Athletic Performance Analysis Research Articles

Evaluation of high altitude training camps with heart rate recovery and heart rate variability analysis: beneficial effect in elite swimmers.

The available evidence on the impact of altitude training on sports performance is inconclusive. Heart rate variability (HRV) and heart rate recovery (HRR) are among the most frequently used parameters in athletic performance analysis and monitoring. Our study aims to investigate the effect of high altitude training on HRR and HRV, which are reliable predictors of athletic performance. Elite national swimmers were included in the study. Time domain and frequency domain analyzes were performed with the Polar Verity Sense device and Kubios HRV software. HRR were measured at one-minute intervals for the first 15 minutes after peak heart rate, and then recorded at the 20th, 25th and 30th minutes. A significant difference is observed from the beginning to the 11th minute. The P value at 1, 3, 5, 7 and 11 minutes is 0.001, 0.023, 0.032, 0.019 and 0.020, respectively. Similarly, a significant change was observed in delta HRR. Among the HRV parameters, RMSSD, SDNN, Poincaré SD1 and PNS are statistically significant. P values are 0.004, 0.018, 0.024 and 0.013 respectively. High altitude training program has a positive effect on HRV and CRV in elite swimmers. This condition is associated with increased cardiac parasympathetic activity. Time domain analyses have proven to be more beneficial for HRV. HRR and HRV are effective, reliable and inexpensive methods of performance monitoring of elite athletes.

Innovative pressure sensing with amorphous silicon nanostructures: Exploring applications in sports training supervision

This study introduces an innovative approach to pressure sensing in sports training using amorphous silicon nanostructure-based sensors. These sensors demonstrated high sensitivity (0.75 Ω/kPa) and a broad pressure detection range (1–100 kPa), making them ideal for capturing the nuances of athletic movements. Their compact size (5 mm×5 mm) and superior durability (over 5000 cycles with minimal performance variation) allowed for seamless integration into athletic shoes and attire. The sensors effectively captured pressure patterns in running, such as heel strikes peaking at 300 kPa, and cycling, revealing a 200 kPa increase in the perineal region during posture shifts. Comparative analysis highlighted the advantages of amorphous silicon nanostructure sensors over existing technologies, including higher sensitivity, wider pressure range, smaller size, and better durability. The integration of these sensors provided invaluable data for optimizing training regimes and preventing injuries. The study also delved into the physical and chemical characterization of the nanostructures, confirming their uniform size distribution, surface morphology, and amorphous nature, which contributed to their exceptional sensing performance. The findings underscore the immense potential of amorphous silicon nanostructure sensors in revolutionizing athletic performance analysis and injury prevention, offering a significant upgrade over current technologies in terms of accuracy, adaptability, and user-friendliness. This research paves the way for more sophisticated, precise, and athlete-centric pressure sensing solutions, transforming the landscape of sports technology and biomechanical assessment.

Design, Fabrication, and Evaluation of 3D Biopotential Electrodes and Intelligent Garment System for Sports Monitoring.

This study presents the development and evaluation of an innovative intelligent garment system, incorporating 3D knitted silver biopotential electrodes, designed for long-term sports monitoring. By integrating advanced textile engineering with wearable monitoring technologies, we introduce a novel approach to real-time physiological signal acquisition, focusing on enhancing athletic performance analysis and fatigue detection. Utilizing low-resistance silver fibers, our electrodes demonstrate significantly reduced skin-to-electrode impedance, facilitating improved signal quality and reliability, especially during physical activities. The garment system, embedded with these electrodes, offers a non-invasive, comfortable solution for continuous ECG and EMG monitoring, addressing the limitations of traditional Ag/AgCl electrodes, such as skin irritation and signal degradation over time. Through various experimentation, including impedance measurements and biosignal acquisition during cycling activities, we validate the system's effectiveness in capturing high-quality physiological data. Our findings illustrate the electrodes' superior performance in both dry and wet conditions. This study not only advances the field of intelligent garments and biopotential monitoring, but also provides valuable insights for the application of intelligent sports wearables in the future.

