@inproceedings{74ba17ec56d1436598e149d69091e25e,
title = "Gait Diagnosis of Parkinson's Disease based on Piezoresistive and Piezoelectric Hybrid Sensors",
abstract = "For the purpose of daily monitoring and quantitative analysis of gait abnormalities for Parkinson's patients, a wearable gait data acquisition system is developed in this paper. The system can collect plantar pressure and deformation by a multi-channel flexible piezoresistive sensor module and a multi-channel flexible piezoelectric sensor module. Through the design of the signal conditioning circuit, the system has the function of real-time acquisition and wireless transmission for piezoresistive and piezoelectric signals. Walking experiments are carried out with the designed system, and the gait data of Parkinson's patients and healthy controls are collected and analyzed. Results show that the proposed gait system can be used for exact diagnosis of Parkinson's disease.",
keywords = "Parkinson's disease, gait analysis, piezoelectric sensor, piezoresistive sensor, wearable device",
author = "Junxiao Xie and Huan Zhao and Junyi Cao",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 10th E-Health and Bioengineering Conference, EHB 2022 ; Conference date: 17-11-2022 Through 18-11-2022",
year = "2022",
doi = "10.1109/EHB55594.2022.9991561",
language = "英语",
series = "2022 10th E-Health and Bioengineering Conference, EHB 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 10th E-Health and Bioengineering Conference, EHB 2022",
}