Revisiting the MotionWatch8©: Calibrating Cut-Points for Measuring Physical Activity and Sedentary Behavior Among Adults With Stroke

Abstract

Reduced moderate-to-vigorous physical activity (MVPA) and increased sedentary behavior (SB) are common following stroke, which can limit stroke recovery and contribute to greater cognitive decline. Hence, the MVPA and SB of adults with stroke should be measured concurrently using objective methods. One currently available method for objectively measuring MVPA and SB is the MotionWatch8© (MW8). However, adults with stroke can have significant mobility restrictions (depending on stroke severity) and thus it is important to determine separate MVPA and SB cut-points for adults with stroke, as well as validate separate cut-points: (1) when the MW8 is worn on the stroke affected side compared to the non-affected side; and (2) for adults with mild stroke versus adults with moderate-to-severe stroke. In the current study, we concurrently measured MW8 actigraphy (worn on both the stroke affected side and the non-affected side) and indirect calorimetry during 10 different activities of daily living for 43 adults with stroke (aged 55–87 years). Using intra-class correlations (ICC), we first investigated the agreement of the MW8 when placed on the affected side as compared to the non-affected side for: (1) all participants irrespective of stroke severity; (2) participants with mild stroke, classified as a Fugl Meyer motor score of ≥79/100; and (3) participants with moderate-to-severe stroke (i.e., Fugl Meyer < 79/100). We then determined cut-points for all participants—as well as separate cut-points based on stroke severity—on both the stroke affected side and non-affected side for SB and MVPA using receiver operating characteristic curves. The results of our analyses indicate that the agreement in MW8 output between the stroke affected and non-affected sides was moderate across all participants (ICC = 0.67), as well as for each sub-group (mild stroke: ICC = 0.64; moderate-to-severe stroke: ICC = 0.77). Additionally, the results of our cut-point analyses support using different cut-points for different levels of stroke severity and also for the stroke affected side. We determined the following cut-points: (1) for the affected side, adults with mild stroke have cut-points of SB ≤134 counts per minute (CPM) and MVPA ≥704 CPM, while adults with moderate-to-severe stroke have cut-points of SB ≤281 CPM and MVPA ≥468 CPM; and (2) the non-affected side, adults with mild stroke have cut-points of SB ≤162 CPM and MVPA ≥661 CPM, while adults with moderate-to-severe stroke have cut-points of SB ≤281 CPM and MVPA ≥738 CPM. Hence, these data provide a new measure for concurrently examining the dynamic relationships between MVPA and SB among adults with stroke.

Behaviour-based movement cut-off points in 3-year old children comparing wrist- with hip-worn actigraphs MW8 and GT3X

“…Differentiation of sedentary from light activity was much greater in the study by Lin et al (45), given the much lower sedentary threshold score (SED < 32 counts/30s) compared to the present study (SED < 215 counts/30s, MOA < 118 counts/30s). This is likely related to Lin et al (45) prioritizing higher specificity at the cost of lower sensitivity in order to minimise false positives due to arm movements. Johansson et al (12) used the opposite adjustment -towards higher sensitivity at the expense of a lower specificity for the SED threshold in order to avoid underestimating the time spent in SED.…”

“…In Johansson et al (12), authors argued for age-specific thresholds since they found that 4-year-old preschool children, who wore a GT3X triaxial on their non-dominant wrist, produced generally higher intensity thresholds per 5s-epoch in comparison to toddlers of 2 years (19). Differentiation of sedentary from light activity was much greater in the study by Lin et al (45), given the much lower sedentary threshold score (SED < 32 counts/30s) compared to the present study (SED < 215 counts/30s, MOA < 118 counts/30s). This is likely related to Lin et al (45) prioritizing higher specificity at the cost of lower sensitivity in order to minimise false positives due to arm movements.…”

“…There is growing evidence of the influence of ambient light on human physiology and behaviour (43), and therefore, various research-grade data loggers capture not only body movements but also light exposure levels (44). Two of those have been validated for sleep/circadian timing and physical activity in adults and children: MotionWatch 8 (Camntech LTd, UK) and ActiGraph GT3X, both using different algorithms and output modes (45)(46)(47). Since we monitor activity in children under free-living conditions in our prospective, population-based NorthPop birth cohort (motionless/sedentary activities, excluding naps/sleep) across a 24h cycle.…”

OUTSTEP‐HF: randomised controlled trial comparing short‐term effects of sacubitril/valsartan versus enalapril on daily physical activity in patients with chronic heart failure with reduced ejection fraction

“…Accelerometry is a non‐invasive method for monitoring PA. Patients were instructed to wear the accelerometer (MotionWatch8®, Camntech, Cambridge, UK) 19,20 wristband continuously during the study. Assessment of PA was performed during the entire duration of the study (from Week −2 to Week 12) using a continuously wrist‐worn accelerometry device on non‐dominant wrist.…”

Association of Barriers, Fear of Falling and Fatigue with Objectively Measured Physical Activity and Sedentary Behavior in Chronic Stroke

“…Considering that inadequate levels of PA of at least moderate intensity are a significant risk factor for recurrent stroke and that sitting time is an independent risk factor for cardiovascular disease-related mortality [ 9 , 13 ], public health programs and policies in chronic stroke should prevent physical inactivity and SB [ 4 ]. In this sense, to change these behaviors, it is critical to know the modifiable factors associated with them in people with sequelae of chronic stroke [ 8 , 14 ].…”