Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Compact and low-noise Analog Front-Ends (AFEs) are becoming increasingly important for the acquisition of bioelectric signals in portable system. In this work,  compare two popular AFEs available on the market, namely the ADS1299 (Texas Instruments) and the RHA2216 (Intan Technologies). This work develops towards the identification of suitable acquisition modules to design an affordable, reliable and portable device for electromyography (EMG) acquisition and prosthetic control. Device features such as Common Mode Rejection (CMR), Input Referred Noise (IRN) and Signal to Noise Ratio (SNR) re evaluated, as ll as the resulting accuracy in myoelectric pattern recognition (MPR) for the decoding of motion intention. Results reported better noise performances and higher MPR accuracy for the ADS1299 and similar SNR values for both devices.
['Enzo Mastinu', 'Max Jair Ortiz-Catalan', 'Bo Håkansson']
I am writing a research paper on a idea Analog Front-Ends comparison in the way of a portable, low-power and low-cost EMG controller based on pattern recognition EMBC 2015.
[{"from": "human", "value": "I am writing a research paper on a idea Analog Front-Ends comparison in the way of a portable, low-power and low-cost EMG controller based on pattern recognition EMBC 2015."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Compact and low-noise Analog Front-Ends (AFEs) are becoming increasingly important for the acquisition of bioelectric signals in portable system. In this work,  compare two popular AFEs available on the market, namely the ADS1299 (Texas Instruments) and the RHA2216 (Intan Technologies). This work develops towards the identification of suitable acquisition modules to design an affordable, reliable and portable device for electromyography (EMG) acquisition and prosthetic control. Device features such as Common Mode Rejection (CMR), Input Referred Noise (IRN) and Signal to Noise Ratio (SNR) re evaluated, as ll as the resulting accuracy in myoelectric pattern recognition (MPR) for the decoding of motion intention. Results reported better noise performances and higher MPR accuracy for the ADS1299 and similar SNR values for both devices."}]