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Tanya Tripathi, Stacey C. Dusing, Peter E. Pidcoe, Yaoying Xu, Mary S. Shall and Daniel L. Riddle

Aims: The American Academy of Pediatrics recommends “parents to incorporate supervised, awake ‘prone play’ in their infant’s routine to support motor development and minimize the risk of plagiocephaly”. The purpose of this feasibility study was to compare usual care to a reward contingency–based intervention, developed to increase prone tolerance and improve motor skills. Methods: Ten full-term infants, 3–6- months old, with poor prone tolerance were randomized to either the Education group or Reward contingency group. Each group participated in three parent education sessions and 15 intervention sessions, over the period of three weeks. Infants in the Reward contingency group used the Prone Play Activity Center, a technology developed to reinforce motor behavior of infants in prone position. Intervention frequency and parent feedback data determined the feasibility of the interventions. Results: Infants in the Reward contingency group practiced a median of 12 of the 15 anticipated intervention sessions in the Prone Play Activity Center. These infants used the device for a mean of 18 minutes per day. Parents of infants in the Education group practiced a median of 10 sessions of the 15 anticipated intervention sessions. Conclusion: The reward contingency–based intervention is feasible for use in a future clinical trial with some modifications.

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Ryan Eckert, Jennifer Huberty, Heidi Kosiorek, Shannon Clark-Sienkiewicz, Linda Larkey and Ruben Mesa

Introduction: The delivery of online interventions in cancer patients/survivors has increased. The measurement of participation in online interventions is important to consider, namely, the challenges of the remote assessment of activity. The purpose of this study was to report the measures used to assess intervention compliance and other physical activity participation in two online yoga studies, the relationship between the multimethod measures used, and the ability of cancer patients to complete these measures. Methods: The methods described are of two online yoga studies (feasibility and pilot). Cancer patients were asked to participate in 60 min/week of online yoga for 12 weeks, complete a weekly yoga log, wear a Fitbit daily for 12 weeks, and complete a weekly physical activity log. Finally, Clicky®, a web analytics software, was used to track online yoga participation. Results: Eighty-four people participated across both studies, with 63/84 participating in online yoga, averaging 57.5 ± 33.2 min/week of self-reported yoga participation compared to 41.4 ± 26.1 min/week of Clicky® yoga participation (Lin concordance = 0.28). All 84 participants averaged 95.5 ± 111.8 min/week of self-reported moderate/vigorous physical activity compared with 98.1 ± 115.9 min/week of Fitbit-determined moderate/vigorous physical activity (Lin concordance = 0.33). Across both studies, 82.9% of the yoga logs were completed, the Fitbit was worn on 75.2% of the days, and 78.7% of the physical activity logs were completed. Conclusions: Weak relationships between self-report and objective measures were demonstrated, but the compliance rates were above 75% for the study measures. Future research is needed, investigating the intricacies of self-report physical activity participation in remote interventions and the validation of a gold standard measurement for online interventions.

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Fahim A. Salim, Fasih Haider, Dees Postma, Robby van Delden, Dennis Reidsma, Saturnino Luz and Bert-Jan van Beijnum

Automatic tagging of video recordings of sports matches and training sessions can be helpful to coaches and players and provide access to structured data at a scale that would be unfeasible if one were to rely on manual tagging. Recognition of different actions forms an essential part of sports video tagging. In this paper, the authors employ machine learning techniques to automatically recognize specific types of volleyball actions (i.e., underhand serve, overhead pass, serve, forearm pass, one hand pass, smash, and block which are manually annotated) during matches and training sessions (uncontrolled, in the wild data) based on motion data captured by inertial measurement unit sensors strapped on the wrists of eight female volleyball players. Analysis of the results suggests that all sensors in the inertial measurement unit (i.e., magnetometer, accelerometer, barometer, and gyroscope) contribute unique information in the classification of volleyball actions types. The authors demonstrate that while the accelerometer feature set provides better results than other sensors, overall (i.e., gyroscope, magnetometer, and barometer) feature fusion of the accelerometer, magnetometer, and gyroscope provides the bests results (unweighted average recall = 67.87%, unweighted average precision = 68.68%, and κ = .727), well above the chance level of 14.28%. Interestingly, it is also demonstrated that the dominant hand (unweighted average recall = 61.45%, unweighted average precision = 65.41%, and κ = .652) provides better results than the nondominant (unweighted average recall = 45.56%, unweighted average precision = 55.45, and κ = .553) hand. Apart from machine learning models, this paper also discusses a modular architecture for a system to automatically supplement video recording by detecting events of interests in volleyball matches and training sessions and to provide tailored and interactive multimodal feedback by utilizing an HTML5/JavaScript application. A proof of concept prototype developed based on this architecture is also described.

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Sandy J. Slater, Anmol Sanghera, Yadira Herrera and Jamie F. Chriqui

Background: Head Start serves over 1 million diverse low-income preschool children and is an ideal setting for developing and implementing obesity prevention efforts, which is expected to have positive impacts on behavior as youth age. This study examined how regional- and state-level Head Start offices have supported implementation of the recently updated physical activity (PA) requirement within the teaching and learning environment Head Start Program Performance Standard (1302.31). Methods: Key informant telephone interviews were conducted with 8 regional- and 36 state-level Head Start representatives. Interviews were recorded and professionally transcribed. Data were coded and analyzed using constant comparative methods in ATLAS.ti (version 8). Audit trails were maintained, and disagreements in codes were discussed and resolved among coders. Results: The following 3 overarching themes emerged: communication, resources and technical assistance, and challenges. Results showed variation in respondent knowledge regarding the Standards. Although regional contacts provide technical assistance, state-level contacts have many information sharing strategies for programs. Implementation challenges included the need for frequent professional development opportunities given staff turnover and low PA competency, and additional PA curricula. Conclusion: Findings can help identify existing or potential strategies that could be adopted more widely or developed to assist Head Start programs incorporate PA into daily activities.

