Analysis of free-living daytime movement in patients with migraine with access to acute treatment

The Journal of Headache and Pain, Journal Year: 2025, Volume and Issue: 26(1)

Published: Feb. 13, 2025

Motion can exacerbate headache during a migraine attack, potentially leading to avoidance of routine physical activity. Advances in wrist-worn actigraphy facilitate objectively analyzing how episodes affect activity everyday settings. The primary hypothesis was hypoactivity daytime events. Secondary hypotheses are the prodromal and postdromal hours closest event. During 90-day prospective observational study, participants diagnosed with wore an device on their non-dominant wrist daily life work, while also logging migraine-related data dedicated smartphone application. There were no restrictions use acute preventive treatments. Data from accelerometer used (i) calculate energy expenditure, (ii) predict types human activities. These metrics compare prodromal, ictal, phases events time-matched intervals non-headache periods. A significant reduction observed ictal phase attacks, as evidenced by decreases both expenditure recognition prediction metrics. movement evening (18:00–24:00) days. However, changes noted phases. Reduced more pronounced when treatments ineffective. This study is first examine impact levels assessing activities individuals migraine, within habitual environments without medication use. Our findings confirm reduced supporting hypothesis. Wrist-worn further indicated that this patients experience sensitivity. Evening Furthermore, attacks ineffective treatment or moderate-to-high intensity associated reductions movement. In contrast, our did not support secondary would decrease NCT04983186 ( www.ClinicalTrials.gov ).

Language: Английский

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Patients with chronic cluster headache may show reduced activity energy expenditure on ambulatory wrist actigraphy recordings during daytime attacks

Brain and Behavior, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 1, 2024

Abstract Objective To investigate the changes in activity energy expenditure (AEE) throughout daytime cluster headache (CH) attacks patients with chronic CH and to evaluate usefulness of actigraphy as a digital biomarker attacks. Background is primary disorder characterized by severe very unilateral pain (orbital, supraorbital, temporal, or any combination these sites), ipsilateral cranial autonomic symptoms and/or sense restlessness agitation. We hypothesized increased AEE from hyperactivity during measured actigraphy. Methods An observational study including was conducted. During 21 days, wore an device on nondominant wrist recorded attack‐related data dedicated smartphone application. Accelerometer were used for calculation before that occurred ambulatory settings, without restrictions acute preventive treatment. compared movements pre‐ictal, ictal, postictal phases wrist‐worn time‐concordant intervals non‐headache periods. Results Four provided 34 attacks, which 15 met eligibility criteria further analysis. In contrast initial hypothesis decrease movement observed pre‐ictal phase (30 min onset onset) phase. A significant ( p < .01) proportion high‐intensity majority oxygen‐treated, observed. This trend less present low‐intensity movements. Conclusion The unexpected under treatment settings has important implications future research CH.

Language: Английский

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Mitigating data quality challenges in ambulatory wrist-worn wearable monitoring through analytical and practical approaches

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: July 30, 2024

Abstract Chronic disease management and follow-up are vital for realizing sustained patient well-being optimal health outcomes. Recent advancements in wearable technologies, particularly wrist-worn devices, offer promising solutions longitudinal monitoring, replacing subjective, intermittent self-reporting with objective, continuous monitoring. However, collecting analyzing data from wearables presents several challenges, such as entry errors, non-wear periods, missing data, artifacts. In this work, we explore these analysis challenges using two real-world datasets (mBrain21 ETRI lifelog2020). We introduce practical countermeasures, including participant compliance visualizations, interaction-triggered questionnaires to assess personal bias, an optimized pipeline detecting periods. Additionally, propose a visualization-oriented approach validate processing pipelines scalable tools tsflex Plotly-Resampler. Lastly, present bootstrapping methodology evaluate the variability of wearable-derived features presence partially segments. Prioritizing transparency reproducibility, provide open access our detailed code examples, facilitating adaptation future research. conclusion, contributions actionable approaches improving collection analysis.

Language: Английский

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Detecting the fractal physical activity pattern in aged adults with cerebral small vessel disease

Frontiers in Aging Neuroscience, Journal Year: 2025, Volume and Issue: 17

Published: April 28, 2025

Actigraphy is widely used to detect a decline in physical activity aged individuals with cerebral small vessel disease (cSVD). Disturbed fractal has been reported adults Alzheimer's (AD), mild cognitive impairment (MCI), and other neuropsychiatric disorders. To analyze the pattern elderly patients cSVD. From May 2021 August 2023, 55 cSVD 60-80 years admitted seventh medical center of PLA General Hospital were included. The presence lacunes, white matter hyperintensities, microbleeds, perivascular spaces on magnetic resonance images (MRI) rated independently. Furthermore, these MRI markers summed score 0-4, representing all features combined. Detrended fluctuation analysis (DFA) was evaluate fluctuations at multiple time scales. relationship between sleep quality analyzed partial Pearson correlation analysis. Individuals low severity burden showed significant tendency toward random relative those higher burden. Similar results obtained when comparing lacune positive negative groups. In cSVD, disturbance associated an average level not quality. These findings demonstrate obvious complexity

Language: Английский

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