Purpose: To analyze the differences in the force–velocity (F–v) profile assessed under unconstrained (ie, using free weights) and constrained (ie, on a Smith machine) vertical jumps, as well as to determine the between-day reliability. Methods: A total of 23 trained participants (18  y) performed an incremental load squat jump test (with ∼35%, 45%, 60%, and 70% of the subjects’ body mass) on 2 different days using free weights and a Smith machine. Nine of these participants repeated the tests on 2 other days for an exploratory analysis of between-day reliability. F–v variables (ie, maximum theoretical force [F 0], velocity [v 0], and power, and the imbalance between the actual and the theoretically optimal F–v profile) were computed from jump height. Results: A poor agreement was observed between the F–v variables assessed under constrained and unconstrained conditions (intraclass correlation coefficient [ICC] < .50 for all). The height attained during each single jump performed under both constrained and unconstrained conditions showed an acceptable reliability (coefficient of variation < 10%, ICC > .70). The F–v variables computed under constrained conditions showed an overall good agreement (ICC = .75–.95 for all variables) and no significant differences between days (P > .05), but a high variability for v 0, the imbalance between the actual and the theoretically optimal F–v profile, and maximal theoretical power (coefficient of variation = 17.0%–27.4%). No between-day differences were observed for any F–v variable assessed under unconstrained conditions (P > .05), but all of the variables presented a low between-day reliability (coefficient of variation > 10% and ICC < .70 for all). Conclusions: F–v variables differed meaningfully when obtained from constrained and unconstrained loaded jumps, and most importantly seemed to present a low between-day reliability.
Pedro L. Valenzuela, Guillermo Sánchez-Martínez, Elaia Torrontegi, Javier Vázquez-Carrión, Zigor Montalvo, and G. Gregory Haff
Scott J. Strath, Taylor W. Rowley, Chi C. Cho, Allison Hyngstrom, Ann M. Swartz, Kevin G. Keenan, Julian Martinez, and John W. Staudenmayer
Purpose: To compare the accuracy and precision of a hip-worn accelerometer to predict energy cost during structured activities across motor performance and disease conditions. Methods: 118 adults self-identifying as healthy (n = 44) and those with arthritis (n = 23), multiple sclerosis (n = 18), Parkinson’s disease (n = 17), and stroke (n = 18) underwent measures of motor performance and were categorized into groups: Group 1, usual; Group 2, moderate impairment; and Group 3, severe impairment. The participants completed structured activities while wearing an accelerometer and a portable metabolic measurement system. Accelerometer-predicted energy cost (metabolic equivalent of tasks [METs]) were compared with measured METs and evaluated across functional impairment and disease conditions. Statistical significance was assessed using linear mixed effect models and Bayesian information criteria to assess model fit. Results: All activities’ accelerometer counts per minute (CPM) were 29.5–72.6% less for those with disease compared with those who were healthy. The predicted MET bias was similar across disease, −0.49 (−0.71, −0.27) for arthritis, −0.38 (−0.53, −0.22) for healthy, −0.44 (−0.68, −0.20) for MS, −0.34 (−0.58, −0.09) for Parkinson’s, and −0.30 (−0.54, −0.06) for stroke. For functional impairment, there was a graded reduction in CPM for all activities: Group 1, 1,215 CPM (1,129, 1,301); Group 2, 789 CPM (695, 884); and Group 3, 343 CPM (220, 466). The predicted MET bias revealed similar results across the Group 1, −0.37 METs (−0.52, −0.23); Group 2, −0.44 METs (−0.60, −0.28); and Group 3, −0.33 METs (−0.55, −0.13). The Bayesian information criteria showed a better model fit for functional impairment compared with disease condition. Conclusion: Using functionality to improve accelerometer calibration could decrease variability and warrants further exploration to improve accelerometer prediction of physical activity.
