Can Changes in Heart Rate Variability Represented in Sound be Identified by Non-Medical Experts?

Bahameish, Mariam

doi:10.1145/3290607.3308456

Cited by 4 publications

(7 citation statements)

References 7 publications

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“…Rather we aimed at clustering the data pairwise to investigate the The next phase of the work was the sonification of the HRV features. In [8] authors sonified the HRV features using a linear mapping. Although which time and frequency domain features were sonified was not explicitly mentioned.…”

Section: Resultsmentioning

confidence: 99%

“…Visual inspection of the spectrograms reveals the distinctive nature of the sonified sounds. An evaluation done by [8] can be helpful in validating the effectiveness of the sonified signals. We adpot a formant synthesis sonification approach with the intuition that it could potentially activate the linguistic centers of the brain, which will make it easy to learn and recall the sound better.…”

Section: Resultsmentioning

confidence: 99%

“…They also used inter beat intervals as a clock to provide the timing for each granular event. In [8] author have examined the categorization task performance of their sonified signals. They found the accuracy of meditation types and states based on their developed auditory interface as 85.6 percent.…”

Section: Related Work a Sonificationmentioning

confidence: 99%

“…They also used inter beat intervals as a clock to provide the timing for each granular event. In [8]…”

Section: Related Work a Sonificationmentioning

confidence: 99%

“…Bio-feedback might also find its use in intelligent health recommend systems [19]. In [8] authors have investigated the effectiveness of representing HRV data with auditory interfaces as a supplement or complement to visual displays. In this paper, we have adopted a similar approach.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy C-Means Clustering and Sonification of HRV Features

Borthakur

Grace²,

Batchelor³

et al. 2019

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)

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Linear and non-linear measures of heart rate variability (HRV) are widely investigated as non-invasive indicators of health. Stress has a profound impact on heart rate, and different meditation techniques have been found to modulate heartbeat rhythm. This paper aims to explore the process of identifying appropriate metrices from HRV analysis for sonification. Sonification is a type of auditory display involving the process of mapping data to acoustic parameters. This work explores the use of auditory display in aiding the analysis of HRV leveraged by unsupervised machine learning techniques. Unsupervised clustering helps select the appropriate features to improve the sonification interpretability. Vocal synthesis sonification techniques are employed to increase comprehension and learnability of the processed data displayed through sound. These analyses are early steps in building a real-time sound-based biofeedback training system.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Related Work a Sonificationmentioning

confidence: 99%

“…They also used inter beat intervals as a clock to provide the timing for each granular event. In [8]…”

Section: Related Work a Sonificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fuzzy C-Means Clustering and Sonification of HRV Features

Borthakur

Grace²,

Batchelor³

et al. 2019

2019 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)

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Listening to life: Sonification for enhancing discovery in biological research

Braun,

Tfirn,

Ford

2024

Biotech & Bioengineering

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Sonification, or the practice of generating sound from data, is a promising alternative or complement to data visualization for exploring research questions in the life sciences. Expressing or communicating data in the form of sound rather than graphs, tables, or renderings can provide a secondary information source for multitasking or remote monitoring purposes or make data accessible when visualizations cannot be used. While popular in astronomy, neuroscience, and geophysics as a technique for data exploration and communication, its potential in the biological and biotechnological sciences has not been fully explored. In this review, we introduce sonification as a concept, some examples of how sonification has been used to address areas of interest in biology, and the history of the technique. We then highlight a selection of biology‐related publications that involve sonifications of DNA datasets and protein datasets, sonifications for data collection and interpretation, and sonifications aimed to improve science communication and accessibility. Through this review, we aim to show how sonification has been used both as a discovery tool and a communication tool and to inspire more life‐science researchers to incorporate sonification into their own studies.

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