Exploring CrossFit performance prediction and analysis via extensive data and machine learning.

The analysis of athletic performance has always aroused great interest from sport scientist. This study utilized machine learning methods to build predictive models using a comprehensive CrossFit (CF) dataset, aiming to reveal valuable insights into the factors influencing performance and emerging trends. Random forest (RF) and multiple linear regression (MLR) were employed to predict performance in four key weightlifting exercises within CF: clean and jerk, snatch, back squat, and deadlift. Performance was evaluated using R-squared (R2) values and mean squared error (MSE). Feature importance analysis was conducted using RF, XGBoost, and AdaBoost models. The RF model excelled in deadlift performance prediction (R2=0.80), while the MLR model demonstrated remarkable accuracy in clean and jerk (R2=0.93). Across exercises, clean and jerk consistently emerged as a crucial predictor. The feature importance analysis revealed intricate relationships among exercises, with gender significantly impacting deadlift performance. This research advances our understanding of performance prediction in CF through machine learning techniques. It provides actionable insights for practitioners, optimize performance, and demonstrates the potential for future advancements in data-driven sports analytics.

Athlete’s Performance Analysis Based on Improved Machine Learning Approach on Wearable Devices

Today, every nation strives for international recognition in a variety of sports. Governments invest in games and sports to raise the performance of their teams and athletes to get notoriety. Numerous people are involved in sports execution, including team management, coaches, and biomechanists who monitor athlete fitness and work to achieve remarkable results. Performance analysis is greatly aided by technological integration in sports management. The performance analysis of athletes is evaluated in this research using an upgraded machine learning approach on Improved Machine Learning approach on Wearable Devices (IMLA-WD). This design strategy utilizes wearable devices to collect health data, which is then fed into a machine-learning model to monitor athletes' progress. The athletes' performance is evaluated using standard machine learning methods, and the deep neural network monitors their health status. With a health prediction accuracy of 98.65%, the statistical findings of the proposed model demonstrate the highest performance compared to existing methodologies.

Summary of the Research Status of Artificial Intelligence in Sports Performance Analysis of Athletes

Summary of the Research Status of Artificial Intelligence in Sports Performance Analysis of Athletes

A Comparative Analysis Study on Para Athletics’ Track Discipline Change and Performance Trend in the Paralympic Games (2004–2020)

The Paralympics is a world-class sports event that inspires and impresses people around the world, of which athletics is the most medal-competitive event in the Paralympics, with more than 130 countries participating. This study aims to provide baseline data for disabled athletes’ (para athletes’) athletic performance improvement on track, by generating information on athletic performance trends through the identification of para athletics’ discipline change in each Paralympic Games (PG) held between 2004 and 2020, and by analyzing differences in records by discipline level (podium group [winners’ group] and final group [group reaching finals]). To achieve its purpose, this study collected data and analyzed athletics’ track events at five Paralympic Games (2004 Athens PG to 2020 Tokyo PG) organized by the International Paralympic Committee (IPC) and checked changes in disciplines. To analyze athletic performance differences between the podium group and the final group by dividing the disciplines in disabled athletes’ track events in the PG that were consecutively held into men’s division and women’s division, this study used Kruskal–Wallis Test, a nonparametric statistical method. Additionally, this study presented the drawn event record trends of the podium group by discipline in each class through visualization. The results drawn through this study are as follows: First, as a result of analyzing the change in disciplines of disabled athletes’ track events, the number of track disciplines in the 5 PG was Track (T) 61, T51, T52, T48, and T44, respectively. Disciplines in the men’s division showed a gradually decreasing trend. In the women’s division, the track disciplines in the 5 PG were T30, T33, T37, T40, and T36, respectively. The disciplines in the women’s division increased until the Rio 2016 PG. Second, according to an analysis of athletic performance by class of para athletes’ track disciplines by PG (2004–2020), significant differences were found in both the podium and final groups. Third, as a result of analyzing the podium group’s record change trends by para athletes’ track disciplines and classes, the following points were revealed: (1) in the mean record change in the men’s podium group records were improving in most classes; (2) according to the women’s podium group record trend analysis the record improvement was high in T37 and T53 classes. In the T11 and T12 classes improved in each PG. In conclusion, as the PG continued, the number of track events in the men’s division of para athlete disciplines decreased, but records show an improving trend. Meanwhile, the number of disciplines shows an increasing trend in the women’s division, and especially the trend was remarkable after 2012. In conclusion, as Paralympic Games continued, the number of disciplines declined in the men’s division but records show an improving trend. As the number of disciplines decreased, athletes went to other disciplines, so competition became fierce and competitiveness was judged to improve. Meanwhile, in the disciplines of the women’s division increased due to the increasing number of in disciplines available.

