Smart Selection of Useful Insights from Wearables

Allmin Susaiyah; Aki Harma; Simone Balloccu; Ehud Reiter; Milan Petkovic

doi:10.1109/ICASSPW59220.2023.10193140

Smart Selection of Useful Insights from Wearables

Allmin Susaiyah^*, Aki Harma, Simone Balloccu, Ehud Reiter, Milan Petkovic

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

The popularity of wearable-devices equipped with inertial measurement units (IMUs) and optical sensors has increased in recent years. These sensors provide valuable activity and heart-rate data that, when analysed across multiple users and over time, can offer profound insights into individual lifestyle habits. However, the high dimensionality of such data and user preference dynamics present significant challenges for mining useful insights. This paper proposes a novel approach that employs natural language processing to mine insights from wearable-data, utilising a neural network model that leverages end-to-end feedback from users. Results demonstrate that this approach effectively increased daily step counts among users, showcasing the potential of this method for optimising health and wellness outcomes.

Original language	English
Title of host publication	ICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings
Publisher	IEEE
Pages	1-4
Number of pages	4
ISBN (Electronic)	9798350302615
DOIs	https://doi.org/10.1109/ICASSPW59220.2023.10193140
Publication status	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops - Rhodes Island, Greece Duration: 4 Jun 2023 → 10 Jun 2023

Conference

Conference	2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops
Abbreviated title	ICASSPW 2023
Country/Territory	Greece
City	Rhodes Island
Period	4/06/23 → 10/06/23

Keywords

Insight Generation
Insight Recommendation
Lifestyle Intervention
Simulations
Wearables

Access to Document

10.1109/ICASSPW59220.2023.10193140

Cite this

@inproceedings{45a70fb84dba4e0685574e631a492be9,

title = "Smart Selection of Useful Insights from Wearables",

abstract = "The popularity of wearable-devices equipped with inertial measurement units (IMUs) and optical sensors has increased in recent years. These sensors provide valuable activity and heart-rate data that, when analysed across multiple users and over time, can offer profound insights into individual lifestyle habits. However, the high dimensionality of such data and user preference dynamics present significant challenges for mining useful insights. This paper proposes a novel approach that employs natural language processing to mine insights from wearable-data, utilising a neural network model that leverages end-to-end feedback from users. Results demonstrate that this approach effectively increased daily step counts among users, showcasing the potential of this method for optimising health and wellness outcomes.",

keywords = "Insight Generation, Insight Recommendation, Lifestyle Intervention, Simulations, Wearables",

author = "Allmin Susaiyah and Aki Harma and Simone Balloccu and Ehud Reiter and Milan Petkovic",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, ICASSPW 2023 ; Conference date: 04-06-2023 Through 10-06-2023",

year = "2023",

doi = "10.1109/ICASSPW59220.2023.10193140",

language = "English",

pages = "1--4",

booktitle = "ICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings",

publisher = "IEEE",

address = "United States",

}

Susaiyah, A, Harma, A, Balloccu, S, Reiter, E & Petkovic, M 2023, Smart Selection of Useful Insights from Wearables. in ICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings. IEEE, pp. 1-4, 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Rhodes Island, Greece, 4/06/23. https://doi.org/10.1109/ICASSPW59220.2023.10193140

Smart Selection of Useful Insights from Wearables. / Susaiyah, Allmin; Harma, Aki; Balloccu, Simone et al.
ICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings. IEEE, 2023. p. 1-4.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

TY - GEN

T1 - Smart Selection of Useful Insights from Wearables

AU - Susaiyah, Allmin

AU - Harma, Aki

AU - Balloccu, Simone

AU - Reiter, Ehud

AU - Petkovic, Milan

PY - 2023

Y1 - 2023

N2 - The popularity of wearable-devices equipped with inertial measurement units (IMUs) and optical sensors has increased in recent years. These sensors provide valuable activity and heart-rate data that, when analysed across multiple users and over time, can offer profound insights into individual lifestyle habits. However, the high dimensionality of such data and user preference dynamics present significant challenges for mining useful insights. This paper proposes a novel approach that employs natural language processing to mine insights from wearable-data, utilising a neural network model that leverages end-to-end feedback from users. Results demonstrate that this approach effectively increased daily step counts among users, showcasing the potential of this method for optimising health and wellness outcomes.

AB - The popularity of wearable-devices equipped with inertial measurement units (IMUs) and optical sensors has increased in recent years. These sensors provide valuable activity and heart-rate data that, when analysed across multiple users and over time, can offer profound insights into individual lifestyle habits. However, the high dimensionality of such data and user preference dynamics present significant challenges for mining useful insights. This paper proposes a novel approach that employs natural language processing to mine insights from wearable-data, utilising a neural network model that leverages end-to-end feedback from users. Results demonstrate that this approach effectively increased daily step counts among users, showcasing the potential of this method for optimising health and wellness outcomes.

KW - Insight Generation

KW - Insight Recommendation

KW - Lifestyle Intervention

KW - Simulations

KW - Wearables

UR - https://www.scopus.com/pages/publications/85168250181

U2 - 10.1109/ICASSPW59220.2023.10193140

DO - 10.1109/ICASSPW59220.2023.10193140

M3 - Conference article in proceeding

AN - SCOPUS:85168250181

SP - 1

EP - 4

BT - ICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings

PB - IEEE

T2 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops

Y2 - 4 June 2023 through 10 June 2023

ER -

Smart Selection of Useful Insights from Wearables

Abstract

Conference

Keywords

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