OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD
Abstract Mental health is vital to human well-being, and prevention strategies to address mental illness have a significant impact on the burden of disease and quality of life. With the recent developments in body-worn sensors, it is now possible to continuously collect data that can be used to gain...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04384-3 |
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| author | Enrique Garcia-Ceja Andrea Stautland Michael A. Riegler Pål Halvorsen Salvador Hinojosa Gilberto Ochoa-Ruiz Jan O. Berle Wenche Førland Kristin Mjeldheim Ketil Joachim Oedegaard Petter Jakobsen |
| author_facet | Enrique Garcia-Ceja Andrea Stautland Michael A. Riegler Pål Halvorsen Salvador Hinojosa Gilberto Ochoa-Ruiz Jan O. Berle Wenche Førland Kristin Mjeldheim Ketil Joachim Oedegaard Petter Jakobsen |
| author_sort | Enrique Garcia-Ceja |
| collection | DOAJ |
| description | Abstract Mental health is vital to human well-being, and prevention strategies to address mental illness have a significant impact on the burden of disease and quality of life. With the recent developments in body-worn sensors, it is now possible to continuously collect data that can be used to gain insights into mental health states. This has the potential to optimize psychiatric assessment, thereby improving patient experiences and quality of life. However, access to high-quality medical data for research purposes is limited, especially regarding diagnosed psychiatric patients. To this extent, we present the OBF-Psychiatric dataset which comprises motor activity recordings of patients with bipolar and unipolar major depression, schizophrenia, and ADHD (attention deficit hyperactivity disorder). The dataset also contains data from a clinical sample diagnosed with various mood and anxiety disorders, as well as a healthy control group, making it suitable for building machine learning models and other analytical tools. It contains recordings from 162 individuals totalling 1565 days worth of motor activity data with a mean of 9.6 days per individual. |
| format | Article |
| id | doaj-art-d697c3c56de749adb7627b9ac3882d2f |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-d697c3c56de749adb7627b9ac3882d2f2025-01-12T12:07:43ZengNature PortfolioScientific Data2052-44632025-01-011211910.1038/s41597-025-04384-3OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHDEnrique Garcia-Ceja0Andrea Stautland1Michael A. Riegler2Pål Halvorsen3Salvador Hinojosa4Gilberto Ochoa-Ruiz5Jan O. Berle6Wenche Førland7Kristin Mjeldheim8Ketil Joachim Oedegaard9Petter Jakobsen10Tecnologico de Monterrey, School of Engineering and SciencesUniversity of Bergen, Department of Clinical MedicineSimulaMet, Holistic SystemsSimulaMet, Holistic SystemsTecnologico de Monterrey, School of Engineering and SciencesTecnologico de Monterrey, School of Engineering and SciencesIndependent ResearcherIndependent ResearcherIndependent ResearcherUniversity of Bergen, Department of Clinical MedicineUniversity of Bergen, Department of Clinical MedicineAbstract Mental health is vital to human well-being, and prevention strategies to address mental illness have a significant impact on the burden of disease and quality of life. With the recent developments in body-worn sensors, it is now possible to continuously collect data that can be used to gain insights into mental health states. This has the potential to optimize psychiatric assessment, thereby improving patient experiences and quality of life. However, access to high-quality medical data for research purposes is limited, especially regarding diagnosed psychiatric patients. To this extent, we present the OBF-Psychiatric dataset which comprises motor activity recordings of patients with bipolar and unipolar major depression, schizophrenia, and ADHD (attention deficit hyperactivity disorder). The dataset also contains data from a clinical sample diagnosed with various mood and anxiety disorders, as well as a healthy control group, making it suitable for building machine learning models and other analytical tools. It contains recordings from 162 individuals totalling 1565 days worth of motor activity data with a mean of 9.6 days per individual.https://doi.org/10.1038/s41597-025-04384-3 |
| spellingShingle | Enrique Garcia-Ceja Andrea Stautland Michael A. Riegler Pål Halvorsen Salvador Hinojosa Gilberto Ochoa-Ruiz Jan O. Berle Wenche Førland Kristin Mjeldheim Ketil Joachim Oedegaard Petter Jakobsen OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD Scientific Data |
| title | OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD |
| title_full | OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD |
| title_fullStr | OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD |
| title_full_unstemmed | OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD |
| title_short | OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD |
| title_sort | obf psychiatric a motor activity dataset of patients diagnosed with major depression schizophrenia and adhd |
| url | https://doi.org/10.1038/s41597-025-04384-3 |
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