Design and testing of a capacitive interface for underwater stretch sensors

The growing popularity of wearable electronics has seen substantial research in soft and flexible strain sensors. From athletic performance analysis to human augmentation, there is a wide range of applications being developed. An area often overlooked is the connections between a network of wearable sensors and their measurement electronics. In dry applications this is as simple as cabling between the two. In underwater environments however this becomes more complicated. Capacitive strain sensors have been used to demonstrate underwater sensor-based motion capture in both a robotic fish and smart glove for divers. Wired connections introduced failure points and eliminated the modularity of the system for potted electronics. In this paper we have demonstrated the use of a capacitive interface as a wireless method to connect wearable strain sensors across an encapsulation to electronics. This removes the need to have wires permanently protruding through the encapsulation. The interfaces’ impact on strain sensor sensitivity and measurement method has been investigated for both resistive and capacitive-based strain sensing.

그룹운동 참여 여성의 신체적 자기효능감이 운동지속 및 생활만족도에 미치는 영향

이 연구는 그룹운동에 참여하는 여성의 신체적 자기효능감이 운동지속 및 생활만족도에 미치는 영향을 규명하는데 목적이 있다. 연구의 목적을 달성하기 위해 그룹운동에 참여하는 여성 400명을 연구 참여자로 선정하여, 그룹운동에 참여하는 여성의 신체적 자기효능감과 운동지속, 생활만족도에 관한 설문지를 배부하였다. 설문지는 비확률적 표집방법(non-probability sampling method)중 판단표본추출법(judgment sample)을 이용하여 표본을 추출하였으며, 설문응답 거부자와 이중기입 및 무 기입, 일괄 응답된 144를 제외한 총 256부의 설문지를 최종 유효표본으로 선정하여 분석하였다. 자료 분석 방법으로는 SPSS 26.0 Version을 이용하여 빈도분석(frequency Analysis), 탐색적 요인분석(exploratory factor analysis), 신뢰도분석(reliability analysis) 및 다중회귀분석(multiple Regression Analysis)을 실시하였다. 자료분석을 통해 도출된 결과는 다음과 같다. 첫째, 신체적 자기효능감 하위요인 모두 생활만족도에 통계적으로 유의한 영향을 미치는 것으로 나타났다. 둘째, 생활만족도 하위요인 모두 운동지속에 통계적으로 유의한 영향을 미치는 것으로 나타났다. 셋째, 신체적 자기효능감 하위요인 모두 운동지속에 통계적으로 유의한 영향을 미치는 것으로 나타났다. 본 연구를 통해 그룹운동에 참여하는 여성의 운동지속과 생활만족도의 향상을 위해서 신체적 자기효능감이 긍정적인 영향을 미치는 것으로 보이며, 신체적 자기효능감의 하위요인 중 운동참여 효능감의 영향이 가장 큰 것으로 나타나고 있다. 이에 신체적 자기효능감에 대한 중요성을 인지하고 여성이 참가하는 그룹운동 프로그램의 개발이 운동지속과 생활만족의 향상을 위해 필요할 것으로 판단된다.

