Sports Applications Research Articles

Influence of Marketing Mix Strategy on Business Arena Corner

The impact of digital development has made a new standard for Startup companies in winning competitions and can still compete in winning customer satisfaction. This makes startup companies compete to formulate a suitable strategy in a very tight competition through marketing strategies applied by each company. This research was conducted to determine how much influence the 7P marketing strategy run by Startup Arena Corner engaged in the digital application of sports venues in Jakarta. This paper reviews literature from past studies related to the mixed concepts of marketing and descriptive analysis used to analyze the best practices of 7P marketing strategies implemented today. The method is to apply all aspects of 7P the marketing strategy with the scenario that Arena Corner will run, compared to the theory that has been led to marketing mix 7P. The results of this study explain that the implementation of Arena Corner's marketing strategy has been fully integrated, both conventional and digital solid marketing implementation so that it is expected that customers can get satisfaction with Arena Corner's products and services. In addition, it is also necessary for customers to feel the user experience that is inherent in the minds of consumers so that Arena Corner can win the hearts of its customers and new consumers. Keywords: Marketing Mix 7P, Strategic Marketing, Business Plan, Arena Corner..

Comparison of Shear Wave Elastography and Dynamometer Test in Muscle Tissue Characterization for Potential Medical and Sport Application.

Skeletal muscle status and its dynamic follow up are of particular importance in the management of several diseases where weight and muscle mass loss and, consequently, immobilization occurs, as in cancer and its treatment, as well as in neurodegenerative disorders. But immobilization is not the direct result of body and muscle mass loss, but rather the loss of the maximal tension capabilities of the skeletal muscle. Therefore, the development of a non-invasive and real-time method which can measure muscle tension capabilities in immobile patients is highly anticipated. Our aim was to introduce and evaluate a special ultrasound measurement technique to estimate a maximal muscle tension characteristic which can be used in medicine and also in sports diagnostics. Therefore, we determined the relationship between the results of shear wave elastography measurements and the dynamometric data of individuals. The measurements were concluded on the m. vastus lateralis. Twelve healthy elite athletes took part in our preliminary proof of principle study—five endurance (S) and seven strength (F) athletes showing unambiguously different muscle composition features, nine healthy subjects (H) without prior sports background, and four cancer patients in treatment for a stage 3 brain tumor (T). Results showed a high correlation between the maximal dynamometric isometric torque (Mmax) and mean elasticity value (E) for the non-athletes [(H + T), (r = 0.795)] and for the athletes [(S + F), (r = 0.79)]. For the athletes (S + F), the rate of tension development at contraction (RTDk) and E correlation was also determined (r = 0.84, p < 0.05). Our measurements showed significantly greater E values for the strength athletes with fast muscle fiber dominance than endurance athletes with slow muscle fiber dominance (p < 0.05). Our findings suggest that shear wave ultrasound elastography is a promising method for estimating maximal muscle tension and, also, the human skeletal muscle fiber ratio. These results warrant further investigations with a larger number of individuals, both in medicine and in sports science.

ISB recommendations for skin-marker-based multi-segment foot kinematics

The foot is anatomically and functionally complex, and thus an accurate description of intrinsic kinematics for clinical or sports applications requires multiple segments. This has led to the development of many multi-segment foot models for both kinematic and kinetic analyses. These models differ in the number of segments analyzed, bony landmarks identified, required marker set, defined anatomical axes and frames, the convention used to calculate joint rotations and the determination of neutral positions or other offsets from neutral. Many of these models lack validation. The terminology used is inconsistent and frequently confusing. Biomechanical and clinical studies using these models should use established references and describe how results are obtained and reported.The International Society of Biomechanics has previously published proposals for standards regarding kinematic and kinetic measurements in biomechanical research, and in this paper also addresses multi-segment foot kinematics modeling. The scope of this work is not to prescribe a particular set of standard definitions to be used in all applications, but rather to recommend a set of standards for collecting, calculating and reporting relevant data.The present paper includes recommendations for the overall modeling and grouping of the foot bones, for defining landmarks and other anatomical references, for addressing the many experimental issues in motion data collection, for analysing and reporting relevant results and finally for designing clinical and biomechanical studies in large populations by selecting the most suitable protocol for the specific application.These recommendations should also be applied when writing manuscripts and abstracts.

