scholarly journals Design and Realization of Heart Rate Signal Detection System Based on Android Mobile Phone

Author(s):  
Yuxin Zhu ◽  
Jing Han
Author(s):  
Ili Najaa Aimi Mohd Nordin ◽  
Najla Aiman Nazari ◽  
Muhammad Rusydi Muhammad Razif ◽  
Nurulaqilla Khamis ◽  
Noraishikin Zulkarnain ◽  
...  

<p>This paper presents study on optimizing RF signal detection and alert system for restricted area. Nowadays, mobile phone utilization is very common among youngsters. Despite of being very useful for educational purpose, it turns into a noteworthy issue while being smuggled into restricted area, such as examination hall and used as a cheating tool. To overcome this problem, an advancement on the detection and alert system of active mobile phone was proposed by implementing RF signal detection system optimization using multi-band dipole antenna and alert system utilizing LED and camera. The system demonstrated higher sensitivity to 3G signal followed by GSM and Wi-Fi with the decrease in voltage value across the LED when distinguishing 3G, GSM and Wi-Fi signal with the estimation of 2.316 V, 1.162 V and 1.054 V respectively. The alert system was improved by activating LED and camera instead of buzzer in displaying the region of the active mobile phone. The camera was able to effectively capture the conceivable cheating area when active mobile phone is present. The images of the potential cheating region can be recovered from the computer. This framework can assist the invigilators with being cautioned to the potential regions of cheating using mobile phone.</p>


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ming Dai ◽  
Kai Zhan ◽  
Rongchao Peng ◽  
Hui Luo ◽  
Jinfeng Xu ◽  
...  

2021 ◽  
pp. 1-10
Author(s):  
Guochun Liu ◽  
Jian Zheng ◽  
Lin Jiang ◽  
Karthik Chandran ◽  
Beenu Mago

The signal analysis helps us derive useful knowledge from biological processes to analyze, describe, and understand their origin mechanisms. However, biomedical signals are not immune and have time-consuming statistics. The major challenges of signal analysis of sportsperson are reliability and accuracy. Sports psychology uses psychological skills to discuss the optimum success and well-being of sports athletes, the developmental and social dimensions of the sport and sports facilities, and structural problems. The signal detection tool is used to detect the best combination of long-term practice predictors for active, sedentary adults’ signal. This paper proposed the wearable assisted signal detection method (WASDM) to find the sportspersons’ behavior signal analysis. This method performs an IoT based heart rate monitoring using a wearable device named intelligent bracelet mounted on the sportsperson to track the variations in his/her human heart rate. The wearable signal detector method analysis the heart rate abnormality and predicts health status, followed by an alarm to the physician and the respective personnel while performing activity session. In this research, various machine learning algorithms have been tried to perform signal analysis and prediction and compared their results to suggest the best in this application scenario. Finally, the experimental analysis shows better outcomes for the sportspersons’ psychological behavior signal analysis than the conventional methods.


1986 ◽  
Vol 79 (2) ◽  
pp. 586-586
Author(s):  
Otis G. Zehl ◽  
Michael G. Price ◽  
Edward H. David ◽  
Jerome C. Kremen

2021 ◽  
Vol 16 (2) ◽  
pp. 188-195
Author(s):  
Keyuan Liu ◽  
Haibin Li ◽  
Ya Wang

The weak direct current (DC) signals detected and converted by the photodetector are output to the mobile phone by voltage/frequency switching, and the signals are processed by the mobile phone APP and audio conversion module. The photodetector is equipped with the automatic switching function to design an optical power meter and detect weak signals. Meanwhile, the optical cable identification system is analyzed and combined with the optical power meter to generate an optical fiber sensing network to improve the weak alternating current (AC) signal detection. This network needs data fusion in sensor nodes’ data collection. The cluster routing protocol is introduced and combined with the back propagation neural network (BPNN) to propose a method suitable for this photoelectric transmission and improve the information fusion and accuracy. In the experiment, the optical power meter is output in gears first, and the output waveforms are normal. The photodiode’s optical power is adjusted to obtain different frequencies on the oscilloscope. In the proposed optical fiber sensing network, weak AC signals are amplified significantly, and different optical fiber lines can be distinguished in the optical cables. The proposed information collection method can reduce network communication and node energy consumption.


2015 ◽  
Vol 9 (4) ◽  
Author(s):  
Liting Yi ◽  
Jingjing Li ◽  
Cangran Guo ◽  
Lei Li ◽  
Jing Liu

Pervasive detection of blood glucose is rather critical for the real-time disease diagnosis which would provide valuable guidance for treatment planning. Here, we established a health care platform for this purpose through incorporating the glucose detection with liquid metal printed sensor and the smart phone monitoring system together. The liquid metal ink composed of bismuth indium stannic (BIS) alloy was identified as an appropriate sensor material to be quickly written or printed on polyvinyl chloride (PVC) substrate at around 59 °C to form desired electrodes. It thus eliminated the complicated procedures as usually required in conventional sensor fabrication strategies. The alloy electrodes were characterized via cyclic voltammetry to demonstrate their practical functionality. Further, unlike using the commonly adopted glucometer, a smart phone was developed as the data acquisition and display center to help improve the portability and ubiquitous virtue of the detection system. Glucose solution in different concentrations was assayed via this platform. It was shown that there is a good linear relationship between the concentration and the integral value of the curve recorded by the mobile phone, which confirms the feasibility of the present method. This quantitative point-of-care system has pervasive feature and is expected to be very useful for future low-cost electrochemical detection.


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