

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Sports can build both strength and be fun at the same time. When it comes to a professional athlete's victory, the winner will enhance his reputation and can earn a great deal of money. The problem that athletes frequently encounter is traumas, which can happen in games or during training. Today, the technology is very advanced and modernized. Innovations and perceptual devices can be created to monitor, measure, analyze and evaluate data from the information received from the introduction of an intelligent system of evaluation and prediction in terms of safety and risk prevention with regard to athletes, by collecting heart rate data, blood oxygen measurement, air density around the athletes’ body, body temperature and a temperature in the sports training room. This is the point of view and vision of a sports industry leaders, who perceive the opportunity and advantage associated with the competition and training of both amateur and professional athletes, to develop the athlete’s physical potential to achieve international excellence. The study of intelligent sensor technology that is used to support devices that work on the guidelines of Internet of Things (IoT) leading to the development of real time data collecting applications. These are used to process or interpret physiological knowledge for an analysis of results and for the prediction of incoming results. It was found that using intelligent sensing technology which are two main groups of detection and measurement: First, human body function sensing and second, measurement to environment around the body or object, and explained to detail in this article.

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Section: The Results Of the Synthesis Of Technological Support For The Sensorization Of Thingsmentioning

confidence: 99%

Section: The Results Of the Synthesis Of The Sensorization Of Things Ecosystemmentioning

confidence: 99%

Section: Sensorization Of Things (Sot)mentioning

confidence: 99%

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Sensorization of Things Intelligent Technology for Sport Science to Develop an Athlete’s Physical Potential

Sattaburuth¹,

Wannapiroon²

2021

HES

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“…The motion recognition algorithm is adopted to identify the motion parameters of the whole motion process, so as to effectively guide the students' motion process [20].…”

Section: 2%mentioning

confidence: 99%

Optimization of a Sports Activity Development Model Using Artificial Intelligence under New Curriculum Reform

Liu

Wilczyńska

Lipowski

et al. 2021

IJERPH

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The recent curriculum reform in China puts forward higher requirements for the development of physical education. In order to further improve students’ physical quality and motor skills, the traditional model was improved to address the lack of accuracy in motion recognition and detection of physical condition so as to assist teachers to improve students’ physical quality. First, the physical education teaching activities required by the new curriculum reform were studied with regard to the actual needs of China’s current social, political, and economic development; next, the application of artificial intelligence technology to physical education teaching activities was proposed; and finally, deep learning technology was studied and a human movement recognition model based on a long short-term memory (LSTM) neural network was established to identify the movement state of students in physical education teaching activities. The designed model includes three components: data acquisition, data calculation, and data visualization. The functions of each layer were introduced; then, the intelligent wearable system was adopted to detect the status of students and a feedback system was established to assist teaching; and finally, the dataset was constructed to train and test the designed model. The experimental results demonstrate that the recognition accuracy and loss value of the training model meet the practical requirements; in the algorithm test, the motion recognition accuracy of the designed model for different subjects was greater than 97.5%. Compared with the traditional human motion recognition algorithm, the designed model had a better recognition effect. Hence, the designed model can meet the actual needs of physical education. This exploration provides a new perspective for promoting the intelligent development of physical education.

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“…The ECG electrodes can be categorized as wet and dry electrodes. (Ag/AgCl) was used in [33], [34] as a wet electrode. Therefore, dry electrodes have been found with merits that overcome the limitation of the wet electrodes like no skin irritation and kin preparation and long-time monitoring continuously.…”

Section: Data Acquisitionmentioning

confidence: 99%

Smart Healthcare for ECG Telemonitoring System

Saeed¹,

Ameen

2021

JSCDM

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Cardiovascular disorders are one of the major causes of sad death among older and middle-aged people. Over the past two decades, health monitoring services have evolved quickly and had the ability to change the way health care is currently provided. However, the most challenging aspect of the mobile and wearable sensor-based human activity recognition pipeline is the extraction of the related features. Feature extraction decreases both computational complexity and time. Deep learning techniques are used for automatic feature learning in a variety of fields, including health, image classification, and, most recently, for the extraction and classification of complex and straightforward human activity recognition in smart health care. This paper reviews the recent state of the art in electrocardiogram (ECG) smart health monitoring systems based on the Internet of things with the machine and deep learning techniques. Moreover, the paper provided possible research and challenges that can help researchers advance state of art in future work.

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Real-time ECG signal acquisition and monitoring for sports competition process oriented to the Internet of Things

Cited by 11 publications

References 26 publications

Sensorization of Things Intelligent Technology for Sport Science to Develop an Athlete’s Physical Potential

Sensorization of Things Intelligent Technology for Sport Science to Develop an Athlete’s Physical Potential

Optimization of a Sports Activity Development Model Using Artificial Intelligence under New Curriculum Reform

Smart Healthcare for ECG Telemonitoring System

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