Motion recognition technology of badminton players in sports video images

Intelligent identification technology has made great progress in transportation, and its application in sports has attracted widespread attention. This research mainly discusses the research of human motion recognition technology in sports dance video images. In geometric algebraic space, using instance templates, a new cfrdF method, using css-based similarity of human body features as features, to construct an angle-adaptive and continuous-scale space template matching algorithm to calculate the similarity between horizontal plates and detected images value, set a certain threshold, so as to match the area where the human body is located. Based on the actual video analysis and display, using the self-similar structure of the color of the human object as the basic feature, it is described by the geometric algebra method, and the human body in the video image is extracted using template convolution objects and design adaptive template functions to extract human movements from sports dance video images. By loading each test video in turn, the posture of the characters in the video is checked every 30 s, and the approximate positions of the head and feet are marked and output to a txt file. Because lying on the ground during sports dance is a way of matching by height correction, the accuracy is less disturbed, but it can still reach 90.9%. The research results show that the template matching robot model proposed in this paper can accurately and robustly extract human objects in video.

Influence of sports applications on college students' exercise behaviors and habits: A thematic analysis

Evolution in digital technology is bringing improvements in the lifestyle and behaviors of ordinary people throughout the world. In recent years, research is undertaken to investigate the penetration of web-based sports applications in students' recreational activities. This study uses a systematic thematic analysis to analyze the literature on the research topic. We perform a rigorous thematic analysis on the qualitative information from ten chosen studies, following the particular data analysis model with five steps: compilation, disassembling, reassembling, interpreting, and concluding. This study's results show that technology-based motivation among students is widely explored in the literature. The exercise environment and behavioral diversity are other identified codes (data units) in the chosen literature. This study finds that the use of technology can effectively promote higher participation of students in low-intensity exercises.

A Review of Deep Learning-Based Contactless Heart Rate Measurement Methods.

The interest in contactless or remote heart rate measurement has been steadily growing in healthcare and sports applications. Contactless methods involve the utilization of a video camera and image processing algorithms. Recently, deep learning methods have been used to improve the performance of conventional contactless methods for heart rate measurement. After providing a review of the related literature, a comparison of the deep learning methods whose codes are publicly available is conducted in this paper. The public domain UBFC dataset is used to compare the performance of these deep learning methods for heart rate measurement. The results obtained show that the deep learning method PhysNet generates the best heart rate measurement outcome among these methods, with a mean absolute error value of 2.57 beats per minute and a mean square error value of 7.56 beats per minute.

Energy-efficient IoT based improved health monitoring system for sports persons

Nowadays, wearable technology and the Internet of Things (IoT) are transforming the healthcare sector by refining the way how devices, applications, and people connect and interact with each other. IoT applications in sports are tremendously useful to monitor health and reduce the risk factor. The battery life of wearable and accurate monitoring has been considered a significant challenge in sports medicine. Hence, in this paper, Energy Efficient IoT based Improved Health Monitoring system (EEIoT-IHMS) has been proposed for accurate and continuous sports person’s health monitoring system. This paper determines the optimal set of clusters based on sensor features, in which power usage has been minimized by duty cycling with optimized prediction accuracy. The experimental results demonstrate that the proposed (EEIoT-IHMS) enhances accuracy ratio, improves battery life, and reduces energy consumption compared to other popular methods.

A Portable and Flexible Self-Powered Multifunctional Sensor for Real-Time Monitoring in Swimming.

A portable and flexible self-powered biosensor based on ZnO nanowire arrays (ZnO NWs) and flexible PET substrate has been designed and fabricated for real-time monitoring in swimming. Based on the piezoelectric effect of polar ZnO NWs, the fabricated biosensor can work in both air and water without any external power supply. In addition, the biosensor can be easily attached to the surface of the skin to precisely monitor the motion state such as joint moving angle and frequency during swimming. The constant output piezoelectric signal in different relative humidity levels enables actual application in different sports, including swimming. Therefore, the biosensor can be utilized to monitor swimming strokes by attaching it on the surface of the skin. Finally, a wireless transmitting application is demonstrated by implanting the biosensor in vivo to detect angiogenesis. This portable and flexible self-powered biosensor system exhibits broad application prospects in sport monitoring, human–computer interaction and wireless sport big data.

Tracking rower motion without on-body sensors using an instrumented machine and an artificial neural network

Human motion tracking is an active field of research driven by its diverse applications in areas such as health care, daily activity recognition, sports, etc. In sports applications, tracking rowing motion is performed to meet several goals, including prevention of injuries, improvement of performance or provision of virtual coaching. Different established approaches rely on on-body sensors to capture rowing motion. While on-body sensors are effective and straight forward to implement, they can disturb the athlete and negatively impact the training. In this paper, an approach is presented to track rowing motion without body-worn sensors or cameras. Instead, sensors were attached to an indoor rowing machine that tracked the motion of its sliding seat, lever handle and the force exercised on the seat. In particular, the motion was tracked by means of linear and angular displacement sensors, as well as force sensors placed underneath the seat. The respective variables were fed into an Artificial Neural Network (ANN) to predict the coordinates of the rower’s shoulder, which in turn, were used to geometrically infer the angles of the shoulder, elbow, hip and thoracolumbar flexion-extension. A successful ANN architecture was iteratively designed by using the Levenberg-Marquardt algorithm and varying the number of hidden neurons in one hidden layer. A comparison between ANN-predicted and experimentally obtained shoulder coordinates from an optical motion capture system showed a mean error of less than 4 cm, which led to an angle mean error value as low as 2.01°. A rigged avatar was used to visually verify the reproduced motion. The avatar animation was well-received by experts, especially considering the shoulder adduction-abduction in the frontal plane.

