scholarly journals Human motion state recognition based on MEMS sensors and Zigbee network

2021 ◽  
Author(s):  
Qing Liu
Keyword(s):  
Human Motion ◽  
Mems Sensors ◽  
State Recognition ◽  
Motion State ◽  
Zigbee Network

scholarly journals Human Motion State Recognition Based on Flexible, Wearable Capacitive Pressure Sensors

Micromachines ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1219
Author(s):  
Qingyang Yu ◽  
Peng Zhang ◽  
Yucheng Chen
Keyword(s):  
Flexible Substrate ◽  
Recognition Rate ◽  
Pressure Sensors ◽  
Recognition System ◽  
Human Motion ◽  
Body Motion ◽  
Capacitive Pressure Sensor ◽  
Wearable Sensor ◽  
State Recognition ◽  
Motion State

Human motion state recognition technology based on flexible, wearable sensor devices has been widely applied in the fields of human–computer interaction and health monitoring. In this study, a new type of flexible capacitive pressure sensor is designed and applied to the recognition of human motion state. The electrode layers use multi-walled carbon nanotubes (MWCNTs) as conductive materials, and polydimethylsiloxane (PDMS) with microstructures is embedded in the surface as a flexible substrate. A composite film of barium titanate (BaTiO3) with a high dielectric constant and low dielectric loss and PDMS is used as the intermediate dielectric layer. The sensor has the advantages of high sensitivity (2.39 kPa−1), wide pressure range (0–120 kPa), low pressure resolution (6.8 Pa), fast response time (16 ms), fast recovery time (8 ms), lower hysteresis, and stability. The human body motion state recognition system is designed based on a multi-layer back propagation neural network, which can collect, process, and recognize the sensor signals of different motion states (sitting, standing, walking, and running). The results indicate that the overall recognition rate of the system for the human motion state reaches 94%. This proves the feasibility of the human motion state recognition system based on the flexible wearable sensor. Furthermore, the system has high application potential in the field of wearable motion detection.

scholarly journals User-Independent Motion State Recognition Using Smartphone Sensors

Sensors ◽  
2015 ◽  
Vol 15 (12) ◽  
pp. 30636-30652 ◽  
Author(s):  
Fuqiang Gu ◽  
Allison Kealy ◽  
Kourosh Khoshelham ◽  
Jianga Shang
Keyword(s):  
State Recognition ◽  
Motion State ◽  
Smartphone Sensors ◽  
Independent Motion

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

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Bu Chang
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Wireless Sensor ◽  
Competitive Sports ◽  
Heart Rate Acceleration ◽  
State Recognition ◽  
Acceleration Signal ◽  
Motion State ◽  
Rate Acceleration ◽  
Athletes Heart

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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