Development of a low-cost team performance tracking system.

The prefrontal cortex (PFC) is referred to as the visceral motor cortex; however, little is known about whether this region influences respiratory or metabolic outflows. The aim of this study was to describe simultaneous changes in respiratory, metabolic and cardiovascular functions evoked by disinhibition of the medial PFC (mPFC) and adjacent lateral septal nucleus (LSN). In urethane-anaesthetized rats, bicuculline methiodide was microinjected (2 mm; GABA-A receptor antagonist) into 90 sites in the mPFC at 0.72-4.00 mm from bregma. Phrenic nerve amplitude and frequency, arterial pressure, heart rate, splanchnic and lumbar sympathetic nerve activities (SNA), expired CO2, and core and brown adipose tissue temperatures were measured. Novel findings included disturbances to respiratory rhythm evoked from all subregions of the mPFC. Injections into the cingulate cortex evoked reductions in central respiratory function exclusively, whereas in ventral sites, particularly the infralimbic region, increases in respiratory drive and frequency, and metabolic and cardiac outflows were evoked. Disinhibition of sites in surrounding regions revealed that the LSN could evoke cardiovascular changes accompanied by distinct oscillations in SNA, as well as increases in respiratory amplitude. We show that activation of neurons within the mPFC and LSN influence respiratory, metabolic and cardiac outflows in a site-dependent manner. This study has implications with respect to the altered PFC neuronal activity seen in stress-related and mental health disorders, and suggests how basic physiological systems may be affected.

Maximal rate of oxygen uptake is one of the most commonly measured parameters in basic and physiological sciences and it is frequently used to indicate the cardio-respiratory fitness of an individual. The purpose of this study was to compare the maximal oxygen uptake (VO2max) and the cardio-respiratory responses of professional volleyball and basketball players to Harvard step test.Twenty-five volleyball players of mean age, height and weight of 26.16yrs, 1.80m, and 80.20kg and twenty-five basketball players of mean age, height and weight as 25.32yrs, 1.88m, 86.48kg were selected through purposive sampling and they performed the exercise protocol for five minutes after which there blood pressure and heart rate (HR) responses were measured. Mean arterial pressure (MAP) and rate pressure product (RPP) was also estimated from the blood pressure responses. The VO2max (maximal oxygen uptake) was estimated using the equation; Fitness index (Short form) = (100 x test duration in seconds) divided by (5.5 x pulse count between 1 and 1.5), RPP was computed using the equation; HR x systolic blood pressure (SYS) and the MAP was calculated using; MAP = Pdiast+ 1/3(Psyst- Pdiast). Comparative analysis was done using descriptive statistics of mean and standard deviation, inferential statistics of independent t-test and Pearson moment product correlation with alpha level of significance set at 0.05.Statistically significant differences were recorded between VO2 max of volleyball players; 39.07ml/kg/min, and basketball players 25.46ml/kg/min, while no statistically significant differences were recorded in their HR; 103.5bpm and 105.3bpm, SYS; 145.4mmHg and 136.7mmHg, diastolic blood pressure(DBP); 76.3mmHg and 74.7mmHg, RPP; 15200mmHg.bpm and 14548mmHg.bpm, MAP; 91.5mmHg and 89mmHg of professional basketball and volleyball players respectively. Positive significant correlations were recorded between the VO2max and RPP (p=0.001), MAP and RPP (p=0.02), MAP and SYS (p=0.00) of basketball players. A Positive significant correlation was recorded between the MAP and RPP (p=0.001), MAP and SYS (p=0.00) of volleyball players. A negative significant correlation was recorded between the VO2max and RPP (p= -0.8) of volleyball players. These data shows that volleyball players had higher VO2max than basketball players which implies that they have better cardio-respiratory endurance level. Frequent training among these athletes will help to reduce the incidence of detraining as this will invariably lead to decrease in aerobic capacity and cardio-respiratory fitness.

