Similarity matrix-based anomaly detection for clinical intervention

The use of digital phenotyping methods in clinical care has allowed for improved investigation of spatiotemporal behaviors of patients. Moreover, detecting abnormalities in mobile sensor data patterns can be instrumental in identifying potential changes in symptomology. We propose a method that temp...

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Bibliographic Details
Published in:Scientific reports 2022-06, Vol.12 (1), p.9162-9162, Article 9162
Main Authors: D’Mello, Ryan, Melcher, Jennifer, Torous, John
Format: Article
Language:English
Subjects:
692/53/2423
692/699/476
Accelerometers
Anxiety
Data collection
Humanities and Social Sciences
Mental depression
Methods
multidisciplinary
Patients
Phenotyping
Science
Science (multidisciplinary)
Sensors
Similarity measures
Smartphones
Time series
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Summary:The use of digital phenotyping methods in clinical care has allowed for improved investigation of spatiotemporal behaviors of patients. Moreover, detecting abnormalities in mobile sensor data patterns can be instrumental in identifying potential changes in symptomology. We propose a method that temporally aligns sensor data in order to achieve interpretable measures of similarity between time points. These computed measures can then be used for anomaly detection, baseline routine computation, and trajectory clustering. In addition, we apply this method on a study of 695 college participants, as well as on a patient with worsening anxiety and depression. With varying temporal constraints, we find mild correlations between changes in routine and clinical scores. Furthermore, in our experiment on an individual with elevated depression and anxiety, we are able to cluster GPS trajectories, allowing for improved understanding and visualization of routines with respect to symptomology. In the future, we aim to apply this method on individuals that undergo data collection for longer periods of time, thus allowing for a better understanding of long-term routines and signals for clinical intervention.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-022-12792-3