scholarly journals Aerobics Exercise Posture Tracking and Recognition System Based on Wireless Smart Sensors

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wenting Zhou
Keyword(s):  
Recognition System ◽  
Smart Sensors ◽  
Average Error ◽  
Dance Music ◽  
Research Issues ◽  
Sensor Model ◽  
Wireless Smart Sensors ◽  
Software And Hardware ◽  
Tracking And Recognition ◽  
Posture Tracking

Wireless sensors are a new, high-end, and popular exploration technology. The positioning and tracking of the human body are two important research issues in sensors. Aerobics is a widely popular sports item that is well-loved by the general public and integrates gymnastics, dance, music, fitness, and entertainment. The application of smart sensors helps to improve the coordination and flexibility of movements. In order to deeply study whether wireless smart sensors can play a role in tracking and recognizing aerobics exercise postures, this article uses sensor design methods, motion analysis, and software and hardware equipment architecture methods to collect samples, analyze smart sensors, and streamline algorithms. And it creates a sensor model and system for posture tracking and recognition. When testing the best position for the placement of the sensor, first fix the sensor at a distance of 2.5 cm from the wrist section and at the middle of the lower arm, keep the upper arm still, and do the stretching and contraction movements of the lower arm. Repeat the exercise 5 times and measure the wrist. The movement curve of the juncture, the result shows that the measured juncture curve at a distance of 2.5 cm is basically the same as the actual winding curve, and the fixed position in the middle deviates more from the normal curve point, and its average error is within 0.9 cm, which is correct. To test the effectiveness of the algorithm again, a total of 8 volunteers’ data were collected during the experiment, and the duration was more than 25 seconds, and each normal posture tried to maintain stability and lasted for about 6 seconds. The statistical accuracy rate is 90.6%. It shows that the algorithm or the system designed in this paper has extremely high accuracy. It is basically realized that from the theory of wireless sensor network, a system model that can be used for posture tracking and recognition of aerobics is designed.

scholarly journals IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW

2017 ◽  
Vol 79 (7) ◽  
Author(s):  
Azlan Muharam ◽  
Afandi Ahmad
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Medical Image ◽  
Rapid Development ◽  
Three Dimensional ◽  
Medical Image Processing ◽  
Subjective Test ◽  
Medical Image Compression ◽  
Research Issues ◽  
Software And Hardware

The rapid development of medical imaging and the invention of various medicines have benefited mankind and the whole community. Medical image processing is a niche area concerned with the operations and processes of generating images of the human body for clinical purposes.  Potential areas such as image acquisition, image enhancement, image compression and storage, and image based visualization also include in medical image processing analysis. Unfortunately, medical image compression dealing with three-dimensional (3-D) modalities still in the pre-matured stage. Along with that, very limited researchers take a challenge to apply hardware on their implementation. Referring to the previous work reviewed, most of the compression method used lossless rather than lossy. For implementation using software, MATLAB and Verilog are the famous candidates among researchers. In term of analysis, most of the previous works conducted objective test compared with subjective test. This paper thoroughly reviews the recent advances in medical image compression mainly in terms of types of compression, software and hardware implementations and performance evaluation. Furthermore, challenges and open research issues are discussed in order to provide perspectives for future potential research. In conclusion, the overall picture of the image processing landscape, where several researchers more focused on software implementations and various combinations of software and hardware implementation.  

scholarly journals A Real-time Face Tracking and Recognition System Based on SeetaFace

2020 ◽  
Vol 1673 ◽  
pp. 012043
Author(s):  
Dilizhati Yilihamu ◽  
Palidan Tuerxun ◽  
Abdusalam Dawut ◽  
Askar Hamdulla
Keyword(s):  
Real Time ◽  
Recognition System ◽  
Face Tracking ◽  
Tracking And Recognition

scholarly journals Sudden Event Monitoring of Civil Infrastructure Using Demand-Based Wireless Smart Sensors

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4480 ◽  
Author(s):  
Yuguang Fu ◽  
Tu Hoang ◽  
Kirill Mechitov ◽  
Jong Kim ◽  
Dichuan Zhang ◽  
...  
Keyword(s):  
Low Power ◽  
Field Experiments ◽  
Effective Means ◽  
Smart Sensors ◽  
Monitoring Systems ◽  
Sleep Mode ◽  
High Fidelity ◽  
Civil Infrastructure ◽  
Event Monitoring ◽  
Wireless Smart Sensors

Wireless smart sensors (WSS) have been proposed as an effective means to reduce the high cost of wired structural health monitoring systems. However, many damage scenarios for civil infrastructure involve sudden events, such as strong earthquakes, which can result in damage or even failure in a matter of seconds. Wireless monitoring systems typically employ duty cycling to reduce power consumption; hence, they will miss such events if they are in power-saving sleep mode when the events occur. This paper develops a demand-based WSS to meet the requirements of sudden event monitoring with minimal power budget and low response latency, without sacrificing high-fidelity measurements or risking a loss of critical information. In the proposed WSS, a programmable event-based switch is implemented utilizing a low-power trigger accelerometer; the switch is integrated in a high-fidelity sensor platform. Particularly, the approach can rapidly turn on the WSS upon the occurrence of a sudden event and seamlessly transition from low-power acceleration measurement to high-fidelity data acquisition. The capabilities of the proposed WSS are validated through laboratory and field experiments. The results show that the proposed approach is able to capture the occurrence of sudden events and provide high-fidelity data for structural condition assessment in an efficient manner.

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