###### Abstract  
Biopotential signals are mainly characterized by low amplitude and thus often distorted by extraneous interferences, such as power line interference in the recording environment and movement artifacts during the acquisition process. With the presence of such large-amplitude interferences, subsequent processing and analysis of the acquired signals becomes quite a challenging task that has been reported by many previous studies. A number of software-based filtering techniques have been proposed, with most of them being able to minimize the interferences but at the expense of distorting the useful components of the target signal. Therefore, this study proposes a hardware-based method that utilizes a shielded drive circuit to eliminate extraneous interferences on biopotential signal recordings, while also preserving all useful components of the target signal. The performance of the proposed method was evaluated by comparing the results with conventional hardware and software filtering methods in three different biopotential signal recording experiments (electrocardiogram (ECG), electro-coulogram (EOG), and electromyography (EMG)) on an ADS1299 EEG-FE platform. The results showed that the proposed method could effectively suppress power line interference as well as its harmonic components, and it could also significantly eliminate the influence of unwanted electrode lead jitter interference. Findings from this study suggest that the proposed method may provide potential insight into high quality acquisition of different biopotential signals to greatly ease subsequent processing in various biomedical applications. shielded drive; power line interference; electrode lead jitter; ECG; EOG; EMG 2018 8 276 20  
in neuroscience, cognitive psychology, and artificial intelligence research, biopotential signals are being increasingly applied to real-time health monitoring, disease diagnoses, control rehabilitation devices, and brain-computer interfaces among others [2,3]. Generally, biopotential signals such as electrocardiogram (ECG), electromyography (EMG), electroencephalography (EEG), and electro-coculogram (EOG) are characterized by high impedance, low frequency, low amplitude, and strong background noise [4,5]. For instance, the amplitude and frequency of an ECG signal typically lie within the range of 0.05-4 mV and 0.05-150 Hz, respectively [6]; the EMG signal has an amplitude that is relatively weaker, in the range of 0.1-2 mV, and a frequency in the range of 0-500 Hz [7,8]; and the EOG signal's amplitude is in the range of 0.4-10 mV with a spectrum in the range of 0.1-38 Hz [9]. When a biopotential signal is recorded, the target/output of the recordings is almost completely submerged by the background noise/interference inherent in the recordings because the signal is often characterized by low amplitude [10]. Thus, such noise/interference is majorly classified into three categories as follows: Firstly, power line interference, which is composed of a 50 Hz or 60 Hz frequency and its harmonics, commonly defined as the electromagnetic noise produced from the power supply circuitry and electronic equipment [11]. Secondly, movement artifacts caused by poor contact between the electrodes and the surface of an individual's skin [12], or as a result of movement of the wires/cables between the electrodes and the amplifier [13]. Thirdly, physiological artifacts in the form of other signal(s) recorded alongside the originally desired biopotential signals [14,15]. To date, several methods have been proposed to eliminate the above-described interferences/noises from a biopotential signal of interest. To that end, most of the methods focused on improving hardware circuitry and using software filtering techniques [16, 17, 18].