Design, Development and Testing of a Low-Cost sEMG System and Its Use in Recording Muscle Activity in Human Gait

• Published in: Sensors (Basel, Switzerland) Vol. 14; no. 5; pp. 8235 - 8258
• Main Authors: Supuk, Tamara, Skelin, Ana, Cic, Maja
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 07.05.2014; Molecular Diversity Preservation International (MDPI)
• Subjects: Adult; Algorithms; Amplifiers, Electronic; artificial EMG signal; bioamplifier; Biomechanics; biomedical sensors; Croatia; Design engineering; Electromyography; Electromyography - economics; Electromyography - instrumentation; EMG signal envelope; Equipment Design; Equipment Failure Analysis; Female; Gait; Gait - physiology; Higher harmonics; Humans; Leg - physiology; Male; Measurement techniques; muscle activity during human gait; Muscle Contraction - physiology; Muscle function; Muscle, Skeletal - physiology; Muscles; Noise; Noise reduction; noise removal; Physiology; Radiation; Recording; Reproducibility of Results; Sampling; Sensitivity and Specificity; Sensors; Signal processing; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio; surface electromyography (sEMG) signals; Wavelet Analysis; wavelets; Young Adult; Croatia
• DOI: 10.3390/s140508235
• ISSN: 1424-8220

Surface electromyography (sEMG) is an important measurement technique used in biomechanical, rehabilitation and sport environments. In this article the design, development and testing of a low-cost wearable sEMG system are described. The hardware architecture consists of a two-cascade small-sized bioamplifier with a total gain of 2,000 and band-pass of 3 to 500 Hz. The sampling frequency of the system is 1,000 Hz. Since real measured EMG signals are usually corrupted by various types of noises (motion artifacts, white noise and electromagnetic noise present at 50 Hz and higher harmonics), we have tested several denoising techniques, both on artificial and measured EMG signals. Results showed that a wavelet—based technique implementing Daubechies5 wavelet and soft sqtwolog thresholding is the most appropriate for EMG signals denoising. To test the system performance, EMG activities of six dominant muscles of ten healthy subjects during gait were measured (gluteus maximus, biceps femoris, sartorius, rectus femoris, tibialis anterior and medial gastrocnemius). The obtained EMG envelopes presented against the duration of gait cycle were compared favourably with the EMG data available in the literature, suggesting that the proposed system is suitable for a wide range of applications in biomechanics.