Evaluation of the Influence of Head Movement on Hearing Aid Algorithm Performance Using Acoustic Simulations

Abstract

Head movements can improve sound localization performance and speech intelligibility in acoustic environments with spatially distributed sources. However, they can affect the performance of hearing aid algorithms, when adaptive algorithms have to adjust to changes in the acoustic scene caused by head movement (the so-called maladaptation effect) or when directional algorithms are not facing in the optimal direction because the head has moved away (the so-called misalignment effect). In this article, we investigated the mechanisms behind these maladaptation and misalignment effects for a set of six standard hearing aid algorithms using acoustic simulations based on premade databases; this was done so we could study the effects as carefully as possible. Experiment 1 investigated the maladaptation effect by analyzing hearing aid benefit after simulated rotational head movement in simple anechoic noise scenarios. The effects of movement parameters (start angle and peak velocity), noise scenario complexity, and adaptation time were studied, as well as the recovery time of the algorithms. However, a significant maladaptation effect was only found in the most unrealistic anechoic scenario with one noise source. Experiment 2 investigated the effects of maladaptation and misalignment using previously recorded natural head movements in acoustic scenes resembling everyday life situations. In line with the results of Experiment 1, no effect of maladaptation was found in these more realistic acoustic scenes. However, a significant effect of misalignment on the performance of directional algorithms was found. This demonstrates the need to take head movement into account in the evaluation of directional hearing aid algorithms.

Speech Intelligibility and Spatial Release From Masking Improvements Using Spatial Noise Reduction Algorithms in Bimodal Cochlear Implant Users

“…Moreover, when moving the head, adaptive beamformers need time to adjust to the new target direction. Hendrikse et al. (2020) found this effect of algorithm adaptation to be less than 1 dB in realistic everyday scenarios comparable to ours.…”

“…Furthermore, in more realistic acoustic environments, Grange and Culling (2016) have shown that even small amounts of head orientation differences can result in considerable SNR changes at the hearing device's microphones. Moreover, Hendrikse et al (2020) investigated the effect of head movements on algorithm benefit in various spatial acoustic scenarios, and they found a significant detrimental effect on the benefit provided by adaptive beamformers. Consequently, the influence of the subject's head orientation and movement on the beamformers' benefits reported by free-field studies cannot be ruled out.…”

The Virtual Reality Lab: Realization and Application of Virtual Sound Environments

“…In that case, subjects virtually stopped moving their heads. Because head movement reduces the benefit in signal to noise ratio provided by spatial filtering ( Hendrikse et al 2020 ), realistic head movement may be a crucial factor in ecologically more valid hearing aid evaluation in the lab.…”

“…The proposed approach can be illustrated by the example of head movements that typically occur in acoustic communication conditions. Hendrikse et al (2020) found in the virtual reality lab that individual head-movement tracks recorded in turn-taking conversations ( Hendrikse et al 2019 ) differentially affected the benefit in signal to noise ratio provided by a standard adaptive directional microphone and that head movement significantly reduced signal to noise ratio benefit of the adaptive directional microphone on average. This demonstrates the relevance of realistic head movement for ensuring the ecological validity of hearing aid outcome measures (benefit in signal to noise ratio, in this case).…”

“…Whereas the quality of acoustic and visual stimulation (items 1 and 2) can be controlled parametrically using current virtual reality technology, and, as mentioned earlier, several studies relating the factors of acoustic and visual stimulation with the corresponding metrics have been published (e.g., Hendrikse et al 2018 , 2019 , 2020 ), items 3 and 4 are largely under-investigated, to the knowledge of the authors. On the basis of the notion of the relevance of bodily acts in communication ( Mead 1956 , p. 98), we may assume that head movements, as well as other gestures, such as leaning forward or backward, or arm and hand movements, are important observables/metrics for estimating the level of involvement, and thus the level of ecological validity, also for items 3 and 4.…”