Отрывок: The raw sEMG signal was band pass filtered from 2oHz to 500Hz. The purpose of the lower frequency limit was to remove DC offset and motion artifacts. The high frequency limit prevents the aliasing. This was achieved by using a zerolag sixth order recursive Butterworth filter. The sEMG signal recorded from VL muscle and recorded knee angle for subject 1 are plotted in Fig 2. Fig. 2. sEMG signal recorded from Vastus lateralis and measured Knee anglewhile perform...
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dc.contributor.author | Dhindsa, Inderjeet Singh | - |
dc.contributor.author | Agarwal, Ravinder | - |
dc.contributor.author | Ryait, Hardeep Singh | - |
dc.date.accessioned | 2016-12-08 10:50:59 | - |
dc.date.available | 2016-12-08 10:50:59 | - |
dc.date.issued | 2016 | - |
dc.identifier | Dspace\SGAU\20161208\60617 | ru |
dc.identifier.citation | Материалы Международной конференции и молодёжной школы «Информационные технологии и нанотехнологии», с. 56-61 | ru |
dc.identifier.isbn | 978-5-7883-1078-7 | - |
dc.identifier.uri | http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Joint-angle-prediction-from-EMG-signals-for-lower-limb-exoskeleton-60617 | - |
dc.description.abstract | This paper presents an algorithm for estimation of the intended knee joint angle from sEMG signals acquired from four muscles of upper limb. The algorithm was evaluated with experiments showing the calculated intended motion while performing a simple daily life activity of sitting in a squat position and standing from a squat position. The proposed algorithm uses mean absolute value (MAV) and root mean square (RMS) for feature extraction and a multi-layer back propagation neural network (BPN) for predicting the knee angle. The algorithm and the experimental results are both presented. The predicted knee angle can be used to control a lower limb exoskeleton. | ru |
dc.language.iso | en | ru |
dc.publisher | Издательство СГАУ | ru |
dc.subject | back propagation | ru |
dc.subject | exoskeleton | ru |
dc.subject | feature extraction | ru |
dc.subject | sEMG | ru |
dc.subject | neural network | ru |
dc.title | Joint angle prediction from EMG signals for lower limb exoskeleton | ru |
dc.type | Article | ru |
dc.textpart | The raw sEMG signal was band pass filtered from 2oHz to 500Hz. The purpose of the lower frequency limit was to remove DC offset and motion artifacts. The high frequency limit prevents the aliasing. This was achieved by using a zerolag sixth order recursive Butterworth filter. The sEMG signal recorded from VL muscle and recorded knee angle for subject 1 are plotted in Fig 2. Fig. 2. sEMG signal recorded from Vastus lateralis and measured Knee anglewhile perform... | - |
Располагается в коллекциях: | Информационные технологии и нанотехнологии |
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56-61.pdf | Основная статья | 488.97 kB | Adobe PDF | Просмотреть/Открыть |
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