• accelerometer
• Android
• devices
• dsp
• electromyography
• emg
• gestuality
• gesture
• gestures
• hand
• machine learning
• Myo
• recognition
• signals
• wearable

Hand gestures play a fundamental role in human interaction. In this thesis we investigate if wearable devices can be exploited to support hand gesture recognition; in particular we present a system composed by two wearable devices connected to user's arm. This two devices collect data from accelerometer sensors and surface electromyographic sensors; data are then filtered, segmented and stored. We evaluated this system with ten different user and we have used collected data to realize a gesture recognizer.