Recovery profiles of eccentric hamstring strength in response to cooling and compression

IntroductionThe effectiveness of different forms of cryotherapy and combined compression (cryo-compression) commonly used in sport to enhance recovery following exercise are not fully understood. Therefore, the exploration of protocols that use contemporary cryo-compression is warranted. The purpose of the study was to investigate the effectiveness of using a cryo-compression device to recover hamstrings eccentric strength following a fatiguing exercise. MethodsEighteen healthy male adult footballers were randomly allocated to receive cryo-compression or rest following a lower limb fatiguing protocol. Cryo-compression was applied for 15-min, target temperature of 10 °C, and high intermittent pressure (5–75 mm Hg) using the Game Ready® device. Rest consisted of 15-min in a prone position on a plinth. To induce hamstring fatigue, participants performed the Yo-Yo intermittent fatigue test (IFT). Skin surface temperature (Tsk) and hamstring eccentric strength measures were taken at three time points; pre-IFT, immediately post-fatigue test (IPFT), and immediately post-intervention (IPI) (rest or Game Ready®). Participants returned one week later and performed the Yo-Yo IFT again and were exposed to the opposite intervention and data collection. ResultsSignificant decreases in Tsk over the posterior thigh were reported for all timepoints compared to pre cryo-compression temperatures (p=<0.05). Overall data displayed no significant main effects for timepoint or condition for PT or AvT (p=<0.05). There was no timepoint × condition interaction for PT or AvT (p=<0.05). Collapse of the data by condition (CC/R) demonstrated no significant effect for time for PT or AvT (p=>0.05). ConclusionsNo significant changes in HES occurred after exposure to cryo-compression or rest applied immediately following the Yo-Yo IFT. Further investigations to maximise beneficial application of contemporary cryo-compression applications in sport are required. Multiple measures of performance over rewarming periods, within competitive training schedules after sport-specific training are required to develop optimal cooling protocols for recovery.

Oxidized Hemp Fibers with Simultaneously Increased Capillarity and Reduced Moisture Sorption as Suitable Textile Material for Advanced Application in Sportswear

Applications of hemp fibers, as a promising natural material in the textile field, mostly require improved fiber properties. In this paper, the oxidation of hemp fibers with potassium permanganate was applied to reduce the amount of non-cellulosic substances and moisture sorption; to introduce functional groups and increase capillarity; make fibers finer, softer and suitable for application in sport wears. The changes in sorption properties were characterized by capillary rise measurement and the ability of water retention and moisture sorption, while changes in mechanical properties were estimated by determination of tenacity and elongation of modified hemp fibers in comparison to the appropriate characteristic of unmodified fibers. ATR-FTIR, SEM techniques, and zeta potential measurement were used for the characterization of fiber structure, morphological and electrokinetic properties. We obtained a finer fiber with increased capillarity (up to 3.68 times) but reduced moisture sorption (down to 1.5 times) and water retention capacity (down to 2.8 times), with accomplished satisfactory preservation of mechanical properties. Obtained oxidized hemp fibers with attained features present a very suitable material for sportswear production. Additionally, in this paper, an improvement of the capillary rise measurement is given.

A STEM Model to Engage Students in Sustainable Science Education through Sports: A Case Study in Qatar

Sports has the potential to integrate with different scientific subjects, including materials science and engineering, making it an ideal approach to enhance the students’ affinity toward sustainable education in science, technology, engineering, and mathematics (STEM). Amid gradual educational reformations in the state of Qatar, a distinctive STEM program titled, “Science in Sports” (SIS) was launched to investigate STEM integrated learning in secondary school students. The participant students, 248 students (112 females and 136 males) from 15 different government-operated (public) secondary schools, from rural and urban areas, were given STEM workshops on one of the sports materials, during this pilot study, resultantly challenging them to engineer a sports product. The study employed a mixed-method study in which quantitative approaches were applied to analyze the program effectiveness, with a t-test statistical analysis performed over data collected from a period of five continuous years from 2012 to 2017 in five different cycles. A more dominant data collection included pre and post surveys, substantiating observations of the program facilitator and their schoolteachers were included in this research and development (R&amp;D) study to review the student learning behavior for a qualitative approach. Moreover, the results of the strength, weakness, opportunities, and threats (SWOT) analysis provided an overview of the program’s effectiveness in implicating the engagement of the students in exhibiting their prototypical skills in engineering sports products along with STEM literacy. Apart from understanding the scientific concepts/principles applied in simple sports applications, student attitudes toward STEM fields augmented, as witnessed by the student productivity.