During a season of competition training, programs change as a means of managing the cumulative stresses of training and performing. Managing this process can be difficult to accomplish in team sports where relative exercise intensity can be dependent on position and role on the team, and effort put forth during training and competition. Measuring exercise variables, such as heart rate, lactate threshold and rating of perceived exertion, are easier to obtain and control during individual training than team training sessions. Recent advances in heart rate monitoring technology have allowed heart rate monitors to be worn by teams during practices and competitions, without interference between belts. Also, equations have been developed to calculate training intensities, referred to as training impulses (TRIMPs) for team athletes. The TRIMP technique was recently modified by Stagno et al. (2007) for implementation during team sport activities. To determine TRIMP values of both practice and competition during a single week at the end of their season for elite youth hockey players. 5 forwards and 4 defenders (n = 9; mean age: 15.7 ± 0.5 years) served as the participants. Heart rates were monitored during an entire week at the end of the season (week 28 of 29) consisting of three practices [Monday (P1), Tuesday (P2), and Thursday (P3)] and three games [one on Saturday (G1) and two on Sunday (G2, G3)]. Games were played on 24 weekends during the 29 week season. Heart rate measurements were recorded during practices and games by coded heart rate monitors that stored the data in the strap. TRIMP values were calculated from the data for each practice and game using the modified TRIMP equation. Stagno et al. (2007) created five heart rates zones between 65-100% of maximal heart rate. Minutes spent in each zone are multiplied by a weighting factor corresponding to each zone. These values are summed to determine total TRIMP value for each event. Maximal heart rate for each participant was determined using the equation developed by Gellish et al. (2007). TRIMP Zones, Total TRIMPs and TRIMPs per minute values are presented below (mean ± SD): Each training session varied in time, Total TRIMPs and TRIMPs/ min. Games decreased in TRIMPs and TRIMPs/min with slight decreases in time. Even though TRIMPs/min data are similar between some practices and some games (P2 = G2;P3 = G1), onlyG3 and P3 are similar in Total TRIMPs. Therefore, this coach has managed the time of practices to evoke game-like intensities but not durations. The use of TRIMPs gives coaches an accurate look at the intensity of practices and games for team activities. At the end of the season, when athletes may be more fatigued, an objective method of determining physiological load (i.e. TRIMP equations) should help coaches assess and track athlete responses.

The aim of this study was to analyse the physiological strain of firefighters, using heart rate (HR) and core temperature, during real wildfire suppression according to the type of attack performed (direct, indirect or mixed). Threeintensity zones were established according to the HR corresponding to the ventilatory threshold (VT) and respiratory compensation threshold (RCT): zone 1, <VT; zone 2 (Z2), between VT and RCT; zone 3 (Z3), >RCT. The exercise workload (training impulse (TRIMP)), the physiological strain index (PSI) and the cumulative heat strain index(CHSI) were calculated using the time spent in each zone, and the HR and core temperature, respectively. Significantly higher mean HR, time spent in Z2 and Z3 and TRIMP h−1 were found in direct and mixed versus indirect attacks. The highest PSI and CHSI were observed in the direct attack. In conclusion, exercise strain and combined thermal strain, but not core temperature during wildfire suppression, are related to the type of attack performed. Statement of relevance: Our findings demonstrated that wildfire firefighting is associated with high physiological demands, which vary significantly depending on the tactics chosen for performing the task. These results should be kept in mind when planning programmes to improve wildland firefighters' physical fitness, which will allow improvement in their performance.

Hyperthermia was induced during prolonged exercise (ExH) and passive heating (PaH) to isolate the influence of exercise on neuromuscular function during a maximal voluntary isometric contraction (MVC) of the quadriceps under heat stress. The influence of cardiovascular strain in limiting endurance performance in the heat was also examined. On separate days, eight males cycled to exhaustion at 60% maximal oxygen uptake or were immersed in a water bath (∼41°C) until rectal temperature (Tre) increased to 39.5°C. The ExH and PaH interventions were performed in ambient conditions of 38°C and 60% relative humidity with Tre reaching 39.8°C during exercise. Before (control) and after each intervention, voluntary activation and force production capacity were evaluated by superimposing an electrically stimulated tetanus during a 45-s MVC. Force production decreased immediately after PaH and ExH compared with control, with the magnitude of decline being more pronounced after ExH (P < 0.01). Mean voluntary activation was also significantly depressed after both interventions (P < 0.01 vs control). However, the extent of decline in voluntary activation was maintained at ∼90% during both PaH and ExH MVC. This decline accounted for 41.5% (PaH) and 33.1% (ExH) of the decrease in force production. In addition, exhaustion coincided with a marked increase in HR (∼96% of maximum) and a decline in stroke volume (25%) and mean arterial pressure (10%) (P < 0.05). The loss of force production capacity during hyperthermia originated from central and peripheral fatigue factors, with the combination of heat stress and previous contractile activity exacerbating the rate of decline. Thus, the observed significant rise in thermal strain in ExH and PaH impaired neuromuscular function and was associated with an exercise performance limiting increase in cardiovascular strain.

