Electromyography (EMG) is a common tool in electrical muscle activity measurement and can be used in multiple areas of clinical and biomedical applications, mainly in identifying neuromuscular diseases, analyzing movement or in human machine interfaces. Traditionally a pair of electrodes were used to measure the signals, but in recent years the use of high density surface EMG (HD-sEMG) gained more popularity as it can sample myoelectric activities from multiple electrodes in an array on a single muscle and provide more information. In this thesis a measurement setup and protocol is proposed that can provide a reliably measurement, furthermore multiple features are extracted from the collected signals to characterise the major muscles around the ankle. 5 healthy subjects were tested using an ankle dynamometer with 5 HD-sEMG placed on the Tibialis Anterior, the Gastrocnemius Medialis, the Soleus, the Gastrocnemius Lateralis, and on the Peroneus Longus. Several tests were conducted using different initial angle of the ankle joint and different percentages of the maximum voluntary contraction. The reliability of the setup was assessed by comparing the variance between the collected signals of the same subject in a repeated test, and by comparing different subjects to each other. Results show a reasonably good reliability with less than $10\%$ variance, and adequate selectivity as well. To examine the muscle characteristics, 7 features were extracted from the collected and processed signals, then the features were plotted and compared to signs for muscle characteristics such as muscle fatigue, activation, and spatial distribution of activation. Correlations between features of mean average value (MAV) and zero crossing (ZC), and different muscle characteristics could be observed.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-289859 |
| Date | January 2021 |
| Creators | Szabó, Balázs |
| Publisher | KTH, Skolan för kemi, bioteknologi och hälsa (CBH) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-CBH-GRU ; 2020:290 |
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