TY - GEN
T1 - Design of wearable and portable physiological parameter monitoring system for attentiveness evaluation
AU - Cao, Tianao
AU - Sun, Jinwei
AU - Guo, Huanhuan
AU - Tang, Jiaze
AU - Wang, Qisong
AU - Liu, Dan
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/6/28
Y1 - 2021/6/28
N2 - With the rapid development of information technology, the "human-machine collaboration"smart education model is emerging increasingly. Aiming at addressing the problems of poor portability of the devices, single sort of physiological signals, and excessively subjective evaluation of attentiveness in current monitoring systems, this paper designed an attentiveness evaluation system based on multiple physiological information. First of all, in view of the large volume of traditional acquisition devices, we designed the miniaturized, wearable multi-physiological signal acquisition node. Based on a single-channel EEG signal analog acquisition front-end, 9-axis acceleration acquisition chip and blood oxygen (SpO2) acquisition module, we acquired the EEG, posture and SpO2 signals synchronously. Secondly, in the light of the bandwidth and power consumption of information transmission in the wireless body area network, we designed a data transmission networking based on wireless radio frequency Wi-Fi, achieving high-speed signal communication with high accuracy. The attentiveness induction experiment was designed, and an objective evaluation index of attentiveness based on reaction time and accuracy rate for regression analysis and fitting was put forward. After preprocessing the raw data, a variety of features were extracted, and the performance of the attentiveness evaluation was verified. Results show that the accuracy rate of the attentiveness is up to 77.1%, which realizes the effective evaluation of attentiveness.
AB - With the rapid development of information technology, the "human-machine collaboration"smart education model is emerging increasingly. Aiming at addressing the problems of poor portability of the devices, single sort of physiological signals, and excessively subjective evaluation of attentiveness in current monitoring systems, this paper designed an attentiveness evaluation system based on multiple physiological information. First of all, in view of the large volume of traditional acquisition devices, we designed the miniaturized, wearable multi-physiological signal acquisition node. Based on a single-channel EEG signal analog acquisition front-end, 9-axis acceleration acquisition chip and blood oxygen (SpO2) acquisition module, we acquired the EEG, posture and SpO2 signals synchronously. Secondly, in the light of the bandwidth and power consumption of information transmission in the wireless body area network, we designed a data transmission networking based on wireless radio frequency Wi-Fi, achieving high-speed signal communication with high accuracy. The attentiveness induction experiment was designed, and an objective evaluation index of attentiveness based on reaction time and accuracy rate for regression analysis and fitting was put forward. After preprocessing the raw data, a variety of features were extracted, and the performance of the attentiveness evaluation was verified. Results show that the accuracy rate of the attentiveness is up to 77.1%, which realizes the effective evaluation of attentiveness.
KW - attemtiveness
KW - biosensing technologies
KW - multi-physiological parameters
KW - wearable device
UR - https://www.scopus.com/pages/publications/85114554115
U2 - 10.1109/ICAICA52286.2021.9498201
DO - 10.1109/ICAICA52286.2021.9498201
M3 - 会议稿件
AN - SCOPUS:85114554115
T3 - 2021 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2021
SP - 1207
EP - 1213
BT - 2021 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2021
Y2 - 28 June 2021 through 30 June 2021
ER -