Smartphone-based ear-electroencephalography to study sound processing in everyday life.

In everyday life, people differ in their sound perception and thus sound processing. Some people may be distracted by construction noise, while others do not even notice. With smartphone-based mobile ear-electroencephalography (ear-EEG), we can measure and quantify sound processing in everyday life by analysing presented sounds and also naturally occurring ones. Twenty-four participants completed four controlled conditions in the lab (1 h) and one condition in the office (3 h). All conditions used the same paired-click stimuli. In the lab, participants listened to click tones under four different instructions: no task towards the sounds, reading a newspaper article, listening to an audio article or counting a rare deviant sound. In the office recording, participants followed daily activities while they were sporadically presented with clicks, without any further instruction. In the beyond-the-lab condition, in addition to the presented sounds, environmental sounds were recorded as acoustic features (i.e., loudness, power spectral density and sounds onsets). We found task-dependent differences in the auditory event-related potentials (ERPs) to the presented click sounds in all lab conditions, which underline that neural processes related to auditory attention can be differentiated with ear-EEG. In the beyond-the-lab condition, we found ERPs comparable to some of the lab conditions. The N1 amplitude to the click sounds beyond the lab was dependent on the background noise, probably due to energetic masking. Contrary to our expectation, we did not find a clear ERP in response to the environmental sounds. Overall, we showed that smartphone-based ear-EEG can be used to study sound processing of well defined-stimuli in everyday life.

Recording Brain Activity with Ear-Electroencephalography.

The c-grid (ear-electroencephalography, sold under the name cEEGrid) is an unobtrusive and comfortable electrode array that can be used for investigating brain activity after affixing around the ear. The c-grid is suitable for use outside of the laboratory for long durations, even for the whole day. Various cognitive processes can be studied using these grids, as shown by previous research, including research beyond the lab. To record high-quality ear-EEG data, careful preparation is necessary. In this protocol, we explain the steps needed for its successful implementation. First, how to test the functionality of the grid prior to a recording is shown. Second, a description is provided on how to prepare the participant and how to fit the c-grid, which is the most important step for recording high-quality data. Third, an outline is provided on how to connect the grids to an amplifier and how to check the signal quality. In this protocol, we list best practice recommendations and tips that make c-grid recordings successful. If researchers follow this protocol, they are comprehensively equipped for experimenting with the c-grid both in and beyond the lab.

Real-Time Audio Processing of Real-Life Soundscapes for EEG Analysis: ERPs Based on Natural Sound Onsets.

With smartphone-based mobile electroencephalography (EEG), we can investigate sound perception beyond the lab. To understand sound perception in the real world, we need to relate naturally occurring sounds to EEG data. For this, EEG and audio information need to be synchronized precisely, only then it is possible to capture fast and transient evoked neural responses and relate them to individual sounds. We have developed Android applications (AFEx and Record-a) that allow for the concurrent acquisition of EEG data and audio features, i.e., sound onsets, average signal power (RMS), and power spectral density (PSD) on smartphone. In this paper, we evaluate these apps by computing event-related potentials (ERPs) evoked by everyday sounds. One participant listened to piano notes (played live by a pianist) and to a home-office soundscape. Timing tests showed a stable lag and a small jitter (< 3 ms) indicating a high temporal precision of the system. We calculated ERPs to sound onsets and observed the typical P1-N1-P2 complex of auditory processing. Furthermore, we show how to relate information on loudness (RMS) and spectra (PSD) to brain activity. In future studies, we can use this system to study sound processing in everyday life.

Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer.

The streaming and recording of smartphone sensor signals is desirable for mHealth, telemedicine, environmental monitoring and other applications. Time series data gathered in these fields typically benefit from the time-synchronized integration of different sensor signals. However, solutions required for this synchronization are mostly available for stationary setups. We hope to contribute to the important emerging field of portable data acquisition by presenting open-source Android applications both for the synchronized streaming (Send-a) and recording (Record-a) of multiple sensor data streams. We validate the applications in terms of functionality, flexibility and precision in fully mobile setups and in hybrid setups combining mobile and desktop hardware. Our results show that the fully mobile solution is equivalent to well-established desktop versions. With the streaming application Send-a and the recording application Record-a, purely smartphone-based setups for mobile research and personal health settings can be realized on off-the-shelf Android devices.

Mobile ear-EEG to study auditory attention in everyday life : Auditory attention in everyday life.

Most research investigating auditory perception is conducted in controlled laboratory settings, potentially restricting its generalizability to the complex acoustic environment outside the lab. The present study, in contrast, investigated auditory attention with long-term recordings (> 6 h) beyond the lab using a fully mobile, smartphone-based ear-centered electroencephalography (EEG) setup with minimal restrictions for participants. Twelve participants completed iterations of two variants of an oddball task where they had to react to target tones and to ignore standard tones. A rapid variant of the task (tones every 2 s, 5 min total time) was performed seated and with full focus in the morning, around noon and in the afternoon under controlled conditions. A sporadic variant (tones every minute, 160 min total time) was performed once in the morning and once in the afternoon while participants followed their normal office day routine. EEG data, behavioral data, and movement data (with a gyroscope) were recorded and analyzed. The expected increased amplitude of the P3 component in response to the target tone was observed for both the rapid and the sporadic oddball. Miss rates were lower and reaction times were faster in the rapid oddball compared to the sporadic one. The movement data indicated that participants spent most of their office day at relative rest. Overall, this study demonstrated that it is feasible to study auditory perception in everyday life with long-term ear-EEG.