Heart rate (HR) monitoring is a practical method for assessing internal load (IL). However, it remains unclear for which age group HR would be an appropriate predictor of IL considering the relationship with external load (EL). Thus, this study aims to evaluate the relevance and applicability of HR monitoring by exploring the relationship between EL and IL among U16 soccer players. EL was measured using global positioning system (GPS) data, while IL was assessed through training impulse (TRIMP), Edward’s TRIMP, HR exertion, rate of perceived exertion (RPE), and session-RPE (s-RPE). Nineteen (N = 19) male footballers from an elite football academy participated, with data collected from 50 training sessions and 11 matches. In the analysis of the training sessions, TRIMP demonstrated a near-perfect correlation with total distance (TD) (p &lt; 0.001), and eTRIMP correlated strongly with TD (r = 0.82) and player load (r = 0.79). HR exertion also correlated significantly with TD, medium-speed running, decelerations, inertial movement analysis (IMA) events, and player load (p &lt; 0.001). In matches, a large correlation was observed between TRIMP and TD (r = 0.73), while the strongest correlation was between RPE and s-RPE with TD and PL (p &lt; 0.001). Furthermore, TD emerged as the best GPS-derived predictor of both TRIMP and HR exertion in training contexts. These findings provide evidence for the validity and usability of heart rate-based and RPE-based measures to indicate IL in U16 soccer players. Future research should focus on contextual factors in exploring the relationship between EL and IL.

Background and Study Aim. Response time is one of the important parameters affecting performance in sports. The aim of this study was to investigate the visual response time of the upper (hand) and lower (foot) extremities after a warm-up activity applied to female football and volleyball players. Material and Methods. Eleven female football players and eleven volleyball players, aged 19.27 ± 1.93 years, with a height of 164.90 ± 8.07 cm, body weight of 57.00 ± 6.01 kg, and 6.40 ± 2.36 years of sports experience, participated in the study as volunteers. Visual response times for the upper and lower extremities were measured before and after the warm-up protocol. The warm-up began with static stretching exercises for 2 minutes. This was followed by aerobic jogging for 2.5 minutes at a heart rate of approximately 140 beats per minute. After that, activities involving dynamic joint mobility were performed for 5 minutes. Finally, a 2.5-minute, three-stage sport-specific warm-up was completed. In total, the warm-up protocol lasted 17 minutes. Results. Volleyball players' upper extremity visual response time did not show significant differences before and after warm-up (Z = -1.561, p = 0.119). Significant differences were found in the upper extremity visual response time of football players before and after warm-up (t = 2.887, p = 0.016). No significant difference was found in the comparison of volleyball and football players' pre-warm-up (t = 1.905, p = 0.071) and post-warm-up (U = 43.000, p = 0.247) two-hand visual response times. A significant difference was found in the comparison of volleyball players' lower extremity visual response times before and after warm-up (Z = -2.674, p = 0.007). No significant difference was found in the comparison of lower extremity visual response times of football players before and after warm-up (t = 2.132, p = 0.059). A significant difference was determined in the comparison of lower extremity visual response times of volleyball and football players before warm-up (t = 3.307, p = 0.004) and after warm-up (U = 20.000, p = 0.008). Conclusions. The findings highlight the importance of sport-specific warm-up protocols in preparing athletes for optimal performance. Implementing appropriate warm-up strategies can therefore be a key factor in maximizing athletic performance and maintaining long-term physical health in female athletes.

