Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/44693
Title: Innovative Digital Phenotyping Method to Assess Body Representations in Autistic Adults: A Perspective on Multisensor Evaluation
Authors: MOURAD, Joanna 
DANIELS, Kim 
BOGAERTS, Katleen 
Desseilles, Martin
BONNECHERE, Bruno 
Issue Date: 2024
Publisher: MDPI
Source: Sensors, 24 (20) (Art N° 6523)
Abstract: In this perspective paper, we propose a novel tech-driven method to evaluate body representations (BRs) in autistic individuals. Our goal is to deepen understanding of this complex condition by gaining continuous and real-time insights through digital phenotyping into the behavior of autistic adults. Our innovative method combines cross-sectional and longitudinal data gathering techniques to investigate and identify digital phenotypes related to BRs in autistic adults, diverging from traditional approaches. We incorporate ecological momentary assessment and time series data to capture the dynamic nature of real-life events for these individuals. Statistical techniques, including multivariate regression, time series analysis, and machine learning algorithms, offer a detailed comprehension of the complex elements that influence BRs. Ethical considerations and participant involvement in the development of this method are emphasized, while challenges, such as varying technological adoption rates and usability concerns, are acknowledged. This innovative method not only introduces a novel vision for evaluating BRs but also shows promise in integrating traditional and dynamic assessment approaches, fostering a more supportive atmosphere for autistic individuals during assessments compared to conventional methods.
Notes: Bonnechere, B (corresponding author), Hasselt Univ, Fac Rehabil Sci, REVAL Rehabil Res Ctr, B-3590 Diepenbeek, Belgium.; Bonnechere, B (corresponding author), Hasselt Univ, Data Sci Inst, Technol Supported & Data Driven Rehabil, B-3590 Diepenbeek, Belgium.; Bonnechere, B (corresponding author), PXL Univ Appl Sci & Arts, Dept PXL Healthcare, B-3500 Hasselt, Belgium.
joanna.mourad@uhasselt.be; kim.daniels@pxl.be;
katleen.bogaerts@uhasselt.be; martin.desseilles@unamur.be;
bruno.bonnechere@uhasselt.be
Keywords: body representations;assessment;autistic adults;multisensor;data integration;digital phenotyping
Document URI: http://hdl.handle.net/1942/44693
e-ISSN: 1424-8220
DOI: 10.3390/s24206523
ISI #: 001342280900001
Rights: 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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