EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

Abstract

Objective Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.

Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges

“…These mobile presentation-devices can be coupled with tailored commercially-available software programmes that allow for data collection with high temporal precision (e.g., Presentation Mobile App; www.neurobs.com ). Some of the smartphone-based applications can incorporate stimuli presentation, signal recording and online processing all within a single device ( Blum et al, 2017 ; Stopczynski et al, 2014b ; Wang et al, 2013 ).…”

“…The flexibility of mobile EEG has been demonstrated in several existing studies ( Liu et al, 2013 ; Poulsen et al, 2017 ; Wascher et al, 2014 ), including one in an open cockpit biplane during flight ( Callan et al, 2015 ). While most commercially-available mobile EEG systems cannot be operated with smartphones – with a few exceptions ( Blum et al, 2017 ; Stopczynski et al, 2014b ; Wang et al, 2013 ) – smartphone-based EEG holds promise for further increasing the portability of a ‘mobile EEG lab’ that would allow for controlled stimuli-delivery in everyday settings with minimal equipment. Testing in convenient locations (e.g., schools or homes) can be advantageous for neurodevelopmentalists, as this reduces the burden on participants and their families from travelling, and is also more inclusive of those who would prefer not to travel, for example, autistic participants who may be anxious about travelling or patients for whom leaving a hospital could be counterindicated.…”

Development of a Modular Board for EEG Signal Acquisition

“…The lack of validation, design knowledge, and analysis for such systems impede progress in this field. Even if there were inappropriate trials to use mobile devices for such a problem [ 6 ], professional high-quality and high-resolution analog front-ends are required to capture the non-stationary brain signals in microvolt ranges. With the introduction of dedicated EEG low-noise programmable analog-to-digital converters (ADCs) such as the ADS1298, such tasks can be achieved more easily.…”

Improved Activity Recognition Combining Inertial Motion Sensors and Electroencephalogram Signals

“…Some works study the auditive odd-ball task ERPs while sitting versus pedaling. 73,74 In an other study, 75 subjects carry out an inhibitory task while walking versus sitting. Other studies include the analysis of pianists EEG ERPs and power spectrum while performing a simple tune, 57 the prediction of braking intention from ERPs, 76 and the effect of rhythmic auditory stimulation on auditory motor synchronization on Parkinson's disease patients.…”

“…However, our sample is greater than those of recently published works on mobile EEG. 73,74,76 The gender representation is quite imbalanced, hence it is not possible to carry out any gender-related contrast analysis. We have carried out the data capture sessions inside rooms without working electrical equipment, but we have not ensured total electromagnetic isolation, i.e.…”