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Title:Zaznava mišične utrujenosti s pomočjo površinskih elektromiogramov in senzorja microsoft kinect
Authors:ID Rojko, Lovro (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf MAG_Rojko_Lovro_2017.pdf (4,57 MB)
MD5: 8955846720FC29C757B25D8C70B237DE
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrskem delu smo proučevali možnost zaznavanja mišične utrujenosti s pomočjo senzorja Microsoft Kinect. Opisali smo zajem površinskih elektromiogramov (EMG) dvoglave in troglave nadlaktne mišice in kinetičnih meritev zgornjih okončin štirih zdravih merjencev in analizirali skupne karakteristike zajetih signalov. Iz kinetičnih meritev smo izračunali štiri veličine, in sicer pot, hitrost, pospešek in višino izvedene vaje. Časovne spremembe teh veličin smo statistično primerjali s spremembo amplitude signalov EMG, ki je znan pokazatelj mišične utrujenosti. Ugotovili smo, da se utrujenost mišice relativno dobro odraža v višini gibov, ostale kinetične metrike pa so bile za našo raziskavo manj informativne. Na podlagi teh rezultatov ocenjujemo, da je v primeru večkratnih ponovitev gibov zgornjih okončin možno zaznavati mišično utrujenost tudi samo iz kinetičnih meritev.
Keywords:Kinect, elektromiogram, mišična utrujenost, hitrost, pot, pospeški, RMS, kinetične meritve, vmesniki človek–stroj
Place of publishing:Maribor
Publisher:[L. Rojko]
Year of publishing:2017
PID:20.500.12556/DKUM-66235 New window
UDC:004.5:612.744(043.2)
COBISS.SI-ID:20702742 New window
NUK URN:URN:SI:UM:DK:I6XUSDKZ
Publication date in DKUM:03.07.2017
Views:1680
Downloads:194
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:Muscle fatigue detection with surface electromyograms and microsoft kinect sensor
Abstract:In this thesis, we examined the possibility of detecting muscle fatigue by using a Microsoft Kinect sensor. We simultaneously acquired surface electromyograms (EMG) of biceps brachii and triceps muscles and movements of upper extremity by Kinect sensor in four healthy subjects and analysed the common characteristics of the acquired signals. For each movement repetition, we calculated five different metrics from kinetic measurements, namely number of movement repetitions per time unit, distance, speed, acceleration and the maximal height of the arm. Temporal changes in these variables were statistically compared with the changes in the root mean square amplitude of the EMG signals, which is a well-known indicator of muscle fatigue. We found that muscle fatigue is relatively well reflected in the height of the arm, whereas the other tested kinetic metrics were less indicative for muscle fatigue. Based on these results we conclude that muscle fatigue can be detected from kinetic measurements of repeated upper limb movements.
Keywords:Kinect, electromyogram, muscle fatigue, speed, distance, acceleration, root mean square, kinetic measurement’s, human-computer interfaces


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