| Judul | Electromyography Signal Acquisition and Processing for Movement Analysis / Edited by: Francesco Di Nardo; Valentina Agostini; Silvia Conforto |
| Penerbitan | Bassel : MDPI, 2023 |
| Deskripsi Fisik | 204p. :ill. |
| ISBN | 978-3-0365-7205-5 |
| Subjek | ELECTRODIAGNOSIS |
| Catatan | This reprint focuses on recent advances in the processing of surface electromyography (EMG) signals acquired during human movement, as well as on innovative approaches to sense muscle activity. A wide range of methods is examined, including machine learning techniques to detect the onset/offset timing of muscle activity and approaches to evaluate muscle fatigue and analyze muscle synergies and co-contractions. Applications of these techniques are explored in different medical scenarios, e.g., for the benefit of patients suffering from low back pain, stroke survivors, and patients requiring polysomnography. |
| Bentuk Karya | Tidak ada kode yang sesuai |
| Target Pembaca | Tidak ada kode yang sesuai |
| Lokasi Akses Online |
https://mdpi-res.com/bookfiles/book/7130/Electromyography_Signal_Acquisition_and_Processing_for_Movement_Analysis.pdf?v=1770862092 |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 213026192 | 616.075 47 Ele | Baca Online | Perpustakaan Pusat - E-Lib KKB Ebook |
Tersedia |
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| 001 | INLIS000000000166823 | ||
| 005 | 20260213090647 | ||
| 007 | ta | ||
| 008 | 260213################|##########|#|## | ||
| 020 | # | # | $a 978-3-0365-7205-5 |
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| 082 | # | # | $a 616.075 47 |
| 084 | # | # | $a 616.075 47 Ele |
| 245 | # | # | $a Electromyography Signal Acquisition and Processing for Movement Analysis /$c Edited by: Francesco Di Nardo; Valentina Agostini; Silvia Conforto |
| 260 | # | # | $a Bassel :$b MDPI,$c 2023 |
| 300 | # | # | $a 204p. : $b ill. |
| 500 | # | # | $a This reprint focuses on recent advances in the processing of surface electromyography (EMG) signals acquired during human movement, as well as on innovative approaches to sense muscle activity. A wide range of methods is examined, including machine learning techniques to detect the onset/offset timing of muscle activity and approaches to evaluate muscle fatigue and analyze muscle synergies and co-contractions. Applications of these techniques are explored in different medical scenarios, e.g., for the benefit of patients suffering from low back pain, stroke survivors, and patients requiring polysomnography. |
| 650 | # | # | $a ELECTRODIAGNOSIS |
| 856 | # | # | $a https://mdpi-res.com/bookfiles/book/7130/Electromyography_Signal_Acquisition_and_Processing_for_Movement_Analysis.pdf?v=1770862092 |
| 990 | # | # | $a 213026192 |
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