Obtaining Data on Hearing Experience Through Self-tracking

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2016Researchpeer-review

Standard

Obtaining Data on Hearing Experience Through Self-tracking. / Johansen, Benjamin; Petersen, Michael Kai; Larsen, Jakob Eg.

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16). Association for Computing Machinery, 2016. p. 594-599.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2016Researchpeer-review

Harvard

Johansen, B, Petersen, MK & Larsen, JE 2016, Obtaining Data on Hearing Experience Through Self-tracking. in Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16). Association for Computing Machinery, pp. 594-599, 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct , Heidelberg, Germany, 12/09/2016. https://doi.org/10.1145/2968219.2968327

APA

Johansen, B., Petersen, M. K., & Larsen, J. E. (2016). Obtaining Data on Hearing Experience Through Self-tracking. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16) (pp. 594-599). Association for Computing Machinery. https://doi.org/10.1145/2968219.2968327

CBE

Johansen B, Petersen MK, Larsen JE. 2016. Obtaining Data on Hearing Experience Through Self-tracking. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16). Association for Computing Machinery. pp. 594-599. https://doi.org/10.1145/2968219.2968327

MLA

Johansen, Benjamin, Michael Kai Petersen, and Jakob Eg Larsen "Obtaining Data on Hearing Experience Through Self-tracking". Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16). Association for Computing Machinery. 2016, 594-599. https://doi.org/10.1145/2968219.2968327

Vancouver

Johansen B, Petersen MK, Larsen JE. Obtaining Data on Hearing Experience Through Self-tracking. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16). Association for Computing Machinery. 2016. p. 594-599 https://doi.org/10.1145/2968219.2968327

Author

Johansen, Benjamin ; Petersen, Michael Kai ; Larsen, Jakob Eg. / Obtaining Data on Hearing Experience Through Self-tracking. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16). Association for Computing Machinery, 2016. pp. 594-599

Bibtex

@inproceedings{b82a23c0442f4cd3af064cfd89f450b4,
title = "Obtaining Data on Hearing Experience Through Self-tracking",
abstract = "This position paper argues that self-tracking data can enrich a pre-fitting process of hearing aids. It is argued that hearing loss consist of three parts. Tonal sensitivity, signal to-noise-sensitivity, and cognitive capabilities which can be assessed by using smartphones. Combining this with contextual data and subjective data (perceived fatigue for example), could generated a hearing profile for the end user. This could be used for continuous fitting based on user feedback of the hearing instruments at a later point in time.We suggest, that pre-fitting and a continuous process could create a paradigm shift empowering and transforming the user into an essential part of the solution, through increased awareness and inclusion. The end result could be a potentially better fitting, and a better hearing experience for the individual.",
keywords = "Hearing Aids, Cognition, Working Memory Capacity, Quanti ed self, non-clinical setu, Personal Informatics, Wearable, Smartphone",
author = "Benjamin Johansen and Petersen, {Michael Kai} and Larsen, {Jakob Eg}",
year = "2016",
doi = "10.1145/2968219.2968327",
language = "English",
isbn = "978-1-4503-4462-3",
pages = "594--599",
booktitle = "Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16)",
publisher = "Association for Computing Machinery",

}

RIS

TY - GEN

T1 - Obtaining Data on Hearing Experience Through Self-tracking

AU - Johansen, Benjamin

AU - Petersen, Michael Kai

AU - Larsen, Jakob Eg

PY - 2016

Y1 - 2016

N2 - This position paper argues that self-tracking data can enrich a pre-fitting process of hearing aids. It is argued that hearing loss consist of three parts. Tonal sensitivity, signal to-noise-sensitivity, and cognitive capabilities which can be assessed by using smartphones. Combining this with contextual data and subjective data (perceived fatigue for example), could generated a hearing profile for the end user. This could be used for continuous fitting based on user feedback of the hearing instruments at a later point in time.We suggest, that pre-fitting and a continuous process could create a paradigm shift empowering and transforming the user into an essential part of the solution, through increased awareness and inclusion. The end result could be a potentially better fitting, and a better hearing experience for the individual.

AB - This position paper argues that self-tracking data can enrich a pre-fitting process of hearing aids. It is argued that hearing loss consist of three parts. Tonal sensitivity, signal to-noise-sensitivity, and cognitive capabilities which can be assessed by using smartphones. Combining this with contextual data and subjective data (perceived fatigue for example), could generated a hearing profile for the end user. This could be used for continuous fitting based on user feedback of the hearing instruments at a later point in time.We suggest, that pre-fitting and a continuous process could create a paradigm shift empowering and transforming the user into an essential part of the solution, through increased awareness and inclusion. The end result could be a potentially better fitting, and a better hearing experience for the individual.

KW - Hearing Aids

KW - Cognition

KW - Working Memory Capacity

KW - Quanti ed self, non-clinical setu

KW - Personal Informatics

KW - Wearable

KW - Smartphone

U2 - 10.1145/2968219.2968327

DO - 10.1145/2968219.2968327

M3 - Article in proceedings

SN - 978-1-4503-4462-3

SP - 594

EP - 599

BT - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16)

PB - Association for Computing Machinery

ER -