Bioelectric potentials provide an intuitive source of control in human-machine interfaces. In this work, a low-cost system for bioelectric signals acquisition and processing was developed and made available as open source. A single module based on the ADS1299 (Texas Instruments, USA) can acquire up to 8 differential or single-ended channels with a resolution of 24 bits and programmable gain up to 24 V/V. Several modules can be daisy-chained together to increase the number of input channels. Opto-isolated USB communication was included in the design to interface safely with a personal computer. The system was designed to be compatible with a low-cost and widely available microcontroller development platform, namely the Tiva LaunchPad (Texas Instruments, USA) featuring an ARM Cortex-M4 core. We made the source files for the PCB, firmware, and high-level software available online (GitHub: ADS_BP). Digital processing was used for float conversion and filtering. The high-level software for control and acquisition was integrated into an already existent open source platform for advanced myoelectric control, namely BioPatRec. This integration provide a complete system for intuitive myoelectric control where signal processing, machine learning, and control algorithms are used for the prediction of motor volition and control of robotic and virtual devices.