Smartphone Sensing for the Well-Being of Young Adults: A Review

Meegahapola, Lakmal; Gática-Pérez, Daniel

doi:10.1109/access.2020.3045935

Cited by 21 publications

(30 citation statements)

References 119 publications

(257 reference statements)

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“…Moreover, prior research in these domains have linked factors such as social context [52], eating location [41], availability and types of food [117], and psychological aspects [51] to food consumption behavior. With increasing smartphone coverage among young adults and the availability of a plethora of mobile health (mHealth) applications [78], smartphones have become a ubiquitous tool that can help young adults adhere to healthier food consumption practices [73].…”

Section: Introductionmentioning

confidence: 99%

One More Bite? Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-Reports

Meegahapola

Ruíz-Correa

Robledo-Valero

et al. 2021

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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While the characterization of food consumption level has been extensively studied in nutrition and psychology research, advancements in passive smartphone sensing have not been fully utilized to complement mobile food diaries in characterizing food consumption levels. In this study, a new dataset regarding the holistic food consumption behavior of 84 college students in Mexico was collected using a mobile application combining passive smartphone sensing and self-reports. We show that factors such as sociability and activity types and levels have an association to food consumption levels. Finally, we define and assess a novel ubicomp task, by using machine learning techniques to infer self-perceived food consumption level (eating as usual, overeating, undereating) with an accuracy of 87.81% in a 3-class classification task by using passive smartphone sensing and self-report data. Furthermore, we show that an accuracy of 83.49% can be achieved for the same classification task by using only smartphone sensing data and time of eating, which is an encouraging step towards building context-aware mobile food diaries and making food diary based apps less tedious for users.

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Section: Introductionmentioning

confidence: 99%

One More Bite? Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-Reports

Meegahapola

Ruíz-Correa

Robledo-Valero

et al. 2021

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Smartphones are ubiquitous and allow people to manage their personal health data (see, for example, [51][52][53]). A simple connection to cloud-based services to store and share data enables treatment over distance, which we facilitated by using the standardized LSL data handling framework.…”

Section: Discussionmentioning

confidence: 99%

Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer

Blum

Hölle

Bleichner

et al. 2021

Sensors

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The streaming and recording of smartphone sensor signals is desirable for mHealth, telemedicine, environmental monitoring and other applications. Time series data gathered in these fields typically benefit from the time-synchronized integration of different sensor signals. However, solutions required for this synchronization are mostly available for stationary setups. We hope to contribute to the important emerging field of portable data acquisition by presenting open-source Android applications both for the synchronized streaming (Send-a) and recording (Record-a) of multiple sensor data streams. We validate the applications in terms of functionality, flexibility and precision in fully mobile setups and in hybrid setups combining mobile and desktop hardware. Our results show that the fully mobile solution is equivalent to well-established desktop versions. With the streaming application Send-a and the recording application Record-a, purely smartphone-based setups for mobile research and personal health settings can be realized on off-the-shelf Android devices.

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“…This offers new opportunities to learn about the diversity of users, e.g. diverse aspects of students' wellbeing [44]. However, there is a set of limitations and open questions that require future work.…”

Section: Diversity-aware Data Collectionmentioning

confidence: 99%

“…Third, diversity-aware data collection must take into account local habits, which may differ across geographical and cultural regions. Collecting smartphone data requires insights into local practices, as the use of smartphones among young people differ across countries [42,44]. Students may use distinct apps in some countries, or use mobile services differently because of the cost of phone devices and data plans, popular local trends, and culture at large.…”

Section: Diversity-aware Data Collectionmentioning

confidence: 99%

The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations

Schelenz

Bison

Busso

et al. 2021

Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society

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Diversity-aware platform design is a paradigm that responds to the ethical challenges of existing social media platforms. Available platforms have been criticized for minimizing users' autonomy, marginalizing minorities, and exploiting users' data for profit maximization. This paper presents a design solution that centers the well-being of users. It presents the theory and practice of designing a diversity-aware platform for social relations. In this approach, the diversity of users is leveraged in a way that allows like-minded individuals to pursue similar interests or diverse individuals to complement each other in a complex activity. The end users of the envisioned platform are students, who participate in the design process. Diversity-aware platform design involves numerous steps, of which two are highlighted in this paper: 1) defining a framework and operationalizing the "diversity" of students, 2) collecting "diversity" data to build diversity-aware algorithms. The paper further reflects on the ethical challenges encountered during the design of a diversity-aware platform.

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Smartphone Sensing for the Well-Being of Young Adults: A Review

Cited by 21 publications

References 119 publications

One More Bite? Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-Reports

One More Bite? Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-Reports

Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer

The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations

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