Punch Trackers: Correct Recognition Depends on Punch Type and Training Experience

Physical Capacities and Combat Performance Characteristics of Male and Female Olympic Boxers

Purpose: The study characterized the anthropometrical and cardiorespiratory profile, and the cardiorespiratory, bio-chemical and immunological responses to 3 × 3 min round (R) free-contact/combat boxing simulation, in elite Olympic Boxers (4 female and 10 male). Methods: The evaluation consisted of resting metabolic rate, anthropometric measurement, maximal graded test exercise (visit 1), free combat simulation (3 × 3 min R, 1 minute rest), and blood samples collected before, during and after the combat (visit 2). Results: Respectively, females and males had (mean±SD; or median: for non-parametric data) body fat percentage (17.2[3.5] and 4.6[0.8]%), predominantly mesomorphic somatotyping, and V ˙ O 2 MAX (50.0 ± 2.5 and 56.2 ± 5.2 ml.kg-1.min-1). The free combat simulation resulted in high cardiovascular strain [mean heart rate corresponding to R1: 92 ± 3; R2: 94 ± 2; and R3: 95 ± 2% of maximal HR] and blood chemistry indicative of acidosis (following R3: 7.21 ± 0.08 pH, bicarbonate 13.1 ± 3.6 mmol.L-1, carbon dioxide 13.9 ± 3.8 mmol.L-1, lactate 15.1 ± 3.8 mmol.L-1, and glucose 8.4 ± 1.3 mmol.L-1). Further, notable general catabolism, hematological and immune responses were evident post combat simulation (1-hour post R3: creatinine 95.2 ± 14.5 µmol.L-1, urea 6.4 ± 1.3 mmol.L-1, white blood cell accumulation 7.8 ± 2.6 × 109.L-1, hemoglobin 14.9 ± 0.8 g.dL-1 and hematocrit 43.7 ± 1.9%). Conclusions: Notable cardiovascular strain and acidosis are seen from the 3 × 3 free combat simulation whilst pronounced catabolism and immune responses are evident 1-hour post R3. This characterization is the first in male and female (who recently adopted the 3 × 3 min R format, as used by males) elite Olympic boxers and provides a characterization framework to assist practitioners and athletes in their attempts to deliver evidence-informed practice for specific conditioning session design.

Validity of Commercially Available Punch Trackers

ABSTRACT

Omcirk, D, Vetrovsky, T, Padecky, J, Malecek, J, and Tufano, JJ. Validity of commercially available punch trackers. J Strength Cond Res 37(11): 2273-2281, 2023-This study determined how well data from commercially available punch trackers (Corner, Hykso, and StrikeTec) related to gold-standard velocity and force measures during full-contact punches. In a quasi-randomized order, 20 male subjects performed 6 individual rear straight punches, rear hooks, and rear uppercuts against a wall-mounted force plate. Punch tracker variables were compared with the peak force of the force plate and to the peak (QPV) and mean velocity (QMV) assessed through Qualisys 3-dimensional tracking. For each punch tracker variable, Pearson's correlation coefficient, mean absolute percentage error (MAPE), and mean percentage error (MPE) were calculated. There were no strong correlations between punch tracker data and gold-standard force and velocity data. However, Hykso "velocity" was moderately correlated with QMV ( r = 0.68, MAPE 0.64, MPE 0.63) and QPV ( r = 0.61, MAPE 0.21, MPE -0.06). Corner Power G was moderately correlated with QMV ( r = 0.59, MAPE 0.65, MPE 0.58) and QPV ( r = 0.58, MAPE 0.27, MPE -0.09), but Corner "velocity" was not. StrikeTec "velocity" was moderately correlated with QMV ( r = 0.56, MAPE 1.49, MPE 1.49) and QPV ( r = 0.55, MAPE 0.46, MPE 0.43). Therefore, none of the devices fared particularly well for all of their data output, and if not willing to accept any room for error, none of these devices should be used. Nevertheless, these devices and their proprietary algorithms may be updated in the future, which would warrant further investigation.

Profiling the Physical Performance of Young Boxers with Unsupervised Machine Learning: A Cross-Sectional Study

Mexico City is the location with the largest number of boxers in Mexico; in fact, it is the first city in the country to open a Technological Baccalaureate in Education and Sports Promotion with a pugilism orientation. This cross-sectional study aimed to determine the physical-functional profile of applicants for admission to the baccalaureate in sports. A total of 227 young athletes (44F; 183M; 15.65 (1.79) years; 63.66 (14.98) kg; >3 years of boxing experience) participated in this study. Body mass (BM), maximal isometric handgrip (HG) strength, the height of the countermovement jump (CMJ), the velocity of straight boxing punches (PV), and the rear hand punch impact force (PIF) were measured. The young boxers were profiled using unsupervised machine learning algorithms, and the probability of superiority (ρ) was calculated as the effect size of the differences. K-Medoids clustering resulted in two sex-independent significantly different groups: Profile 1 (n = 118) and Profile 2 (n = 109). Except for BM, Profile 2 was statistically higher (p < 0.001) with a clear distinction in terms of superiority on PIF (ρ = 0.118), the PIF-to-BM ratio (ρ = 0.017), the PIF-to-HG ratio (ρ = 0.079) and the PIF-to-BM+HG ratio (ρ = 0.008). In general, strength levels explained most of the data variation; therefore, it is reasonable to recommend the implementation of tests aimed at assessing the levels of isometric and applied strength in boxing gestures. The identification of these physical-functional profiles might help to differentiate training programs during sports specialization of young boxing athletes.

