A Randomized Crossover Pilot Trial on the Influence of a Daily Mindfulness Yoga Practice on Menstrual Cycle Symptoms, Measures of Well-Being, and Training Perception in Athletic Women.

The menstrual cycle (MC) is a series of hormonal fluctuations that occur approximately every 22-35 days in reproductive-age females, often resulting in a range of physical and psychological symptoms at different points of the cycle. MC symptoms range from mild discomfort to debilitating effects. One intervention that may be able to address these symptoms is yoga, a mind-body practice that incorporates physical postures with breathwork to foster a mindful connection to the body.

Composite activity type and stride-specific energy expenditure estimation model for thigh-worn accelerometry.

Background: Accurately measuring energy expenditure during physical activity outside of the laboratory is challenging, especially on a large scale. Thigh-worn accelerometers have gained popularity due to the possibility to accurately detect physical activity types. The use of machine learning techniques for activity classification and energy expenditure prediction may improve accuracy over current methods.

Assessing the Accuracy of Activity Classification Using Thigh-Worn Accelerometry: A Validation Study of ActiPASS in School-Aged Children.

Background: The ActiPASS software was developed from the open-source Acti4 activity classification algorithm for thigh-worn accelerometry. However, the original algorithm has not been validated in children or compared with a child-specific set of algorithm thresholds. This study aims to evaluate the accuracy of ActiPASS in classifying activity types in children using 2 published sets of Acti4 thresholds.

Menstrual cycle patterns and their relationship with measures of well-being and perceived performance metrics in competitive and recreational resistance-trained athletes.

Background: There is mixed evidence on how the menstrual cycle (MC) affects sports performance, with many studies showing variations in performance during different phases of the MC, while other evidence shows that the MC's effects on performance may be trivial. Therefore, this exploratory longitudinal monitoring study was designed to investigate MC characteristics and symptoms in a resistance-trained (RT) population to look for associations between measures of well-being and perceived performance metrics across the MC.

Methods: RT females reported their workout habits, perceived performance metrics, and measures of well-being while tracking their MC with detailed methods via daily check-ins in an app.

Predicting daily recovery during long-term endurance training using machine learning analysis.

Purpose: The aim of this study was to determine if machine learning models could predict the perceived morning recovery status (AM PRS) and daily change in heart rate variability (HRV change) of endurance athletes based on training, dietary intake, sleep, HRV, and subjective well-being measures.

Methods: Self-selected nutrition intake, exercise training, sleep habits, HRV, and subjective well-being of 43 endurance athletes ranging from professional to recreationally trained were monitored daily for 12 weeks (3572 days of tracking). Global and individualized models were constructed using machine learning techniques, with the single best algorithm chosen for each model.

Female RNA concussion (FeRNAC) study: assessing hormone profiles and salivary RNA in females with concussion by emergency departments in New Zealand: a study protocol.

Background: Females of reproductive age with concussion report a greater number of symptoms that can be more severe and continue for longer than age matched males. Underlying mechanisms for sex differences are not well understood. Short non-coding Ribonucleic Acids (sncRNAs) are candidate salivary biomarkers for concussion and have been studied primarily in male athletes.

Where Are Czech Adolescents Active? The Patterns of Movement and Transport Behavior in Different Active Living Domains.

To understand the environmental determinants of physical activity (PA), precise spatial localization is crucial. This cross-sectional study focuses on the spatiotemporal distribution of PA among Czech adolescents (n = 171) using Global Positioning System loggers and accelerometers. The results showed that adolescents spent most of their time in sedentary behavior, with 57.

Can an inertial measurement unit, combined with machine learning, accurately measure ground reaction forces in cricket fast bowling?

This study examined whether an inertial measurement unit (IMU) could measure ground reaction force (GRF) during a cricket fast bowling delivery. Eighteen male fast bowlers had IMUs attached to their upper back and bowling wrist. Each participant bowled 36 deliveries, split into three different intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%.