Improvement of the passing quality of an American football training machine

In American football, high quality training focused on catching is currently not done with passing machines due to their poor pass accuracy and precision. From a coach’s point of view, accurate and precise passing machines are needed to relieve the quarterback from too much training effort. The two aims of this study were to increase the precision of a passing machine and develop an accurate pass prediction model for it. To meet the two aims and provide evidence that a passing machine can be precise and accurate enough for high quality training, an automated passing machine was developed and two experiments were carried out. The results of the first experiment showed that the machine performs with a precision within ±1% of the throwing distance for 218 of the 225 passes. The second experiment resulted in a pass prediction model, which is based on 55 videos and a fitting approach using a neural network. The model estimates the machine configuration for a pass to a targeted point in space. In regard to precision and accuracy, the performance of the machine exceeds the performance of a skilled quarterback. This project improves the state of the art of passing machines for American football and opens possibilities for research in various fields like motion analysis for catches, hand-eye coordination and performance analysis of athletes.

Automated Activity Recognition with Gait Positions Using Machine Learning Algorithms

Exoskeletons are wearable devices for enhancing human physical performance and for studying actions and movements. They are worn on the body for additional power and load-carrying capacity. Exoskeletons can be controlled using signals from the muscles. In recent years, gait analysis has attracted increasing attention from fields such as animation, athletic performance analysis, and robotics. Gait patterns are unique, and each individual has his or her own distinct gait pattern characteristics. Gait analysis can monitor activity in sensitive areas. This paper uses various machine learning algorithms to predict the activity of subjects using exoskeletons. Here, localization data from the UIC machine learning repository are used to recognize activities with gait positions. The study also compares five machine learning methods and examines their efficiency and accuracy in activity prediction for three different subjects. The results for the various machine learning methods along with efficiency and accuracy results are discussed.

Ambulatory measurement of three-dimensional foot displacement during treadmill walking using wearable wireless ultrasonic sensor network.

Techniques that could be used to monitor human motion precisely are helpful in various applications such as rehabilitation, gait analysis, and athletic performance analysis. This paper focuses on the 3-D foot trajectory measurements based on a wearable wireless ultrasonic sensor network. The system consists of an ultrasonic transmitter (mobile) and several receivers (anchors) with fixed known positions. In order not to restrict the movement of subjects, a radio frequency (RF) module is used for wireless data transmission. The RF module also provides the synchronization clock between mobile and anchors. The proposed system measures the time-of-arrival (TOA) of the ultrasonic signal from mobile to anchors. Together with the knowledge of the anchor's position, the absolute distance that the signal travels can be computed. Then, the range information defines a circle centered at this anchor with radius equal to the measured distance, and the mobile resides within the intersections of several such circles. Based on the TOA-based tracking technique, the 3-D foot trajectories are validated against a camera-based motion capture system for ten healthy subjects walking on a treadmill at slow, normal, and fast speeds. The experimental results have shown that the ultrasonic system has sufficient accuracy of net root-mean-square error ( 4.2 cm) for 3-D displacement, especially for foot clearance with accuracy and standard deviation ( 0.62 ±7.48 mm) compared to the camera-based motion capture system. The small form factor and lightweight feature of the proposed system make it easy to use. Such a system is also much lower in cost compared to the camera-based tracking system.