Open access

Ryoko Kawakami, Yuko Gando, Kiminori Kato, Susumu S. Sawada, Haruki Momma, Motohiko Miyachi, I-Min Lee, Steven N. Blair, Minoru Tashiro, Chika Horikawa, Yasuhiro Matsubayashi, Takaho Yamada, Kazuya Fujihara and Hirohito Sone

Background: To examine the association between muscular and performance fitness (MPF) and the incidence of glaucoma. Methods: A total of 27,051 glaucoma-free participants aged 20–87 years underwent physical fitness tests between April 2001 and March 2002. The MPF index was calculated using an age- and sex-specific summed z-score from grip strength, vertical jump, single-leg balance, forward bending, and whole-body reaction time. The participants were divided into quartiles according to the MPF index and each physical fitness test. Participants were followed up for the development of glaucoma, which was defined based on physician-diagnosed glaucoma at an annual health examination between April 2002 and March 2008. Hazard ratios for the incidence of glaucoma were estimated using Cox proportional hazards models. Results: During follow-up, 303 participants developed glaucoma. Compared with the lowest MPF index group, hazard ratio (95% confidence interval) of developing glaucoma was 0.64 (0.46–0.89) for the highest MPF index group (P for trend = .001). Vertical jump and whole-body reaction time were associated with incident glaucoma (P for trend = .01 and <.001, respectively). There were no associations between the other physical fitness tests and the incidence of glaucoma. Conclusion: Higher MPF is associated with lower incidence of glaucoma.

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Roman P. Kuster, Daniel Baumgartner, Maria Hagströmer and Wilhelmus J.A. Grooten

Background: Sedentary behavior (SB) is associated with several chronic diseases and office workers especially are at increased risk. SB is defined by a sitting or reclined body posture with an energy expenditure of ≤1.5 metabolic equivalents. However, current objective methods to measure SB are not consistent with its definition. There is no consensus on which sensor placement and type should be used. Aim: To compare the accuracy of newly developed artificial intelligence models for 15 sensor placements in combination with four signal types (accelerometer only/plus gyroscope and/or magnetometer) to detect posture and physical in-/activity during desk-based activities. Method: Signal features for the model development were extracted from sensor raw data of 30 office workers performing 10 desk-based tasks, each lasting 5 min. Direct observation (posture) and indirect calorimetry (in-/activity) served as the reference criteria. The best classification model for each sensor was identified and compared among the sensor placements, both using Friedman and post hoc Wilcoxon tests (p ≤ .05). Results: Posture was most accurately measured with a lower body sensor, while in-/activity was most accurately measured with an upper body or waist sensor. The inclusion of additional signal types improved the posture classification for some placements, while the acceleration signal already contained the relevant signal information for the in-/activity classification. Overall, the thigh accelerometer most accurately classified desk-based SB. Conclusion: This study favors, in line with previous work, the measurement of SB with a thigh-worn accelerometer and adds the information that this sensor is also accurate in measuring physical in-/activity while sitting and standing.

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Justin B. Hollander, Ann Sussman, Peter Lowitt, Neil Angus and Minyu Situ

Background: Understanding more about the unseen side of our responses to visual stimuli offers a powerful new tool for transportation planning. Traditional transportation planning tends to focus on the mobility of vehicles rather than on opportunities to encourage sustainable transport modes, like walking. Methods: Using eye-tracking emulation software, this study measured the unconscious visual responses people have to designs and layouts in new built environments, focusing on what makes streets most walkable. Results: The study found key differences between the way the brain takes in conventional automobile-oriented residential developments versus new urbanist layouts, with the former lacking key fixation points. Conclusion: The study’s discoveries significantly explain why new urbanist layouts promote walking effortlessly and conventional automobile-oriented residential developments cannot.

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Rodrigo Sudatti Delevatti, Ana Carolina Kanitz, Cláudia Gomes Bracht, Salime Donida Chedid Lisboa, Elisa Corrêa Marson, Thaís Reichert, Vitória Bones and Luiz Fernando Martins Kruel

Background: There are a lack of clinical trials with suitable methodological quality that compare aquatic exercise training types in type 2 diabetes (T2D) treatment. This study aimed to compare the effects of aerobic and combined aquatic training on cardiorespiratory outcomes in patients with T2D. Methods: Untrained patients with T2D were randomized to receive an aerobic aquatic training, a combined aquatic training, or a procedure control in 3 weekly sessions for 15 weeks. The sessions were 50 minutes long. The intensities were from 85% to 100% of heart rate of anaerobic threshold and at maximal velocity for aerobic and resistance parts, respectively. Resting heart rate, peak oxygen uptake (VO2peak), and oxygen uptake corresponding to second ventilatory threshold and its relation with VO2peak were evaluated. Results: Participants were 59.0 (8.2) years old and 51% women. Intervention groups increased in VO2peak (aerobic aquatic training group: 4.48 mL·kg−1·min−1, P = .004; combined aquatic training group: 5.27 mL·kg−1·min−1; P = .006) and oxygen uptake corresponding to second ventilatory threshold, whereas the control group presented an increase in oxygen uptake corresponding to second ventilatory threshold and minimal change in VO2peak. Conclusions: Aerobic and combined aquatic exercise interventions improve the cardiorespiratory fitness of patients with T2D.