Sociodemographic differences in 24-hour time-use behaviours in New Zealand children.

Background: The time that children spend in physical activity, sedentary behaviour, and sleep each day (i.e., 24-h time-use behaviours), is related to physical and mental health outcomes.

Factors Influencing Substrate Oxidation During Submaximal Cycling: A Modelling Analysis.

Background: Multiple factors influence substrate oxidation during exercise including exercise duration and intensity, sex, and dietary intake before and during exercise. However, the relative influence and interaction between these factors is unclear.

Objectives: Our aim was to investigate factors influencing the respiratory exchange ratio (RER) during continuous exercise and formulate multivariable regression models to determine which factors best explain RER during exercise, as well as their relative influence.

The relationship between bowling intensity and ground reaction force in cricket pace bowlers.

This study examined the relationship between perceived bowling intensity, ball release speed and ground reaction force (measured by peak force, impulse and loading rate) in male pace bowlers. Twenty participants each bowled 36 deliveries, split evenly across three perceived intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%. Peak force and loading rate were significantly different across the three perceived intensity zones in the horizontal and vertical directions (Cohen's range = 0.

Factors Influencing AMPK Activation During Cycling Exercise: A Pooled Analysis and Meta-Regression.

Background: The 5' adenosine monophosphate (AMP)-activated protein kinase (AMPK) is a cellular energy sensor that is activated by increases in the cellular AMP/adenosine diphosphate:adenosine triphosphate (ADP:ATP) ratios and plays a key role in metabolic adaptations to endurance training. The degree of AMPK activation during exercise can be influenced by many factors that impact on cellular energetics, including exercise intensity, exercise duration, muscle glycogen, fitness level, and nutrient availability. However, the relative importance of these factors for inducing AMPK activation remains unclear, and robust relationships between exercise-related variables and indices of AMPK activation have not been established.

Smart Watch Versus Classic Receivers: Static Validity of Three GPS Devices in Different Types of Built Environments.

In order to study the relationship between human physical activity and the design of the built environment, it is important to measure the location of human movement accurately. In this study, we compared an inexpensive GPS receiver (Holux RCV-3000) and a frequently used Garmin Forerunner 35 smart watch, with a device that has been validated and recommended for physical activity research (Qstarz BT-Q1000XT). These instruments were placed on six geodetic points, which represented a range of different environments (e.

Quantifying cricket fast bowling volume, speed and perceived intensity zone using an Apple Watch and machine learning.

This study examined whether an inertial measurement unit (IMU) and machine learning models could accurately measure bowling volume (BV), ball release speed (BRS), and perceived intensity zone (PIZ). Forty-four male pace bowlers wore a high measurement range, research-grade IMU (SABELSense) and a consumer-grade IMU (Apple Watch) on both wrists. Each participant bowled 36 deliveries, split into two different PIZs (Zone 1 = 70-85% of maximum bowling effort, Zone 2 = 100% of maximum bowling effort).

Peak fat oxidation is positively associated with vastus lateralis CD36 content, fed-state exercise fat oxidation, and endurance performance in trained males.

Purpose: Whole-body fat oxidation during exercise can be measured non-invasively during athlete profiling. Gaps in understanding exist in the relationships between fat oxidation during incremental fasted exercise and skeletal muscle parameters, endurance performance, and fat oxidation during prolonged fed-state exercise.

Methods: Seventeen endurance-trained males underwent a (i) fasted, incremental cycling test to assess peak whole-body fat oxidation (PFO), (ii) resting vastus lateralis microbiopsy, and (iii) 30-min maximal-effort cycling time-trial preceded by 2-h of fed-state moderate-intensity cycling to assess endurance performance and fed-state metabolism on separate occasions within one week.

Cluster size prediction for military clothing using 3D body scan data.

Aim: To determine how anthropometric characteristics cluster in the New Zealand Defence Force, and to describe the characteristics of each cluster. This information can inform the development of new uniform sizing systems for the New Zealand Defence Force.