Relationship between performance in game actions and the match result. A study in volleyball training stages

In recent years, a number of quantitative methods have been identified and developed with the specific intent of assisting the objective analysis of athletic performance (Nelson & Groom, 2012). The main aim of this research was to clarify the importance of performance in game actions as determinant of match result in a sample of young volleyball male players. The study sample was composed of 74 male participants belonging to the Under-16 teams (M: 14.61; SD: .88) from the Extremadura Volleyball League in the 2010/2011 season. The studied variables were: performance in game actions (serve, defense, setting and spike) and match result (win/lost). FIVB Observational System (Coleman, 1975) has been the instrument for data recollection, it has been applied previously in numerous studies and is accepted as a valid tool for research community. The T-test for independent samples results showed statistically significant differences in performance of game actions: serve (F1,72= 3.86; p=.048; np2=.492), defense (F1,72=14.07; p<.001.; np2=.959), setting (F1,72=34.83; p<.001.; np2=1.00) and spike (F1,72=9.05 ; p=.004; np2=.84) between players from winner and loser teams. Our results coincide with previous studies that emphasize the importance of game actions in volleyball (Asterios et al., 2009). This analysis is important as it assists in the collection of performance information that can feedback athletes in an attempt to enhance their understanding and competitive performance (Maslovat & Franks, 2008) and also for talent identification and recruitment (Carling et al., 2005).

The analysis of athletic performance: some practical and philosophical considerations

This article presents a hypothetical dialogue between a notational analyst (NA) recently schooled in the positivistic assessment of athletic performance, an ‘old-school’ traditional coach (TC) who favours subjective analysis, and a pragmatic educator (PE). The conversation opens with NA and TC debating the respective value of quantitative and qualitative methods of performance analysis. Having considered their arguments from a-distance, PE offers a philosophically underpinned point of view that helps to practically reconcile NA's and TC's opposing positions. While primarily focusing on practical issues relating to the analysis of athletic performance, PE contends that ‘quantitative’ and ‘qualitative’ approaches can be legitimately used in combination. Such a stance would appear in-line with a pragmatic philosophical perspective, which by focusing on practical issues embraces pluralistic methods. It is hoped that this dialogue will facilitate further philosophical and practical debate to generate knowledge that could enrich coaches' understanding by presenting an approach to performance analysis that is more realistic for practitioners.

스포츠정보 데이터 추출을 위한 실험적 솔루션으로서의 뉴로마케팅

This study brings to the forefront possible implications of the neuro-marketing technology as a more scientific research technique that is expected to replace the traditional consumer study in many cases, exploring beneficial aspects of that technology, which aims at appealing to consumers at the unconscious level. Neuro-marketing that claims to be grounded in brain science is still in a fledgling stage. However, as demand from the industry grows, this new area appears to get more and more attention from the academic community. Especially a plurality of approaches to neuro-marketing research are already found in the areas of product and design development, brand power creation, and effective advertising, and this robust academic interest has led to several successful cases of industrial applications. The promising areas where neuro-science can be applied to the sports-related industry range from advertisement effect analysis of sports events, to analysis of spacial layout for sports product stores and sports facilities, sports-related brand image analysis, design effect analysis and testing in sports products, and analysis of athletic performance at sports venues. At this time, making more efforts to advance research in the field of combining neuro-science and sports science, in addition to those academic initiatives so far, will contribute to gaining a stronger foothold for sports science.

Improved wireless tracking for indoor sports

Wireless tracking technology is being used in a wide range of applications including performance analysis of athletes. While GPS is commonly used in outdoor environments, there are no widely deployed solutions for indoor environments to date. Indoor sports venues are often fabricated using metal structures and cladding which create difficult radio propagation environments for localization. In this paper we present a new algorithm based on measurement of time of arrival with greatly reduced susceptibility to multipath interference. Data has been collected in an indoor netball court using the WASP localization system that we developed. Using this data we show that our algorithm is able to reliably and accurately track multiple players under conditions in which conventional localization algorithms fail.