Older horses have an increased risk of hyperthermia due to impaired cardiovascular function. While many studies have investigated thermoregulation in horses during exercise, none have investigated the effects of ageing. To test the hypothesis that there is a difference in thermoregulation during exercise and plasma volume (PV) in young and old horses. Study 1: 6 young (Y, 7.7 ± 0.5 years) and 5 old (O, 26.0 ± 0.8 years) unfit Standardbred mares (507 ± 11 kg, mean ± s.e.) ran on a treadmill (6% grade, velocity calculated to generate a work rate of 1625 watts) until core temperature reached 40 °C. Core (CT), skin (ST), rectal temperature (RT) and heart rate (HR) were measured every min until 10 min post exertion. Packed cell volume (HCT), lactate (LA) and plasma protein (TP) were measured in blood samples collected before, at 40 °C and every 5 min until 10 min post exercise. Sweat loss was estimated using bodyweight. Study 2: Plasma volume was measured in 26 young (8.2 ± 0.7 years) and 8 old (26.6 ± 0.7 years) Standardbred mares (515 ± 12 kg) using Evans Blue dye. Pre-exercise blood (rBV) and red cell (rRCV) volumes were calculated using PV and HCT. Data analysis utilised repeated measures ANOVA and t tests and data are expressed as mean ± s.e. Old horses reached 40 °C faster (998 ± 113 vs. 1925 ± 259 s; P < 0.05) with a greater HR at 40 °C (184 ± 6 vs. 140 ± 5 beats/min; P < 0.05) and greater sweat losses (P < 0.05). Heart rate did not differ (P > 0.05) post exercise. Age did not alter (P > 0.05) CT, ST, RT, LA, HCT or TP. Plasma volume was greater in Y vs. O horses (P < 0.05, 28.5 ± 1.4 vs. 24.1 ± 1.6 l) as was rBV (41.3 ± 2.0 vs. 35.3 ± 2.3 l) and rRCV (13.3 ± 0.6 vs. 11.1 ± 0.8 l). Ageing compromises the ability to handle the combined demand of exercise and thermoregulation in part due to decreased absolute pre-exercise PV.

The scientific understanding of the physiological load during practices and competitions is quite limited. While sports coaches may be able to assess the stresses and cumulative fatigue of their players, these perceptions can be biased and inaccurate. Therefore, a need exists to develop a method of determining acute and cumulative loads throughout a sports season. The Training Impulse (TRIMP) method was devised for this purpose and has been recently revised by Stagno, et, al. (2007) for use with team sports. To compare TRIMP values for forwards and defensemen during ice hockey games on different sized rinks on consecutive days using the new team-based TRIMP formula. Our hypothesis was that TRIMP scores would be greater for the game on the larger ice surface as more area must be covered. The six participants (mean age: 15.7 + 0.5 years) were forwards and defensemen playing on a regionally elite male ice hockey team. Heart rates were collected by a heart rate system that records and saves the data within a chest strap. Two games played on consecutive days (on the 19th week of a 29 week season) on different sized ice rinks were monitored. Game 1 (G1) was played on a rink that measured 200 × 85 feet, while the rink for Game 2 (G2) measured 200 × 100 feet. Each game began with a twenty minute on-ice warm-up. During G1 the ice was resurfaced between all periods. During G2, a short break was taken between the 1st and 2nd periods and the ice was resurfaced between the 2nd and 3rd periods. The TRIMPs were calculated for warm-ups, resurfacing times and playing time. Data is presented for the total time period (from the warm-up to the end of the game) and for the game period (only while the game was in progress). Data are presented in table below: Our research hypothesis was based on the logic that playing on a larger ice surface would lead to greater TRIMPs. This was not found to be true. G1 produced greater TRIMPs and greater TRIMPs per minute than G2 even though the second game was on the larger ice surface. TRIMP values for G2 may have been lower as it was the second game within a 24 hour period. While the athletes are used to playing two or three games during a two-day weekend, the second game may have lower TRIMP values due to fatigue. Thus fatigue may influence TRIMPs more than rink size. Further analyses of other game weekends may indicate a trend. As there is now a heart rate monitoring system that will capture data without the need for an external data capturing module, it is now more feasible to obtain heart rate data from team sports such as hockey and soccer. Since the revised TRIMP formula only requires heart rate data, it can now be used by coaches to track physiological loads during practice sessions and competitions. For coaches and trainers that are concerned about unintended overreaching/overtraining, this method may be a beneficial component to add to their tracking system.

