Blind estimation of number of motion multi-human targets in wireless pyroelectric infrared sensor networks

Zhao, Ning; Li, Fangmin; Liu, XueDong

doi:10.1016/j.infrared.2013.08.015

Cited by 7 publications

(2 citation statements)

References 11 publications

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“…In professional competitive sports, real-time monitoring of human heart rate and corresponding sports status can not only fully obtain the energy consumed by athletes in the process of sports but also analyze their corresponding sports quality level. Systematic comprehensive analysis of the above two data can further improve athletes' sports level, improve defects in the process of sports, and improve sports quality [1][2][3]. The traditional heart rate detection of athletes is mainly based on hardware equipment such as heart rate belt, but the traditional hardware heart rate belt is inconvenient to wear, and its heart rate monitoring of athletes during exercise is not accurate [4].…”

Section: Introductionmentioning

confidence: 99%

Application of Heart Rate Acceleration Motion Wireless Sensor Fusion in Individual Special Competitive Sports

Chang

2021

Journal of Sensors

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Heart rate monitoring is becoming more and more important in the development of modern health industry. At present, wireless sensor network equipment is mainly used to realize the real-time or periodic monitoring of human heart rate, so as to realize the health management of specific people. At the same time, the monitoring and analysis technology of heart rate is also widely used in special competitive sports. Through the real-time monitoring and analysis of athletes’ heart rate, we can feedback and analyze their corresponding competitive state in real time, so as to monitor the sudden state of athletes, and also provide a basis for the improvement of athletes’ later sports level. Based on this, this paper will use a single-chip microcomputer as the central data processing unit of the monitoring system at the hardware level, and inertial sensor and heart rate sensor at the sensor level. The system will design data acquisition module, motion positioning module, low-power module, athlete heart rate acquisition module, and motion state recognition module. Aiming at the low accuracy of traditional heart rate acceleration motion wireless sensor in competitive sports athletes’ heart rate recognition and motion state recognition, this paper innovatively proposes an athlete heart rate recognition algorithm based on acceleration signal, which extracts the frequency-domain characteristics of motion signal. The time-domain and time-frequency characteristics of athletes’ acceleration signal are used to realize the recognition of athletes’ sports state, and the power spectrum cancellation technology is used to realize the accurate detection of athletes’ heart rate. In order to verify the advantages of the hardware system and algorithm in this paper, three sports with quiet, dynamic, and random dynamic characteristics are selected for experimental verification. The experimental results show that the software algorithm proposed in this paper has obvious accuracy advantages in quiet and dynamic competitive sports compared with the traditional algorithm.

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Section: Introductionmentioning

confidence: 99%

Application of Heart Rate Acceleration Motion Wireless Sensor Fusion in Individual Special Competitive Sports

Chang

2021

Journal of Sensors

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“…Hao et al introduced multiple human tracking and identification with wireless distributed PIR sensor systems [ 16 ]. Zhao et al presented a novel method to select the maximum likelihood function of Bayesian network models as the independent criterion to blindly estimate the number of moving multiple human targets [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors

Yan

Lou

et al. 2018

Sensors

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Analysis of the multiple factors affecting human identification ability based on pyroelectric infrared technology is a complex problem. First, we examine various sensed pyroelectric waveforms of the human body thermal infrared signal and reveal a mechanism for affecting human identification. Then, we find that the mechanism is decided by the distance, human target, pyroelectric infrared (PIR) sensor, the body type, human moving velocity, signal modulation mask, and Fresnel lens. The mapping relationship between the sensed waveform and multiple influencing factors is established, and a group of mathematical models are deduced which fuse the macro factors and micro factors. Finally, the experimental results show the macro-factors indirectly affect the recognition ability of human based on the pyroelectric technology. At the same time, the correctness and effectiveness of the mathematical models is also verified, which make it easier to obtain more pyroelectric infrared information about the human body for discriminating human targets.

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Multiple human location in a distributed binary pyroelectric infrared sensor network

Yang

Wei

Zhang

2017

Infrared Physics & Technology

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Blind estimation of number of motion multi-human targets in wireless pyroelectric infrared sensor networks

Cited by 7 publications

References 11 publications

Application of Heart Rate Acceleration Motion Wireless Sensor Fusion in Individual Special Competitive Sports

Application of Heart Rate Acceleration Motion Wireless Sensor Fusion in Individual Special Competitive Sports

Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors

Multiple human location in a distributed binary pyroelectric infrared sensor network

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