mQoL Lab: Step-by-step creation of a flexible platform to conduct studies using interactive, mobile, wearable and ubiquitous devices

Research output: Contribution to journalConference articleResearchpeer-review

Standard

mQoL Lab : Step-by-step creation of a flexible platform to conduct studies using interactive, mobile, wearable and ubiquitous devices. / Berrocal, Allan; Manea, Vlad; de Masi, Alexandre; Wac, Katarzyna.

In: Procedia Computer Science, Vol. 175, 2020, p. 221-229.

Research output: Contribution to journalConference articleResearchpeer-review

Harvard

Berrocal, A, Manea, V, de Masi, A & Wac, K 2020, 'mQoL Lab: Step-by-step creation of a flexible platform to conduct studies using interactive, mobile, wearable and ubiquitous devices', Procedia Computer Science, vol. 175, pp. 221-229. https://doi.org/10.1016/j.procs.2020.07.033

APA

Berrocal, A., Manea, V., de Masi, A., & Wac, K. (2020). mQoL Lab: Step-by-step creation of a flexible platform to conduct studies using interactive, mobile, wearable and ubiquitous devices. Procedia Computer Science, 175, 221-229. https://doi.org/10.1016/j.procs.2020.07.033

Vancouver

Berrocal A, Manea V, de Masi A, Wac K. mQoL Lab: Step-by-step creation of a flexible platform to conduct studies using interactive, mobile, wearable and ubiquitous devices. Procedia Computer Science. 2020;175:221-229. https://doi.org/10.1016/j.procs.2020.07.033

Author

Berrocal, Allan ; Manea, Vlad ; de Masi, Alexandre ; Wac, Katarzyna. / mQoL Lab : Step-by-step creation of a flexible platform to conduct studies using interactive, mobile, wearable and ubiquitous devices. In: Procedia Computer Science. 2020 ; Vol. 175. pp. 221-229.

Bibtex

@inproceedings{147f11a70c214abfb7912562fb496f1f,
title = "mQoL Lab: Step-by-step creation of a flexible platform to conduct studies using interactive, mobile, wearable and ubiquitous devices",
abstract = "Human subject studies with mobile users are widely used to understand, and model, human aspects such as behaviours and preferences, in the lab and in the wild. These studies usually employ mixed methods, collecting data by active participation and passive sensing using interactive, mobile, wearable, and ubiquitous devices. Researchers rely on a software platform to design and execute their studies, but existing solutions require a steep learning curve, allow little control, and offer limited guarantees. Our research lab built the mQoL Lab platform using open source technologies, and evolved it to a durable and reliable software ecosystem in over ten mobile subject studies along eight years across three countries. In this paper, we share the acquired experience via tangible artifacts such as requirements, architecture, design, step-by-step support, configuration scripts, and recommendations for researchers to construct a software platform supporting mobile subject studies. The paper is especially relevant for researchers embracing short-term to longitudinal, observational or intervention-based studies, leveraging mixed methods, including multiple devices, and tens to hundreds of simultaneous participants.",
keywords = "Data collection, Mixed methods, Mobile interaction, Mobile platform, Mobile studies, Passive sensing, Wearable devices",
author = "Allan Berrocal and Vlad Manea and {de Masi}, Alexandre and Katarzyna Wac",
year = "2020",
doi = "10.1016/j.procs.2020.07.033",
language = "English",
volume = "175",
pages = "221--229",
journal = "Procedia Computer Science",
issn = "1877-0509",
publisher = "Elsevier",
note = "null ; Conference date: 09-08-2020 Through 12-08-2020",

}

RIS

TY - GEN

T1 - mQoL Lab

AU - Berrocal, Allan

AU - Manea, Vlad

AU - de Masi, Alexandre

AU - Wac, Katarzyna

PY - 2020

Y1 - 2020

N2 - Human subject studies with mobile users are widely used to understand, and model, human aspects such as behaviours and preferences, in the lab and in the wild. These studies usually employ mixed methods, collecting data by active participation and passive sensing using interactive, mobile, wearable, and ubiquitous devices. Researchers rely on a software platform to design and execute their studies, but existing solutions require a steep learning curve, allow little control, and offer limited guarantees. Our research lab built the mQoL Lab platform using open source technologies, and evolved it to a durable and reliable software ecosystem in over ten mobile subject studies along eight years across three countries. In this paper, we share the acquired experience via tangible artifacts such as requirements, architecture, design, step-by-step support, configuration scripts, and recommendations for researchers to construct a software platform supporting mobile subject studies. The paper is especially relevant for researchers embracing short-term to longitudinal, observational or intervention-based studies, leveraging mixed methods, including multiple devices, and tens to hundreds of simultaneous participants.

AB - Human subject studies with mobile users are widely used to understand, and model, human aspects such as behaviours and preferences, in the lab and in the wild. These studies usually employ mixed methods, collecting data by active participation and passive sensing using interactive, mobile, wearable, and ubiquitous devices. Researchers rely on a software platform to design and execute their studies, but existing solutions require a steep learning curve, allow little control, and offer limited guarantees. Our research lab built the mQoL Lab platform using open source technologies, and evolved it to a durable and reliable software ecosystem in over ten mobile subject studies along eight years across three countries. In this paper, we share the acquired experience via tangible artifacts such as requirements, architecture, design, step-by-step support, configuration scripts, and recommendations for researchers to construct a software platform supporting mobile subject studies. The paper is especially relevant for researchers embracing short-term to longitudinal, observational or intervention-based studies, leveraging mixed methods, including multiple devices, and tens to hundreds of simultaneous participants.

KW - Data collection

KW - Mixed methods

KW - Mobile interaction

KW - Mobile platform

KW - Mobile studies

KW - Passive sensing

KW - Wearable devices

UR - https://www.mendeley.com/catalogue/d3af96b7-b4e5-3a8d-8436-4feb45e23ce4/

UR - https://www.mendeley.com/catalogue/d3af96b7-b4e5-3a8d-8436-4feb45e23ce4/

U2 - 10.1016/j.procs.2020.07.033

DO - 10.1016/j.procs.2020.07.033

M3 - Conference article

VL - 175

SP - 221

EP - 229

JO - Procedia Computer Science

JF - Procedia Computer Science

SN - 1877-0509

Y2 - 9 August 2020 through 12 August 2020

ER -

ID: 255886404