Despite the significant amount of research on the application of myoelectric research for upper limb prostheses control [1] and advances in signal processing and classification methods for myoeletric signals (MES), patient satisfaction and acceptance for modern hand prostheses is lacking [2]. This is partly due to missing intuitive and natural control possibilities for accessing the various grip patterns that are available with current prostheses models on the market. As a step towards easy prototyping and seamless integration of a wide variety of prostheses, we present a system based on the Arduino microcontroller platform. With adaptable Simulink TM models and a wide number of libraries for the Arduino IDE, the system allows electromyographic (EMG) processing as well as basic classification for actuating both basic hand models and more advanced hand prostheses. Complex classifier models can be trained with a PC-based MATLABTM application prior to microcontroller operation.     «

Despite the significant amount of research on the application of myoelectric research for upper limb prostheses control [1] and advances in signal processing and classification methods for myoeletric signals (MES), patient satisfaction and acceptance for modern hand prostheses is lacking [2]. This is partly due to missing intuitive and natural control possibilities for accessing the various grip patterns that are available with current prostheses models on the market. As a step towards easy prot...     »