| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document

Title:VMESNIK MIŠICE-STROJ ZA RAZPOZNAVANJE ELEKTROMIOGRAFSKIH MERITEV MIŠIC PODLAHTI
Authors:Jug, Miloš (Author)
Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf UN_Jug_Milos_2016.pdf (2,84 MB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu smo proučili področje neinvazivnega merjenja elektromiogramov (EMG) mišic podlahti in razpoznavo gibov s pomočjo nevronskih mrež. Za zajem signalov EMG smo uporabili zapestnico Myo, iz katere smo pridobili še podatke o kotu pronacije in supinacije zapestja. Razviti programski vmesnik omogoča shranjevanje in vizualizacijo signalov EMG in razpoznava osem gibov, in sicer fleksijo, ekstenzijo, radialno deviacijo, ulnarno deviacijo, pronacijo in supinacijo zapestja ter stisnjeno pest in razširjeno dlan. S temi gibi nadzira navidezno gibanje v štirih prostostnih stopnjah. Preučili smo vpliv števila nevronov v skriti plasti nevronske mreže in vpliv števila kanalov na natančnost razpoznave gibov. V sklopu diplomske naloge smo priredili tudi odprtokodno igro, ki simulira letenje letala in za njegov nadzor uporabili gibe zapestja.
Keywords:vmesnik mišice-stroj, površinski elektromiogram, nevronska mreža, zapestnica Myo, razpoznava gest, simulacija letenja
Year of publishing:2016
Publisher:M. Jug
Source:[Maribor
UDC:004.5:621.391(043.2)
COBISS_ID:20144150 Link is opened in a new window
NUK URN:URN:SI:UM:DK:99XSUWZP
Views:443
Downloads:76
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
:
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:AddThis
AddThis uses cookies that require your consent. Edit consent...

Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Secondary language

Language:English
Title:MUSCLE-COMPUTER INTERFACE FOR CLASSIFICATION OF FOREARM ELECTROMYOGRAPHIC SIGNALS
Abstract:muscle-computer interface, surface electromyogram, neural net, Myo armband, gesture recognition, flight simulation
Keywords:In this diploma thesis we studied non-invasive electromyogram (EMG) measurements of forearm muscles and gesture recognition with neural networks. We used Myo armband for signal capturing. Along with EMG signals, we also recorded angle of forearm pronation and supination. Developed programming interface supports saving and visualisation of EMG signals and recognises eight gestures, namely writs extension, flexion, radial deviation, ulnar deviation, pronation, supination, fist making and spread palm. With these gestures the interface controls four degrees of freedom. We have studied how the number of neurons in the hidden layer of the neural network and the number of channels affect accuracy of described gesture recognition. We also adapted an open source flight simulator game, in order to control it with wrist gestures.


Comments

Leave comment

You have to log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica