Privacy-Aware Acoustic Assessments of Everyday Life

Bitzer, Jöerg; Kissner, Sven; Holube, Inga

doi:10.17743/jaes.2016.0020

Cited by 10 publications

(7 citation statements)

References 15 publications

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“…In order to comply with European privacy protection laws, which do not allow recording other people in public, it is necessary to store the audio in such a way that the content of conversations or the identity of a person is protected. There are smartphone based audio recording solutions that allow this by only storing some audio features (Bitzer, Kisser, & Holube, 2016;Kowalk, Kissner, von Gablenz, Holube, & Bitzer, 2018).…”

Section: Additional Sensorsmentioning

confidence: 99%

Building an Ear-EEG System by Hacking a Commercial Neck Speaker and a Commercial EEG Amplifier to Record Brain Activity Beyond the Lab

Bleichner

Emkes

2020

Journal of Open Hardware

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Electroencephalography (EEG) allows measuring human brain activity for scientific, diagnostic and therapeutic purposes. For scientific purposes, EEG is traditionally used to study the brain-behaviour relationship under well controlled laboratory conditions while the participant sits quietly in a room. Consequently, our knowledge regarding the brain-behaviour relationship was limited to human behaviour under constrained conditions. The development of mobile EEG hardware in the last years allows moving beyond the lab and studying brain activity in everyday life. Most EEG systems record from electrodes that are distributed over the head, kept in place with an elastic cap or net. For long term EEG recordings, to study natural behaviour in public, these systems are not optimal, as they are rather bulky and unpleasant to wear for longer periods. We argue for " transparent", ear-centered EEG systems instead. Transparent in the sense that both the person wearing the EEG system as well as the people interacting with that person are not disturbed by it. We describe here the integration of a commercially available research-grade mobile EEG amplifier and a commercially available neck speaker as a mounting system to be used in combination with ear electrodes (cEEGrid). This nEEGlace can be used for ear-EEG recordings in public over extended periods of time. The integrated microphone and the integrated speakers provide the possibility to play and record sound. This allows conducting experiments on auditory perception beyond the lab by both studying the brain responses to naturally occurring sounds as well as to experimental auditory stimuli. We describe the general design, present a working prototype, outline a number of use cases and discuss future improvements of the proposed design.

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Section: Additional Sensorsmentioning

confidence: 99%

Building an Ear-EEG System by Hacking a Commercial Neck Speaker and a Commercial EEG Amplifier to Record Brain Activity Beyond the Lab

Bleichner

Emkes

2020

Journal of Open Hardware

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“…Our privacy-preserving EMA system olMEGA 1 [24][25][26] only stored acoustical features (root mean square, RMS; auto and cross-power spectral density, PSD; zero crossing rate, ZCR). All features were calculated online from recordings by two head-worn, near-ear microphones attached to glasses.…”

Section: Privacy-preserving Featuresmentioning

confidence: 99%

“…The system has a flat frequency response within 1 dB between 100 Hz and 3 kHz. Beyond 3 kHz, a slight rise was measured up to 3 dB at 8 kHz [24]. The system was calibrated to SPL at 1 kHz.…”

Section: Privacy-preserving Featuresmentioning

confidence: 99%

“…The PSD of the 25 ms intervals (samplingrate = 80 Hz) were smoothed with a first-order, low-pass filter with time constants of s = 125 ms and the smoothed spectra were downsampled to 8 Hz to prevent reconstruction of the original signal. These processing steps led to unrecognizable speech in the reconstructed signal, but the presence of voices and their gender was not hidden [24].…”

Section: Privacy-preserving Featuresmentioning

confidence: 99%

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Near-ear sound pressure level distribution in everyday life considering the user’s own voice and privacy

Jule

Holube²,

Bitzer³

2022

Acta Acust.

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Recently, exploring acoustic conditions of people in their everyday environments has drawn a lot of attention. One of the most important and disturbing sound sources is the test participant’s own voice. This contribution proposes an algorithm to determine the own-voice audio segments (OVS) for blocks of 125 ms and a method for measuring sound pressure levels (SPL) without violating privacy laws. The own voice detection (OVD) algorithm here developed is based on a machine learning algorithm and a set of acoustic features that do not allow for speech reconstruction. A manually labeled real-world recording of one full day showed reliable and robust detection results. Moreover, the OVD algorithm was applied to 13 near-ear recordings of hearing-impaired participants in an ecological momentary assessment (EMA) study. The analysis shows that the grand mean percentage of predicted OVS during one day was approx. 10% which corresponds well to other published data. These OVS had a small impact on the median SPL over all data. However, for short analysis intervals, significant differences up to 30 dB occurred in the measured SPL, depending on the proportion of OVS and the SPL of the background noise.

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“…However, the responses are possibly biased by interlocked effects of long-term memory and inference (Bradburn, Rips, & Shevell, 1987; Shiffman, Stone, & Hufford, 2008). To bridge the temporal gap between perception and assessment of the perception, ecological momentary assessment methods have recently been applied in audiological research (e.g., Bitzer, Kissner, & Holube, 2016; Kowalk, Kissner, von Gablenz, Holube, & Bitzer, 2018; Wu, Stangl, Zhang, & Bentler, 2015) to avoid distortions by averaging auditory experiences over a long period of time. The development of measures to assess behaviors was established in this realm.…”

Section: Introductionmentioning

confidence: 99%

Development and Application of an Annotation Procedure to Assess the Impact of Hearing Aid Amplification on Interpersonal Communication Behavior

et al. 2018

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Hearing impairment is associated with a decrease in speech intelligibility and health-related quality of life, such as social isolation and participation restriction. However, little is known about the extent to which hearing impairment and hearing aid fittings change behavior in acute communication situations as well as interrelated behavior patterns. Based on a pilot study, in which the basis for annotating communication behavior was laid, group discussions in noise were initiated with 10 participants using three different hearing-aid brands. The proposed offline annotation scheme revealed that different hearing aids were associated with changes in behavior patterns. These behavioral changes were congruent with speech recognition threshold results and also with subjective assessments. Some of the results were interpreted in terms of participation restriction and activity limitation following the framework of the International Classification of Functioning, Disability and Health. In addition to the offline annotation scheme, a procedure for instantaneous coding of eight behavior patterns was iteratively developed and used for the quick examination of lab studies with good to excellent interrater reliability values.

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Privacy-Aware Acoustic Assessments of Everyday Life

Cited by 10 publications

References 15 publications

Building an Ear-EEG System by Hacking a Commercial Neck Speaker and a Commercial EEG Amplifier to Record Brain Activity Beyond the Lab

Building an Ear-EEG System by Hacking a Commercial Neck Speaker and a Commercial EEG Amplifier to Record Brain Activity Beyond the Lab

Near-ear sound pressure level distribution in everyday life considering the user’s own voice and privacy

Development and Application of an Annotation Procedure to Assess the Impact of Hearing Aid Amplification on Interpersonal Communication Behavior

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