Applying time series analyses on continuous accelerometry data—A clinical example in older adults with and without cognitive impairment

• Published in: PloS one Vol. 16; no. 5; p. e0251544
• Main Authors: Rackoll, Torsten, Neumann, Konrad, Passmann, Sven, Grittner, Ulrike, Külzow, Nadine, Ladenbauer, Julia, Flöel, Agnes
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 13.05.2021; Public Library of Science (PLoS)
• Subjects: Accelerometers; Accelerometry - methods; Activities of daily living; Activity patterns; Age Factors; Aged; Alzheimer's disease; Animal models; Biological rhythms; Biology and Life Sciences; Biometrics; Brain research; Circadian Rhythm; Circadian rhythms; Cognitive ability; Cognitive Dysfunction - diagnosis; Cognitive Dysfunction - epidemiology; Cognitive tasks; Data analysis; Dementia disorders; Demographic aspects; Diagnosis; Diet; Dietary supplements; Engineering and Technology; Epidemiology; Female; Health aspects; Humans; Magnetic resonance imaging; Male; Measurement; Medicine and Health Sciences; Melatonin; Memory; Memory Consolidation; Middle Aged; Neurodegenerative diseases; Neuropsychology; Observational studies; Older people; Pathology; Physical activity; Physical training; Physiological aspects; Psychological aspects; Research and Analysis Methods; Signs and symptoms; Sleep; Social Sciences; Time series; Time-series analysis; Germany
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0251544

Many clinical studies reporting accelerometry data use sum score measures such as percentage of time spent in moderate to vigorous activity which do not provide insight into differences in activity patterns over 24 hours, and thus do not adequately depict circadian activity patterns. Here, we present an improved functional data analysis approach to model activity patterns and circadian rhythms from accelerometer data. As a use case, we demonstrated its application in patients with mild cognitive impairment (MCI) and age-matched healthy older volunteers (HOV). Data of two studies were pooled for this analysis. Following baseline cognitive assessment participants were provided with accelerometers for seven consecutive days. A function on scalar regression (FoSR) approach was used to analyze 24 hours accelerometer data. Information on 48 HOV (mean age 65 SD 6 years) and 18 patients with MCI (mean age 70, SD 8 years) were available for this analysis. MCI patients displayed slightly lower activity in the morning hours (minimum relative activity at 6:05 am: -41.3%, 95% CI -64.7 to -2.5%, p = 0.031) and in the evening (minimum relative activity at 21:40 am: -48.4%, 95% CI -68.5 to 15.4%, p = 0.001) as compared to HOV after adjusting for age and sex. Using a novel approach of FoSR, we found timeframes with lower activity levels in MCI patients compared to HOV which were not evident if sum scores of amount of activity were used, possibly indicating that changes in circadian rhythmicity in neurodegenerative disease are detectable using easy-to-administer accelerometry. Effects of Brain Stimulation During Nocturnal Sleep on Memory Consolidation in Patients With Mild Cognitive Impairments, ClinicalTrial.gov identifier: NCT01782391. Effects of Brain Stimulation During a Daytime Nap on Memory Consolidation in Patients With Mild Cognitive Impairment, ClinicalTrial.gov identifier: NCT01782365.