Supun Nakandala, Marta M. Jankowska, Fatima Tuz-Zahra, John Bellettiere, Jordan A. Carlson, Andrea Z. LaCroix, Sheri J. Hartman, Dori E. Rosenberg, Jingjing Zou, Arun Kumar, and Loki Natarajan
Background: Machine learning has been used for classification of physical behavior bouts from hip-worn accelerometers; however, this research has been limited due to the challenges of directly observing and coding human behavior “in the wild.” Deep learning algorithms, such as convolutional neural networks (CNNs), may offer better representation of data than other machine learning algorithms without the need for engineered features and may be better suited to dealing with free-living data. The purpose of this study was to develop a modeling pipeline for evaluation of a CNN model on a free-living data set and compare CNN inputs and results with the commonly used machine learning random forest and logistic regression algorithms. Method: Twenty-eight free-living women wore an ActiGraph GT3X+ accelerometer on their right hip for 7 days. A concurrently worn thigh-mounted activPAL device captured ground truth activity labels. The authors evaluated logistic regression, random forest, and CNN models for classifying sitting, standing, and stepping bouts. The authors also assessed the benefit of performing feature engineering for this task. Results: The CNN classifier performed best (average balanced accuracy for bout classification of sitting, standing, and stepping was 84%) compared with the other methods (56% for logistic regression and 76% for random forest), even without performing any feature engineering. Conclusion: Using the recent advancements in deep neural networks, the authors showed that a CNN model can outperform other methods even without feature engineering. This has important implications for both the model’s ability to deal with the complexity of free-living data and its potential transferability to new populations.
Stacey Alvarez-Alvarado and Gershon Tenenbaum
Inquiry of the psychological states during the exercise experience failed to fully account for the role of motivation to adhere and the disposition of exertion tolerance (ET). The current study expands the scope of the integrated cognitive–perceptual–affective framework by measuring the motivation to sustain effort in two physical tasks and accounting for ET. Thirty male participants performed cycling and isometric handgrip tasks to assess the progression of the rating of perceived exertion, attentional focus, affective responses, and motivation to adhere, along with an incremental workload. The ET was determined by a handgrip task time to voluntary exhaustion. The findings indicated significant time effects and linear trends for perceived exertion, attentional focus, affect, and perceived arousal but not motivation to adhere during the handgrip and cycling tasks. The ET played a key role in the integrity of the model, particularly in perceptual, attentional, and affective responses. The intended model serves to stimulate new research into adaptation mechanisms.
Bronwyn Clark, Elisabeth Winker, Matthew Ahmadi, and Stewart Trost
Accurate measurement of time spent sitting, standing, and stepping is important in studies seeking to evaluate interventions to reduce sedentary behavior. In this study, the authors evaluated the agreement in classification of these activities from three algorithms applied to thigh-worn ActiGraph accelerometers using predictions from the widely used activPAL device as a criterion. Participants (n = 29, 72% female, age 23–68 years) wore the activPAL3™ micro (processed by PAL software, version 7.2.32) and the ActiGraph™ GT9X accelerometer on the right front thigh concurrently for working hours on one full workday (7.2 ± 1.2 hr). ActiGraph output was classified via the three test algorithms: ActiGraph’s ActiLife software (inclinometer); an open source method; and, a machine-learning algorithm reported in the literature (Acti4). Performance at an instance level was evaluated by computing classification accuracy (F scores) for 15-s windows. The F scores showed high accuracy relative to the criterion for identifying sitting (96.7–97.1) and were 84.7–85.1 for identifying standing and 78.1–80.6 for identifying stepping. The four methods agreed strongly in total time spent sitting, standing, and stepping, with intraclass correlation coefficients of .96 (95% confidence interval [.92, .96]), .92 (95% confidence interval [.81, .96]), and .87 (95% confidence interval [.53, .95]) but sometimes overestimated sitting time and underestimated standing time relative to activPAL. These algorithms for identifying sitting, standing, and stepping from thigh-worn accelerometers provide estimates that are very similar to those obtained using the activPAL.
Shanie A.L. Jayasinghe, Rui Wang, Rani Gebara, Subir Biswas, and Rajiv Ranganathan
Impairment of arm movements poststroke often results in the use of compensatory trunk movements to complete motor tasks. These compensatory movements have been mostly observed in tightly controlled conditions, with very few studies examining them in more naturalistic settings. In this study, the authors quantified the presence of compensatory movements during a set of continuous reaching and manipulation tasks performed with both the paretic and nonparetic arm (in 9 chronic stroke survivors) or the dominant arm (in 20 neurologically unimpaired control participants). Kinematic data were collected using motion capture to assess trunk and elbow movement. The authors found that trunk displacement and rotation were significantly higher when using the paretic versus nonparetic arm (P = .03). In contrast, elbow angular displacement was significantly lower in the paretic versus nonparetic arm (P = .01). The reaching tasks required significantly higher trunk compensation and elbow movement than the manipulation tasks. These results reflect increased reliance on compensatory trunk movements poststroke, even in everyday functional tasks, which may be a target for home rehabilitation programs. This study provides a novel contribution to the rehabilitation literature by examining the presence of compensatory movements in naturalistic reaching and manipulation tasks.