Pain Perception in Contact Sport Athletes: A Scoping Review

Contact sports athletes are regularly facing acute physical pain in part of their sport; however, the literature investigating pain perception in these athletes remains scarce. This scoping review aimed to explore the literature surrounding pain perception in contact sport athletes and to compile and understand how it is studied. The search strategy consisted of using index terms and keywords in the MEDLINE, EMBASE, SPORTDiscus, Web of Science, PsycINFO, CINAHL and ProQuest Dissertations & Theses Global search engines. Results from 11 studies revealed that a mix of team contact sports and combat sports are studied and are included under the umbrella of contact sports. These athletes are being compared with non-athletes as well as athletes from non-contact sports. The cold pressor test and the pain pressure test are the two predominant methods used to investigate physical pain. This review highlights the need to clearly define sports based on contact levels expected in play to better define the types of pain athletes are facing in their practice. Athletes' level of play as well as years of experience should also be more rigorously reported. While contact sport athletes seem to have a higher level of pain tolerance than both active controls and non-contact athletes, the methods of pain testing are not always justified and appropriate in relation to the pain induced during contact sports. Future experimental studies should use pain testing methods relevant to the pain experienced during contact sports and to better justify the rationale for the choice of these methods.

Acute effects of ballistic versus heavy-resistance exercises on countermovement jump and rear-hand straight punch performance in amateur boxers

Background

Ballistic and heavy-resistance exercises may potentially enhance lower body power, which is paramount for the punching performance of amateur boxers. This study aimed to determine the acute effects of ballistic exercise (BE) and heavy-resistance exercise (HRE) on countermovement jump (CMJ) and rear-hand straight punch performance in amateur boxers.

Methods

Ten amateur boxers performed two conditioning exercises in a randomized and counterbalanced order as follows: squat jump with 4 sets × 8 repetitions at 30% one-repetition maximum (1RM) for BE and squat with 3 sets × 5 repetitions at 80% 1RM for HRE. The jump height (JH), relative maximal force (RMF), relative maximal power (RMP) of the CMJ, punch force (PF), and punch speed (PS) of a rear-hand straight punch were measured before and 3, 6, 9, and 12 min after either BE or HRE.

Results

No significant condition × time interaction was found for JH (p = 0.303), RMF (p = 0.875), RMP (p = 0.480), PF (p = 0.939), and PS (p = 0.939). In addition, no main effect of the condition for JH (p = 0.924), RMF (p = 0.750), RMP (p = 0.631), PF (p = 0.678), and PS (p = 0.712). A significant main effect of time was observed for PF (p = 0.001) and PS (p = 0.001), whereas JH (p = 0.081), RMF (p = 0.141), and RMP (p = 0.430) were not. Pairwise comparison identified that PF (p = 0.031) and PS (p = 0.005) significantly increased at 9 min compared with those at baseline.

Conclusions

The findings of this study demonstrated that BE and HRE protocols can potentiate the rear-hand straight punch performance at 9 min but bring less favorable improvements for JH, RMF, or RMP of CMJ.

Fusion Models for Generalized Classification of Multi-Axial Human Movement: Validation in Sport Performance

We introduce a set of input models for fusing information from ensembles of wearable sensors supporting human performance and telemedicine. Veracity is demonstrated in action classification related to sport, specifically strikes in boxing and taekwondo. Four input models, formulated to be compatible with a broad range of classifiers, are introduced and two diverse classifiers, dynamic time warping (DTW) and convolutional neural networks (CNNs) are implemented in conjunction with the input models. Seven classification models fusing information at the input-level, output-level, and a combination of both are formulated. Action classification for 18 boxing punches and 24 taekwondo kicks demonstrate our fusion classifiers outperform the best DTW and CNN uni-axial classifiers. Furthermore, although DTW is ostensibly an ideal choice for human movements experiencing non-linear variations, our results demonstrate deep learning fusion classifiers outperform DTW. This is a novel finding given that CNNs are normally designed for multi-dimensional data and do not specifically compensate for non-linear variations within signal classes. The generalized formulation enables subject-specific movement classification in a feature-blind fashion with trivial computational expense for trained CNNs. A commercial boxing system, 'Corner', has been produced for real-world mass-market use based on this investigation providing a basis for future telemedicine translation.

Using an artificial neural network to develop an optimal model of straight punch in boxing and training in punch techniques based on this model and real-time feedback

The work was aimed to develop an optimal model of a straight punch in boxing based on an artificial neural network (ANN) in the form of a multilayer perceptron, as well as to develop a technique for improving the technique of punches in boxing based on feedback, when each punch delivered by a boxer was compared with the optimal model. The architecture of the neural network optimal punch model included an input layer of 600 nodes-the values of absolute accelerations and angular velocities, four hidden ones, as well as a binary output layer (the best and not the best punch). To measure accelerations and angular velocities, inertial measuring devices were attached to the boxers' wrists. Highly qualified participated in the data set for the development of the optimal model. The best punches were chosen according to the criteria of strength and speed. The punch force was determined using a boxing pad with the function of measuring the punch force. In order to be able to compare punches, a unified parameter was developed, called the punch quality, which is equal to the product of the effective force and the punch speed. To study the effects of biofeedback, the boxing pads were equipped with five LEDs. The more LEDs were turned on, the more the punch corresponded to the optimal model. As a result of the study, an almost linear relationship was found between the quality of the punch of entry-level boxers and the optimal model. The use of feedback allowed for an increase in the quality of punches from 11 to 25%, which is on average twice as high as in the group where the feedback method was not used. Studies have shown that it is possible to develop an optimal punch model. According to the degree of compliance with this model, you can evaluate and train boxers in the technique.