Restrained rats and the observer effect in physiology

The current paper aimed to prepare axial stability exercises with a variety of back muscle contractions for volleyball players, and identify their important effects on some physiological indicators according to sports technology and the explosive ability of volleyball players. The research was based on two hypotheses, both of which indicated statistically significant variations in test results. Pre and post brain signals (EEG) for the three beta brain waves in the experimental group. There are statistically significant variations between the before and post-test findings for the explosive ability of the legs in the experimental group participants. The experimental research technique was used by creating one experimental group. The research population was represented by 12 young volleyball players from Al-Kahraba Club, who were selected using a comprehensive enumeration method to represent their community of origin, with a 100% representation of their community of origin in the sample for the 2023/2024 sports season. The latest sports technologies were employed to measure brain signals (EEG) for the three beta brain waves. This method is easy to apply on the volleyball court and does not require the transportation of players to other laboratories, as is the case with the (Neurosky) device, which includes a sensitive head kit. The Sarget test is approved for the purpose of measuring the explosiveness of the legs, and the EEG is equipped with NeuroSky technology to detect nerve signals. The exercises were prepared and applied in the research experiment by applying pre-tests on 8/10/2023 and then applying axial stability exercises with varying back muscle contractions for the period from 8/13/2023 until 10/5/2023. Applying post-tests on 8/10/2023 concluded the experiment, and the SPSS system statistically processed the collected data, leading to the conclusions and applications that axial stability exercises with varying back muscle contractions enhance the level of low beta EEG signals. To improve volleyball players' explosive abilities, coaches should prioritize physiological (EEG) signals measurement in line with their sports technology. Mobile balance tools used in axial stability training should be suitable for the players' abilities and ensure their safety from sudden falls or injuries.

Training progressions and sufficient recovery are integral to enhancing exercise performance. Athletes in individual sports (i.e., cycling, running, swimming, triathlon) can use one of numerous techniques such as heart rate, rating of perceived exertion, or lactate threshold velocity to determine exercise intensity. However, in team sport activities the exercise intensity for each athlete is much more difficult to predetermine as members of the team usually perform similar activities which would not necessarily be of the same relative intensity. Likewise, technology has not been as easily utilized in team sports as it has been in individual sports. Recent advances have allowed for heart rate to be collected during team activities through the use of coded heart rate belts which prevent interference between belts worn by teammates. Also, training impulse (TRIMP) equations, where both exercise intensity (from heart rate) and duration of the activity are used to determine exercise load, have been developed and revised. Stagno et al. (2007) recently modified the TRIMP technique for use with team sports. To determine TRIMP values for elite youth ice hockey players during practice and games within a single week during the middle of their season. Seven forwards and five defensemen (mean age: 15.8 + 0.4 years) served as the participants for this study following informed consent. A week of two practices (Tuesday and Thursday) and three games (two on Saturday, one on Sunday) were monitored during the middle of the season (week 15 of 29). In a 29 week season, the team played games on 24 weekends. Heart rate data was collected using coded heart rate monitors that stored the data in the strap. After the practices and games the TRIMP values were determined using the modified equation developed by Stagno et al. (2007) in which heart rates between 65-100% of maximal were divided into 5 zones (1 = 65-71%, 2 = 72-78%, 3 = 79-85%, 4 = 86-92%, 5 = 93-100%). The number of minutes spent in each zone was then multiplied by a weighting factor and the values then summed to determine total TRIMPs. Maximal heart rate was estimated using the equation developed by Gellish et al. (2007). RESULTS (mean + SD): The games were similar in total TRIMPs to the practices. However, a much greater number of TRIMPs in zone 5 were reported in games than in practice sessions. The TRIMP values for the practices and games were lower than those reported by Stagno et al. (2007) for elite male field hockey players. Whether these differences were due to the level of athlete, the age of the athlete, or the time of season will require further research. Use of TRIMPs should give the coach a quantifiable means of examining practice sessions and games for team activities and thus a greater means of assessing and comparing the physiological load of the training sessions.

