Design and Implementation of Analog Filter and Amplifier for Surface EMG Signals
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Date
2020
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Abstract
Bu çalışmada, sağlıklı bireylerin yüzey elektrotlar yardımıyla, ön kol kaslarından elektromyografi (EMG) ölçümünün, gerçek zamanlı alınması ve aktivite takibi yapabilen giyilebilir cihaz tasarımı hedeflenmiştir. Elin açma ve kapatma hareketleri tekrarlanarak ölçümler yapılmıştır. Ölçümler sırasında kol yüzeyi üzerinde oluşan, 0-10 mV arasındaki voltaj işlemsel yükselteç ile arttırılmıştır. Tasarlanan yükselteç devresinde, ham yüzey EMG başarılı şekilde ölçülmüştür. EMG sinyali üzerindeki elektriksel veya diğer etkenlerden kaynaklı gürültülerin çıkartılması için filtre devreleri tasarlanmıştır. Bu filtreler, yüksek geçiren ve alçak geçiren filtrelerdir. Filtrelerin, EMG sinyali üzerindeki gürültüleri yok ettikleri gözlemlenmiştir. Yükseltilmiş EMG sinyalinin daha kolay incelenebilmesi için, negatif polarmadaki sinyaller hassas doğrultucu ile pozitif polarmaya geçirilmiştir. Bu aşamadan sonra tasarlanan yumuşatma devresi, kasılma sırasında oluşan sinyallerdeki gürültüleri büyük oranda azaltmıştır diğer aşamalara göre verilerin daha net oldukları gözlemlenmiştir. Bu aşamalar sonunda, sinyalin genliği büyük oranda azalmıştır. Sinyalin genliğini arttırmak için tasarlanan kazanç devresi çıkış voltajı maksimum 3 V olarak ölçülmüştür. EMG sinyalinin kolay ve pratik şekilde incelenebilmesi için, üzerinde HMI modülü ve SD kart girişi bulunan mikrodenetleyici tabanlı kontrol kartı tasarlanmıştır. Bu sayede, verilerin gerçek zamanlı takibi ve kayıt başlatılması dokunmatik ekran üzerinde bulunan ara yüz ile yapılabilmiştir. Veriler '.cvs' formatında kayıt edilmiştir. Kayıtlı veriler yapay sinir ağları ile kol hareketlerinin sınıflandırılmasında veri kümesi olarak kullanılabilecektir. Anahtar Kelimeler: Elektromiyografi, işlemsel yükselteç, elektronik filtre, hassas doğrultucu, yumuşatma, yapay sinir ağları, HMI, SD kart.
In this study, it was aimed to design a wearable device that can take real-time measurement and activity monitoring of electromyography (EMG) from the forearm muscles with the help of surface electrodes of healthy individuals. The opening and closing movements of the hand were repeated and measurements were made. The voltage between 0-10 mV on the arm surface during the measurements is increased by the operational amplifier. In the designed amplifier circuit, raw surface EMG has been successfully measured. Filter circuits are designed to remove noise caused by electrical or other factors on the EMG signal. These filters are high pass and low pass filters. The filters have been observed to eliminate noises on the EMG signal. In order to analyze the amplified EMG signal more easily, the signals in the negative polarization were switched to positive polarization with the full wave rectifier. After this stage, the designed smoothing circuit greatly reduced the noise in the signals generated during the contraction, and it was observed that the data were clearer than other stages. At the end of these stages, the amplitude of the signal is greatly reduced. The gain circuit output voltage which was designed to increase the amplitude of the signal, was measured as 3 V maximum. In order to analyze the EMG signal easily and practically, a microcontroller based control card with HMI module and SD card input is designed. In this way, real time tracking and recording initiation of the data can be done with the interface on the touch screen. The data were recorded in '.cvs' format. The recorded data can be used as a dataset for classifying arm movements with neural networks. Key Words: electromyography, operational amplifier, electronic filter, precision rectifier, smoothing, neural networks, HMI, SD card.
In this study, it was aimed to design a wearable device that can take real-time measurement and activity monitoring of electromyography (EMG) from the forearm muscles with the help of surface electrodes of healthy individuals. The opening and closing movements of the hand were repeated and measurements were made. The voltage between 0-10 mV on the arm surface during the measurements is increased by the operational amplifier. In the designed amplifier circuit, raw surface EMG has been successfully measured. Filter circuits are designed to remove noise caused by electrical or other factors on the EMG signal. These filters are high pass and low pass filters. The filters have been observed to eliminate noises on the EMG signal. In order to analyze the amplified EMG signal more easily, the signals in the negative polarization were switched to positive polarization with the full wave rectifier. After this stage, the designed smoothing circuit greatly reduced the noise in the signals generated during the contraction, and it was observed that the data were clearer than other stages. At the end of these stages, the amplitude of the signal is greatly reduced. The gain circuit output voltage which was designed to increase the amplitude of the signal, was measured as 3 V maximum. In order to analyze the EMG signal easily and practically, a microcontroller based control card with HMI module and SD card input is designed. In this way, real time tracking and recording initiation of the data can be done with the interface on the touch screen. The data were recorded in '.cvs' format. The recorded data can be used as a dataset for classifying arm movements with neural networks. Key Words: electromyography, operational amplifier, electronic filter, precision rectifier, smoothing, neural networks, HMI, SD card.
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Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering
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73