Human Motion Analysis: A Review

Human motion analysis is receiving increasing attention from computer vision researchers. This interest is motivated by a wide spectrum of applications, such as athletic performance analysis, surveillance, man–machine interfaces, content-based image storage and retrieval, and video conferencing. This paper gives an overview of the various tasks involved in motion analysis of the human body. We focus on three major areas related to interpreting human motion: (1) motion analysis involving human body parts, (2) tracking a moving human from a single view or multiple camera perspectives, and (3) recognizing human activities from image sequences. Motion analysis of human body parts involves the low-level segmentation of the human body into segments connected by joints and recovers the 3D structure of the human body using its 2D projections over a sequence of images. Tracking human motion from a single view or multiple perspectives focuses on higher-level processing, in which moving humans are tracked without identifying their body parts. After successfully matching the moving human image from one frame to another in an image sequence, understanding the human movements or activities comes naturally, which leads to our discussion of recognizing human activities.

Fractal (power law) analysis of athletic performance

The human body involves the complex interaction between many feedback systems. This is certainly indicative that we are basically a nonlinear organism. Recent developments in the understanding of nonlinear systems suggest that fractal (power law) relationships may be the rule, not the exception. In this article it is shown that the performance of male and female superior athletes exhibits a fractal relationship between world record running and swimming times and the distance of the event. Furthermore, the precision of this relationship is so accurate that the small deviations exhibited by data from a fractal fit might be explained using the dominant interplay between aerobic and anaerobic energy expenditure.

Analysis of athletic performance with prophylactic ankle devices

We evaluated the effect of different ankle support devices on athletic performance. Thirty varsity college athletes were tested with both ankles supported by taping, Swede-O brace, Kallassy brace or left unsupported. The athletes performed four events: broad jump, vertical leap, 10 yard shuttle run, and 40 yard sprint. The events and appliances were randomized to prevent bias by fatigue. Compared to the results when no support was used, ankle taping resulted in a significant decreased performance in the vertical jump (4%), shuttle run (1.6%), and sprint (3.5%) (P less than 0.05). Use of the Swede-O brace decreased performance in the vertical jump (4.6%), broad jump (3.6%), and time of the sprint (3.2%). Results using the Kallassy brace showed a decrease in the vertical jump (3.4%) when compared to no support. The test results of the shuttle run with taping were slower than the Kallassy brace (P less than 0.05). Wearing the Swede-O brace caused the athletes' broad jump distance to decrease more than the Kallassy brace (P less than 0.05). Subjective questionnaires supported the Kallassy brace as the most comfortable support and the one that decreased performance the least. Taping of the ankles is universally accepted for ankle prophylaxis. This study has shown a decrease in performance when ankles are taped compared to ankles with no protection. Since the decreases in performance caused by ankle braces are minor, this should not be used as a criterion for selection of prophylactic support compared to taping.

Analysis of athletic performance with prophylactic ankle devices

We evaluated the effect of different ankle support devices on athletic performance. Thirty varsity college athletes were tested with both ankles supported by taping, Swede-O brace, Kallassy brace or left unsupported. The athletes performed four events: broad jump, vertical leap, 10 yard shuttle run, and 40 yard sprint. The events and appliances were randomized to prevent bias by fatigue. Compared to the results when no support was used, ankle taping resulted in a significant decreased performance in the vertical jump (4%), shuttle run (1.6%), and sprint (3.5%) (P less than 0.05). Use of the Swede-O brace decreased performance in the vertical jump (4.6%), broad jump (3.6%), and time of the sprint (3.2%). Results using the Kallassy brace showed a decrease in the vertical jump (3.4%) when compared to no support. The test results of the shuttle run with taping were slower than the Kallassy brace (P less than 0.05). Wearing the Swede-O brace caused the athletes' broad jump distance to decrease more than the Kallassy brace (P less than 0.05). Subjective questionnaires supported the Kallassy brace as the most comfortable support and the one that decreased performance the least. Taping of the ankles is universally accepted for ankle prophylaxis. This study has shown a decrease in performance when ankles are taped compared to ankles with no protection. Since the decreases in performance caused by ankle braces are minor, this should not be used as a criterion for selection of prophylactic support compared to taping.