Assessment and treatment of visuospatial neglect using active learning with Gaussian processes regression

被引:1
作者
De Boi, Ivan [1 ]
Embrechts, Elissa [2 ]
Schatteman, Quirine [2 ]
Penne, Rudi [1 ]
Truijen, Steven [2 ]
Saeys, Wim [2 ]
机构
[1] Univ Antwerp, Fac Appl Engn, Dept Electromech, Res Grp InViLab, Groenenborgerlaan 171, B-2020 Antwerp, Belgium
[2] Univ Antwerp, Dept Rehabil Sci & Physiotherapy REVAKI, Res Grp MOVANT, Univpl 1, B-2610 Antwerp, Belgium
关键词
Visuospatial neglect; Gaussian processes; Active learning; Personalised healthcare; Human-centred AI; COGNITIVE REHABILITATION;
D O I
10.1016/j.artmed.2024.102770
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Visuospatial neglect is a disorder characterised by impaired awareness for visual stimuli located in regions of space and frames of reference. It is often associated with stroke. Patients can struggle with all aspects of daily living and community participation. Assessment methods are limited and show several shortcomings, considering they are mainly performed on paper and do not implement the complexity of daily life. Similarly, treatment options are sparse and often show only small improvements. We present an artificial intelligence solution designed to accurately assess a patient's visuospatial neglect in a three-dimensional setting. We implement an active learning method based on Gaussian process regression to reduce the effort it takes a patient to undergo an assessment. Furthermore, we describe how this model can be utilised in patient oriented treatment and how this opens the way to gamification, tele-rehabilitation and personalised healthcare, providing a promising avenue for improving patient engagement and rehabilitation outcomes. To validate our assessment module, we conducted clinical trials involving patients in a real -world setting. We compared the results obtained using our AI -based assessment with the widely used conventional visuospatial neglect tests currently employed in clinical practice. The validation process serves to establish the accuracy and reliability of our model, confirming its potential as a valuable tool for diagnosing and monitoring visuospatial neglect. Our VR application proves to be more sensitive, while intra-rater reliability remains high.
引用
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页数:9
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