Group processes are important for promoting relational and performance-related outcomes in sport; however, research exploring emotional and physiological synchrony and performance outcomes is rare. The objective of this study was to examine perceived emotional synchrony, physiological synchrony, and performance among male volleyball players using a naturalistic uncontrolled prospective case study approach over nine practices. Athletes participated in a coach-led pre-practice group visualization routine, while their heart rate and heart rate variability were continuously monitored. Athletes completed post-practice measures of emotional synchrony, and athletes and coaches completed ratings of individual and team performance. Emotional and physiological synchrony were not significantly correlated, but they were differentially related to performance outcomes, and there were significant interaction effects between physiological synchrony and time. Athletes’ ratings of their own and their team’s performance were associated with their perceived emotional synchrony. Coach performance ratings were associated with pre-practice team physiological synchrony but were unrelated to athletes’ perceived emotional synchrony. Heart rate synchrony was associated with athlete and coach performance ratings and may be important for team dynamics and performance outcomes. The findings demonstrate evidence for emotional and physiological synchrony among athletes, providing a platform for future research examining processes and impacts of synchrony in sport.

Purpose: The aim of this study was to evaluate the reproducibility of internal and external load parameters during recreational small-sided football games. Methods: Ten healthy untrained young adult males (age: 20.2 ± 1.9 yr, body mass: 69.2 ± 6.3 kg, height: 175.4 ± 5.9 cm, body fat: 19.7 ± 5.2%) performed two 2 × 20-min sessions of four versus four plus goalkeeper small-sided games (SSG) 1 week apart on a standard, outdoor, 40 × 20-m artificial grass pitch. Twelve external (total distance, peak speed, player load, work rate and distance covered at 0–2, 2–5, 5–7, 7–9, 9–13, 13–16, 16–20 and >20 km/h) and seven internal load parameters (heart rate and time spent in different heart rate zones [<70%, 71–80%, 81–90%, 91–95%, 96–100%, 91–100%]) were measured. Reproducibility was reported as intraclass coefficient correlation (ICC), the coefficient of variation (CV), and the typical error of measurements (TE). Results: No statistical differences (p> .05) between sessions were found in any measures. Minimal test-retest variability was noted for mean and peak heart rate (HRpeak) relative to HRpeak with CV values of 3.4% and 2.6%, respectively. Acceptable variability (CV<10%) was demonstrated for total distance covered, distance covered at 2–5 km/h, and peak speed. Distance covered in different speed zones (CV = 15.7–47.6%) and percentage of time in each HR zone showed large-to-very large variability (CV = 36.2–128.4%). Mean heart rate (HRmean), HRpeak, distance covered at 5–7, 13–16 and >20 km/h, and percentage of time above 95%HRpeak were the most reliable variables (ICC = 0.74–0.79), followed by total distance covered, peak speed, and percentage of time at 80–90% HRpeak (ICC = 0.39–0.67). The lowest reliability was observed for distance covered in the moderate speed zones 7–9 km/h (ICC = 0.12) and 9–13 km/h (ICC = −0.09), and percentage of time at 70–80% HRpeak (ICC = −0.01). Conclusions: Small-sided games can be used when planning training-induced exercise responses in relation to total distance covered, peak speed, and mean heart rate. This evidence further supports the use of SSG when organizing recreational football training, in young adult males, with the purpose of improving health profile due to the high reproducibility of HRmean and total distance covered.

This study aimed to (1) classify the external-load measures carried out during the preseason period by male volleyball players via cluster technique identifying the most important external-load measures and (2) assess the differences between clusters in internal-load variables. Twenty-two male Division 1 and 2 volleyball players (mean [SD] age 21.2 [3.0]y, stature 186.4 [6.0]cm, body mass 80.0[10.5kg]) were recruited for this study. Players' external (jump, player load, acceleration, deceleration, and change of direction) and internal (percentage of peak heart rate, summated heart-rate zones, and session rating of perceived exertion) loads were monitored during 5weeks of the preseason period for both Division 1 and Division 2 teams. External-load measures were classified via a 2-step cluster analysis followed by predicting importance analysis, while differences in internal-load measures between clusters were analyzed using linear mixed models. The 3 identified clusters classified the sessions in high (C1, 30.1%) moderate (C2, 31.8%), and low (C3, 38.1%) load. Predicting importance analysis found jump as the main cluster predictor (predicting value = 1), followed by player load (predicting value = 0.73). An effect of cluster was found on each internal-load measure (P < .001), with post hoc analyses showing lower values in C3 compared with C1 and C2 (P < .05, effect sizes ranges from small to moderate). Volleyball coaches can adopt a monitoring system including cluster analysis to classify the preseason training sessions' load having a higher consideration for jump and player load as the main external-load measures.