Name
Abstract | ||
|---|---|---|
Stroke is a kind of cerebral vascular disease with high death rate and high disability rate, most stroke patients lose a lot of physiological function. For example, motor function, language function, etc. Two data acquisition methods of lower limb rehabilitation system for patients with stroke were introduced in this paper that is EEG signal extraction based on BCI and lower limb muscle electrical stimulation system based on EMG model. Through the wavelet packet transform (WPT) to analyze the EEG signal and collect the effective EEG signal. The wavelet transform is used to analyze the time and frequency domain, which provides a good feature vector for the dynamic analysis and motion recognition of EMG signals. |
Year | Venue | Field |
|---|---|---|
2017 | ICIRA | Frequency domain,Feature vector,Brain–computer interface,Stroke,Feature extraction,Speech recognition,Control engineering,Engineering,Wavelet packet decomposition,Electroencephalography,Wavelet transform |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
7 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heng Tang | 1 | 30 | 1.49 |
| Gongfa Li | 2 | 239 | 43.45 |
| Ying Sun | 3 | 291 | 40.03 |
| Guozhang Jiang | 4 | 172 | 27.25 |
| Jianyi Kong | 5 | 80 | 13.32 |
| Zhaojie Ju | 6 | 284 | 48.23 |
| Du Jiang | 7 | 97 | 14.40 |