Classification of Free-Living Body Posture with ECG Patch Accelerometers: Application to the Multicenter AIDS Cohort Study.

Purpose: As health studies increasingly monitor free-living heart performance via ECG patches with accelerometers, researchers will seek to investigate cardio-electrical responses to physical activity and sedentary behavior, increasing demand for fast, scalable methods to process accelerometer data. We extend a posture classification algorithm for accelerometers in ECG patches when researchers do not have ground-truth labels or other reference measurements (i.e., upright measurement). Methods: Men living with and without HIV in the Multicenter AIDS Cohort study wore the Zio XT® for up to two weeks (n = 1,250). Our novel extensions for posture classification include (1) estimation of an upright posture for each individual without a reference upright measurement; (2) correction of the upright estimate for device removal and re-positioning using novel spherical change-point detection; and (3) classification of upright and recumbent periods using a clustering and voting process rather than a simple inclination threshold used in other algorithms. As no posture labels exist in the free-living environment, we perform numerous sensitivity analyses and evaluate the algorithm against labelled data from the Towson Accelerometer Study, where participants wore accelerometers at the waist. Results: On average, 87.1% of participants were recumbent at 4am and 15.5% were recumbent at 1pm. Participants were recumbent 54 minutes longer on weekends compared to weekdays. Performance was good in comparison to labelled data in a separate, controlled setting (accuracy = 96.0%, sensitivity = 97.5%, specificity = 95.9%). Conclusions: Posture may be classified in the free-living environment from accelerometers in ECG patches even without measuring a standard upright position. Furthermore, algorithms that fail to account for individuals who rotate and re-attach the accelerometer may fail in the free-living environment.

Relationship between skeletal mitochondrial function and digital markers of free-living physical activity in older adults.

This study examined the association between in vivo skeletal mitochondrial function and digital free-living physical activity patterns-a measure that summarizes biological, phenotypic, functional, and environmental effects on mobility. Among 459 participants (mean age 68 years; 55% women) in the Baltimore Longitudinal Study of Aging, mitochondrial function was quantified as skeletal muscle oxidative capacity via post-exercise phosphocreatine recovery rate (τPCr) in the vastus lateralis muscle of the left thigh, using 31P magnetic resonance spectroscopy. Accelerometry was collected using a 7-day, 24-h wrist-worn protocol and summarized into activity amount, intensity, endurance, and accumulation patterning metrics. Linear regression, two-part linear and logistic (bout analyses), and linear mixed effects models (time-of-day analyses) were used to estimate associations between τPCr and each physical activity metric. Interactions by age, sex, and gait speed were tested. After covariate adjustment, higher τPCr (or poorer mitochondrial function) was associated with lower activity counts/day (ß = - 6593.7, SE = 2406.0; p = 0.006) and activity intensity (- 81.5 counts, SE = 12.9; p < 0.001). For activity intensity, the magnitude of association was greater for men and those with slower gait speed (interaction p < 0.02 for both). Conversely, τPCr was not associated with daily active minutes/day (p = 0.15), activity fragmentation (p = 0.13), or endurance at any bout length (p > 0.05 for all). Time-of-day analyses show participants with high τPCr were less active from 6:00 a.m. to 12:00 a.m. than those with low τPCr. Results indicate that poorer skeletal mitochondrial function is primarily associated with lower engagement in high intensity activities. Our findings help define the connection between laboratory-measured mitochondrial function and real-world physical activity behavior.

Musculoskeletal Pain Characteristics and Objectively Measured Physical Activity in Older Adults.

BACKGROUND: Pain is associated with reports of restricted physical activity (PA), yet the association between musculoskeletal pain characteristics and objectively measured PA quantities and patterns in late life is not well understood. METHODS: A total of 553 adults (mean age 75.8 ±â€…8.4 years, 54.4% women) in the Baltimore Longitudinal Study of Aging (BLSA) completed a health interview and subsequent 7-day wrist-worn ActiGraph assessment in the free-living environment between 2015 and 2020. Pain characteristics, including pain presence in 6x sites (ie, shoulders, hands/wrists, low back, hip, knees, and feet), pain laterality in each site, and pain distribution were assessed. PA metrics were summarized into total daily activity counts (TAC), activity fragmentation, active minutes/day, and diurnal patterns of activity. Linear regression models and mixed-effects models examined the association between pain characteristics and PA outcomes, adjusted for demographics and comorbidities. RESULTS: Unilateral knee pain was associated with 184 070 fewer TAC (p = .039) and 36.2 fewer active minutes/day (p = .032) compared to those without knee pain. Older adults with shoulder pain or hand/wrist pain had more active minutes compared to those without pain (p < .05 for all). For diurnal patterns of activity, participants with knee pain had fewer activity counts during the afternoon (12:00 pm to 5:59 pm). Analyses stratified by sex showed that these associations were only significant among women. CONCLUSIONS: Our study highlights the importance of assessing pain laterality in addition to pain presence and suggests that pain interferes with multiple aspects of daily activity. Longitudinal studies are needed to assess the temporality of these findings.

Validation of a Zio XT Patch Accelerometer for the Objective Assessment of Physical Activity in the Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: Combination devices to monitor heart rate/rhythms and physical activity are becoming increasingly popular in research and clinical settings. The Zio XT Patch (iRhythm Technologies, San Francisco, CA, USA) is US Food and Drug Administration (FDA)-approved for monitoring heart rhythms, but the validity of its accelerometer for assessing physical activity is unknown. OBJECTIVE: To validate the accelerometer in the Zio XT Patch for measuring physical activity against the widely-used ActiGraph GT3X. METHODS: The Zio XT and ActiGraph wGT3X-BT (Actigraph, Pensacola, FL, USA) were worn simultaneously in two separately-funded ancillary studies to Visit 6 of the Atherosclerosis Risk in Communities (ARIC) Study (2016-2017). Zio XT was worn on the chest and ActiGraph was worn on the hip. Raw accelerometer data were summarized using mean absolute deviation (MAD) for six different epoch lengths (1-min, 5-min, 10-min, 30-min, 1-h, and 2-h). Participants who had ≥3 days of at least 10 h of valid data between 7 a.m-11 p.m were included. Agreement of epoch-level MAD between the two devices was evaluated using correlation and mean squared error (MSE). RESULTS: Among 257 participants (average age: 78.5 ± 4.7 years; 59.1% female), there were strong correlations between MAD values from Zio XT and ActiGraph (average r: 1-min: 0.66, 5-min: 0.90, 10-min: 0.93, 30-min: 0.93, 1-h: 0.89, 2-h: 0.82), with relatively low error values (Average MSE × 106: 1-min: 349.37 g, 5-min: 86.25 g, 10-min: 56.80 g, 30-min: 45.46 g, 1-h: 52.56 g, 2-h: 54.58 g). CONCLUSIONS: These findings suggest that Zio XT accelerometry is valid for measuring duration, frequency, and intensity of physical activity within time epochs of 5-min to 2-h.