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 › Published conference contribution

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	2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings
Subtitle of host publication	ICASSPW 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	4
ISBN (Electronic)	9798350302615
ISBN (Print)	979-8-3503-0262-2
DOIs	https://doi.org/10.1109/ICASSPW59220.2023.10193140
Publication status	Published - 2 Aug 2023
Event	2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, ICASSPW 2023 - Rhodes Island, Greece Duration: 4 Jun 2023 → 10 Jun 2023

Conference

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

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Insight Generation
Insight Recommendation
Lifestyle Intervention
Simulations
Wearables

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10.1109/ICASSPW59220.2023.10193140Licence: Unspecified

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Smart Selection of Useful Insights from Wearables. / Susaiyah, Allmin; Harma, Aki; Balloccu, Simone et al.
2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings: ICASSPW 2023 . Institute of Electrical and Electronics Engineers Inc., 2023.

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

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

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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",

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doi = "10.1109/ICASSPW59220.2023.10193140",

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AU - Susaiyah, Allmin

AU - Harma, Aki

AU - Balloccu, Simone

AU - Reiter, Ehud

AU - Petkovic, Milan

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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.

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KW - Insight Recommendation

KW - Lifestyle Intervention

KW - Simulations

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M3 - Published conference contribution

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SN - 979-8-3503-0262-2

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

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Smart Selection of Useful Insights from Wearables

Abstract

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Bibliographical note

Keywords

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