COTIDIANA Dataset – Smartphone-Collected Data on the Mobility, Finger Dexterity, and Mental Health of People With Rheumatic and Musculoskeletal Diseases

Rheumatic and Musculoskeletal Diseases (RMDs) are very common and can negatively impact patients' quality of life. The current care of patients with RMDs is episodic, based on a few yearly doctor visits, which may not provide an adequate picture of the patient's condition. Researchers have hypothesized that RMDs could be passively monitored using smartphones or sensors, however, there are no datasets to support this development. We introduce the COTIDIANA Dataset: a holistic, multimodal, multidimensional, and open-access resource that gathers data on mobility and physical activity, finger dexterity, and mental health, key dimensions affected by RMDs. We gathered smartphone and self-reported data from 31 patients and 28 age-matched controls, including inertial sensors, keyboard metrics, communication logs, and reference tests/scales. A preliminary analysis showed the potential for extracted metrics to predict RMD diagnosis and condition characteristics. Our dataset shall enable the community to create mobile and wearable-based solutions for patients with RMDs.

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Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2024-09-09
DOI
https://doi.org/10.1109/jbhi.2024.3456069
Citations
2
Primary Topic
Fibromyalgia and Chronic Fatigue Syndrome Research
Type
article
Field-Weighted Citation Impact
0.77
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article

COTIDIANA Dataset – Smartphone-Collected Data on the Mobility, Finger Dexterity, and Mental Health of People With Rheumatic and Musculoskeletal Diseases

Helga Radner, Ana Rita Henriques, Paul Studenic, Ricardo Graça et al.
2 citations
IEEE Journal of Biomedical and Health Informatics
Fibromyalgia and Chronic Fatigue Syndrome Research
0.77
article

COTIDIANA Dataset – Smartphone-Collected Data on the Mobility, Finger Dexterity, and Mental Health of People With Rheumatic and Musculoskeletal Diseases

Helga Radner, Ana Rita Henriques, Paul Studenic, Ricardo Graça, Ana Maria Rodrigues, Elsa F Mateus, Francisco Nunes, N. Nakhost Lotfi, Pedro Matias, Ricardo Azevedo Araújo, Maria Valada, David Belo
article en
2 citations

Abstract

Rheumatic and Musculoskeletal Diseases (RMDs) are very common and can negatively impact patients' quality of life. The current care of patients with RMDs is episodic, based on a few yearly doctor visits, which may not provide an adequate picture of the patient's condition. Researchers have hypothesized that RMDs could be passively monitored using smartphones or sensors, however, there are no datasets to support this development. We introduce the COTIDIANA Dataset: a holistic, multimodal, multidimensional, and open-access resource that gathers data on mobility and physical activity, finger dexterity, and mental health, key dimensions affected by RMDs. We gathered smartphone and self-reported data from 31 patients and 28 age-matched controls, including inertial sensors, keyboard metrics, communication logs, and reference tests/scales. A preliminary analysis showed the potential for extracted metrics to predict RMD diagnosis and condition characteristics. Our dataset shall enable the community to create mobile and wearable-based solutions for patients with RMDs.

IEEE Journal of Biomedical and Health InformaticsVol. 28(11)
Fraunhofer Portugal Research (PT), Medical University of Vienna (AT), Universidade Nova de Lisboa (PT)
Openalex Percentile: Top 26%
Fibromyalgia and Chronic Fatigue Syndrome Research
0.77
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