Methods: Anthropometric data (n = 84 variables) from 1,003 participants (212 females; 791 males) in the New Zealand Defence Force Anthropometry Survey (NZDFAS) were used.

Prediction of military combat clothing size using decision trees and 3D body scan data.

Aim: To determine how well decision tree models can predict tailor-assigned uniform sizes using anthropometry data from the New Zealand Defence Force Anthropometry Survey (NZDFAS). This information may inform automatic sizing systems for military personnel.

Methods: Anthropometric data from two separate samples of the New Zealand Defence Force military were used.

Pre-Exercise Carbohydrate or Protein Ingestion Influences Substrate Oxidation but Not Performance or Hunger Compared with Cycling in the Fasted State.

Nutritional intake can influence exercise metabolism and performance, but there is a lack of research comparing protein-rich pre-exercise meals with endurance exercise performed both in the fasted state and following a carbohydrate-rich breakfast. The purpose of this study was to determine the effects of three pre-exercise nutrition strategies on metabolism and exercise capacity during cycling. On three occasions, seventeen trained male cyclists (VO 62.

Can Machine Learning with IMUs Be Used to Detect Different Throws and Estimate Ball Velocity in Team Handball?

Injuries in handball are common due to the repetitive demands of overhead throws at high velocities. Monitoring workload is crucial for understanding these demands and improving injury-prevention strategies. However, in handball, it is challenging to monitor throwing workload due to the difficulty of counting the number, intensity, and type of throws during training and competition.

Can an inertial measurement unit (IMU) in combination with machine learning measure fast bowling speed and perceived intensity in cricket?

This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was attached to the thoracic back of 44 fast bowlers. Each participant bowled 36 deliveries at two different PIZ zones (Zone 1 = 24 deliveries at 70% to 85% of maximum perceived bowling effort; Zone 2 = 12 deliveries at 100% of maximum perceived bowling effort) in a random order.

Sociodemographic and Built Environment Associates of Travel to School by Car among New Zealand Adolescents: Meta-Analysis.

Travelling to school by car diminishes opportunities for physical activity and contributes to traffic congestion and associated noise and air pollution. This meta-analysis examined sociodemographic characteristics and built environment associates of travelling to school by car compared to using active transport among New Zealand (NZ) adolescents. Four NZ studies (2163 adolescents) provided data on participants' mode of travel to school, individual and school sociodemographic characteristics, distance to school and home-neighbourhood built-environment features.

Effects of a Curriculum-Integrated Dance Program on Children's Physical Activity.

Background: Curriculum-integrated dance programs are a promising but relatively under-researched strategy for increasing children's physical activity (PA). The aim of this study was to determine the impact of a curriculum-integrated dance program on children's PA.

Methods: A total of 134 primary children aged 7-9 years from 4 New Zealand schools were assigned to either a dance group (n = 78) or a control group (n = 56).

Application of Raw Accelerometer Data and Machine-Learning Techniques to Characterize Human Movement Behavior: A Systematic Scoping Review.

Background: Application of machine learning for classifying human behavior is increasingly common as access to raw accelerometer data improves. The aims of this scoping review are (1) to examine if machine-learning techniques can accurately identify human activity behaviors from raw accelerometer data and (2) to summarize the practical implications of these machine-learning techniques for future work.

Methods: Keyword searches were performed in Scopus, Web of Science, and EBSCO databases in 2018.

The Importance of Pedestrian Network Connectivity for Adolescent Health: A Cross-sectional Examination of Associations between Neighbourhood Built Environments and Metabolic Health in the Pacific Islands Families Birth Cohort Study.

The research aim was to investigate associations between objectively-assessed built environment attributes and metabolic risk in adolescents of Pacific Islands ethnicity, and to consider the possible mediating effect of physical activity and sedentary time. Youth ( = 204) undertook a suite of physical assessments including body composition, blood sampling, and blood pressure measurements, and seven day accelerometry. Objective measures of the neighbourhood built environment were generated around individual addresses.