التفاصيل البيبلوغرافية
| العنوان: |
Identification of Fatigue and Sleepiness in Immune and Neurodegenerative Disorders from Measures of Real-World Gait Variability. |
| المؤلفون: |
Hinchliffe C, Rehman RZU, Branco D, Jackson D, Ahmaniemi T, Guerreiro T, Chatterjee M, Manyakov NV, Pandis I, Davies K, Macrae V, Aufenberg S, Paulides E, Hildesheim H, Kudelka J, Emmert K, Van Gassen G, Rochester L, van der Woude CJ, Reilmann R, Maetzler W, Ng WF, Del Din S |
| المصدر: |
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2023 Jul; Vol. 2023, pp. 1-4. |
| نوع المنشور: |
Clinical Study; Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: [IEEE] Country of Publication: United States NLM ID: 101763872 Publication Model: Print Cited Medium: Internet ISSN: 2694-0604 (Electronic) Linking ISSN: 23757477 NLM ISO Abbreviation: Annu Int Conf IEEE Eng Med Biol Soc Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: [Piscataway, NJ] : [IEEE], [2007]- |
| مواضيع طبية MeSH: |
Disorders of Excessive Somnolence*/diagnosis , Disorders of Excessive Somnolence*/etiology , Disorders of Excessive Somnolence*/physiopathology , Fatigue*/diagnosis , Fatigue*/etiology , Fatigue*/physiopathology , Gait*/physiology , Immune System Diseases*/complications , Immune System Diseases*/physiopathology , Neurodegenerative Diseases*/complications , Neurodegenerative Diseases*/physiopathology , Sleepiness*/physiology, Humans |
| مستخلص: |
Current assessments of fatigue and sleepiness rely on patient reported outcomes (PROs), which are subjective and prone to recall bias. The current study investigated the use of gait variability in the "real world" to identify patient fatigue and daytime sleepiness. Inertial measurement units were worn on the lower backs of 159 participants (117 with six different immune and neurodegenerative disorders and 42 healthy controls) for up to 20 days, whom completed regular PROs. To address walking bouts that were short and sparse, four feature groups were considered: sequence-independent variability (SIV), sequence-dependant variability (SDV), padded SDV (PSDV), and typical gait variability (TGV) measures. These gait variability measures were extracted from step, stride, stance, and swing time, step length, and step velocity. These different approaches were compared using correlations and four machine learning classifiers to separate low/high fatigue and sleepiness.Most balanced accuracies were above 50%, the highest was 57.04% from TGV measures. The strongest correlation was 0.262 from an SDV feature against sleepiness. Overall, TGV measures had lower correlations and classification accuracies.Identifying fatigue or sleepiness from gait variability is extremely complex and requires more investigation with a larger data set, but these measures have shown performances that could contribute to a larger feature set.Clinical relevance- Gait variability has been repeatedly used to assess fatigue in the lab. The current study, however, explores gait variability for fatigue and daytime sleepiness in real-world scenarios with multiple gait-impacted disorders. |
| تواريخ الأحداث: |
Date Created: 20231212 Date Completed: 20240204 Latest Revision: 20240327 |
| رمز التحديث: |
20240327 |
| DOI: |
10.1109/EMBC40787.2023.10339956 |
| PMID: |
38083383 |
| قاعدة البيانات: |
MEDLINE |
Full Text Finder