Katie Potter, Robert T. Marcotte, Greg J. Petrucci, Caitlin Rajala, Deborah E. Linder, and Laura B. Balzer
Given high rates of obesity and chronic disease in both people and dogs, it is important to understand how dogs and dog owners influence each other’s health, including physical activity (PA) levels. Research suggests that dog owners who walk their dogs are more likely to meet PA guidelines than those who do not, but few studies have investigated dog walking intensity or its contribution to dog owners’ total moderate-to-vigorous PA using accelerometry. Furthermore, no studies have examined the contribution of dog walking to dogs’ total PA or the relationship between dog and dog owner PA using accelerometers on dogs. The authors used accelerometers on 33 dog owner–dog pairs to investigate (a) the intensity of dog walking behavior, (b) the contribution of dog walking to dog owners’ overall moderate-to-vigorous PA and dogs’ overall PA, and (c) the correlation between dog and dog owner PA. Dog owners wore an ActiGraph accelerometer and logged all dog walking for 7 days; dogs wore a Fitbark activity monitor. On average, 64.1% (95% confidence interval [55.2, 73.1]) of daily dog walking was moderate to vigorous intensity, and dog walking accounted for 51.2% (95% confidence interval [44.1, 58.3]) of dog owners’ daily moderate-to-vigorous PA. Dog walking accounted for 41.2% (95% confidence interval [36.0, 46.4]) of dogs’ daily PA. Dog owners’ daily steps were moderately correlated (r = .54) with dogs’ daily activity points. These findings demonstrate the interdependence of dog and dog owner PA and can inform interventions that leverage the dog–owner bond to promote PA and health in both species.
Brendan L. Pinto, Daniel Viggiani, and Jack P. Callaghan
The lumbar extensor spinae (LES) has an oblique orientation with respect to the compressive axis of the lumbar spine, allowing it to counteract anterior shear forces. This mechanical advantage is lost as spine flexion angle increases. The LES orientation can also alter over time as obliquity decreases with age and is associated with decreased strength and low back pain. However, it is unknown if LES orientation is impacted by recent exposures causing adaptations over shorter timescales. Hence, the effects of a 10-minute sustained spine flexion exposure on LES orientation, thickness, and activity were investigated. Three different submaximally flexed spine postures were observed before and after the exposure. At baseline, orientation (P < .001) and thickness (P = .004) decreased with increasingly flexed postures. After the exposure, obliquity further decreased at low (pairwise comparison P < .001) and moderately (pairwise comparison P = .008) flexed postures. Low back creep occurred, but LES thickness did not change, indicating that decreases in orientation were not solely due to changes in muscle length at a given posture. Activation did not change to counteract decreases in obliquity. These changes encompass a reduced ability to offset anterior shear forces, thus increasing the potential risk of anterior shear-related injury or pain after low back creep-generating exposures.
Jack P. Callaghan
Ali Brian, Angela Starrett, Adam Pennell, Pamela Haibach-Beach, Emily Gilbert, Alexandra Stribing, Sally Taunton Miedema, and Lauren Lieberman
Youth with visual impairments are more likely to be overweight than peers without visual impairments and often struggle with their locomotor skills. Locomotor development can combat unhealthy body weight statuses by supporting physical activity behaviors. There are no longitudinal investigations concerning the locomotor skill and body mass index (BMI) developmental trajectories of youth with visual impairments. The purpose of this study was to examine the 3-year developmental trajectory of the locomotor skills and BMI of youth with visual impairments including differential effects of self-reported gender and degree of vision. Participants (N = 34, M age = 11.75 years, 47% female) showed severely delayed and arrested locomotor development with increases in BMI across 3 years regardless of self-reported gender or degree of vision. Participants failed to breech a proficiency barrier of motor competence to combat against increases in BMI across time. Additional longitudinal inquiries are needed.