Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome
Abstract Background Chronic Fatigue Syndrome patients suffer from symptoms that cannot be explained by a single underlying biological cause. It is sometimes claimed that these symptoms are a manifestation of a disrupted autonomic nervous system. Prior works studying this claim from the complex adapt...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2024-04-01
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| Series: | BioPsychoSocial Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13030-024-00305-9 |
| _version_ | 1797219754857988096 |
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| author | Paloma Rabaey Peter Decat Stefan Heytens Dirk Vogelaers An Mariman Thomas Demeester |
| author_facet | Paloma Rabaey Peter Decat Stefan Heytens Dirk Vogelaers An Mariman Thomas Demeester |
| author_sort | Paloma Rabaey |
| collection | DOAJ |
| description | Abstract Background Chronic Fatigue Syndrome patients suffer from symptoms that cannot be explained by a single underlying biological cause. It is sometimes claimed that these symptoms are a manifestation of a disrupted autonomic nervous system. Prior works studying this claim from the complex adaptive systems perspective, have observed a lower average complexity of physical activity patterns in chronic fatigue syndrome patients compared to healthy controls. To further study the robustness of such methods, we investigate the within-patient changes in complexity of activity over time. Furthermore, we explore how these changes might be related to changes in patient functioning. Methods We propose an extension of the allometric aggregation method, which characterises the complexity of a physiological signal by quantifying the evolution of its fractal dimension. We use it to investigate the temporal variations in within-patient complexity. To this end, physical activity patterns of 7 patients diagnosed with chronic fatigue syndrome were recorded over a period of 3 weeks. These recordings are accompanied by physicians’ judgements in terms of the patients’ weekly functioning. Results We report significant within-patient variations in complexity over time. The obtained metrics are shown to depend on the range of timescales for which these are evaluated. We were unable to establish a consistent link between complexity and functioning on a week-by-week basis for the majority of the patients. Conclusions The considerable within-patient variations of the fractal dimension across scales and time force us to question the utility of previous studies that characterise long-term activity signals using a single static complexity metric. The complexity of a Chronic Fatigue Syndrome patient’s physical activity signal does not suffice to characterise their high-level functioning over time and has limited potential as an objective monitoring metric by itself. |
| first_indexed | 2024-04-24T12:38:41Z |
| format | Article |
| id | doaj.art-b5f2123328774b8fa6d7ac5330b3057f |
| institution | Directory Open Access Journal |
| issn | 1751-0759 |
| language | English |
| last_indexed | 2024-04-24T12:38:41Z |
| publishDate | 2024-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BioPsychoSocial Medicine |
| spelling | doaj.art-b5f2123328774b8fa6d7ac5330b3057f2024-04-07T11:22:42ZengBMCBioPsychoSocial Medicine1751-07592024-04-0118112110.1186/s13030-024-00305-9Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue SyndromePaloma Rabaey0Peter Decat1Stefan Heytens2Dirk Vogelaers3An Mariman4Thomas Demeester5IDLab, Department of Information Technology, Ghent University - imecDepartment of Public Health and Primary Care, Ghent UniversityDepartment of Public Health and Primary Care, Ghent UniversityCenter of Integrative Medicine, Department of Physical Medicine and Rehabilitation, University Hospital GhentCenter of Integrative Medicine, Department of Physical Medicine and Rehabilitation, University Hospital GhentIDLab, Department of Information Technology, Ghent University - imecAbstract Background Chronic Fatigue Syndrome patients suffer from symptoms that cannot be explained by a single underlying biological cause. It is sometimes claimed that these symptoms are a manifestation of a disrupted autonomic nervous system. Prior works studying this claim from the complex adaptive systems perspective, have observed a lower average complexity of physical activity patterns in chronic fatigue syndrome patients compared to healthy controls. To further study the robustness of such methods, we investigate the within-patient changes in complexity of activity over time. Furthermore, we explore how these changes might be related to changes in patient functioning. Methods We propose an extension of the allometric aggregation method, which characterises the complexity of a physiological signal by quantifying the evolution of its fractal dimension. We use it to investigate the temporal variations in within-patient complexity. To this end, physical activity patterns of 7 patients diagnosed with chronic fatigue syndrome were recorded over a period of 3 weeks. These recordings are accompanied by physicians’ judgements in terms of the patients’ weekly functioning. Results We report significant within-patient variations in complexity over time. The obtained metrics are shown to depend on the range of timescales for which these are evaluated. We were unable to establish a consistent link between complexity and functioning on a week-by-week basis for the majority of the patients. Conclusions The considerable within-patient variations of the fractal dimension across scales and time force us to question the utility of previous studies that characterise long-term activity signals using a single static complexity metric. The complexity of a Chronic Fatigue Syndrome patient’s physical activity signal does not suffice to characterise their high-level functioning over time and has limited potential as an objective monitoring metric by itself.https://doi.org/10.1186/s13030-024-00305-9Chronic Fatigue SyndromeComplex adaptive systemsActivity patternsTime-dependent complexityFractal dimensionPersonalised monitoring |
| spellingShingle | Paloma Rabaey Peter Decat Stefan Heytens Dirk Vogelaers An Mariman Thomas Demeester Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome BioPsychoSocial Medicine Chronic Fatigue Syndrome Complex adaptive systems Activity patterns Time-dependent complexity Fractal dimension Personalised monitoring |
| title | Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome |
| title_full | Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome |
| title_fullStr | Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome |
| title_full_unstemmed | Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome |
| title_short | Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome |
| title_sort | time dependent complexity characterisation of activity patterns in patients with chronic fatigue syndrome |
| topic | Chronic Fatigue Syndrome Complex adaptive systems Activity patterns Time-dependent complexity Fractal dimension Personalised monitoring |
| url | https://doi.org/10.1186/s13030-024-00305-9 |
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