Highly Sensitive Porous PDMS-Based Capacitive Pressure Sensors Fabricated on Fabric Platform for Wearable Applications.

A novel porous polydimethylsiloxane (PDMS)-based capacitive pressure sensor was fabricated by optimizing the dielectric layer porosity for wide-range pressure sensing applications in the sports field. The pressure sensor consists of a porous PDMS dielectric layer and two fabric-based conductive electrodes. The porous PDMS dielectric layer was fabricated by introducing nitric acid (HNO3) into a mixture of PDMS and sodium hydrogen bicarbonate (NaHCO3) to facilitate the liberation of carbon dioxide (CO2) gas, which induces the creation of porous microstructures within the PDMS dielectric layer. Nine different pressure sensors (PS1, PS2,..., PS9) were fabricated in which the porosity (pore size, thickness) and dielectric constant of the PDMS dielectric layers were varied by changing the curing temperature, the mixing proportions of the HNO3/PDMS concentration, and the PDMS mixing ratio. The response of the fabricated pressure sensors was investigated for the applied pressures ranging from 0 to 1000 kPa. A relative capacitance change of ∼100, ∼323, and ∼485% was obtained by increasing the curing temperature from 110 to 140 to 170 °C, respectively. Similarly, a relative capacitance change of ∼170, ∼282, and ∼323% was obtained by increasing the HNO3/PDMS concentration from 10 to 15 to 20%, respectively. In addition, a relative capacitance change of ∼94, ∼323, and ∼460% was obtained by increasing the PDMS elastomer base/curing agent ratio from 5:1 to 10:1 to 15:1, respectively. PS9 exhibited the highest sensitivity over a wide pressure sensing range (low-pressure ranges (<50 Pa), 0.3 kPa-1; high-pressure ranges (0.2-1 MPa), 3.2 MPa-1). From the results, it was observed that the pressure sensors with dielectric layers prepared at relatively higher curing temperatures, higher HNO3 concentrations, and higher PDMS ratios resulted in increased porosity and provided the highest sensitivity. As an application demonstrator, a wearable fit cap was developed using an array of 16 pressure sensors for measuring and mapping the applied pressures on a player's head while wearing a helmet. The pressure mapping aids in observing and understanding the proper fit of the helmet in sports applications.

Wireless ECG and cardiac monitoring systems: State of the art, available commercial devices and useful electronic components

Wireless ElectroCardioGram (ECG) systems are employed in manifold application fields: tele-monitoring, sport applications, support to ageing people at home, fetal ECG, wearable devices and ambulatory monitoring. The presence of cables often hinders user’s free movements, alongside clinicians’ routine operations. Therefore, wireless ECG systems are desirable. This paper aims at reviewing the solutions described in the literature, besides commercially available devices and electronic components useful to setup laboratory prototypes. Several systems have been developed, different in terms of the adopted technology; when approaching the development of a wireless ECG system, some important aspects should be considered: electrodes (disposable, wet/dry, without contact, insulated), analog front-end, data acquisition systems (including amplifiers, multiplexer), wireless transmission technology (e.g. WiFi, Bluetooth) and power consumption (battery lifetime, miniaturization purposes). Technological advancements and continuous research have already brought to miniaturized and comfortable devices, but there is still room for improvement on multiple sides.

Design of Intelligent Assistant System for Billiards Hit Training

Image processing technology has increasing important applications in sports in recent years, such as result prediction, technical analysis, and foul determination. For most billiards beginners, how to hit the billiard ball into the ball belt is not a simple matter. In order to assist the beginners in billiards training, this article proposes an assisted hitting system. The system is divided into three parts: bag detection, billiard detection, and hitting suggestions. In the ball belt detection, double-peak histogram threshold segmentation, edge detection and Hough transform are used to detect the edge line, and then the ball belt position is detected. In billiard ball detection, the normalized RGB method is used to extract the foreground, the Hough transform circle detection method is used to detect the center and radius of the sphere, and the neural network is used to determine the white ball. In the shot suggestion, the force and angle of the shot are given by the dynamic formula, and the path simulation of the ball in the background is given. Experiments show that the recognition method is effective and the path simulation is consistent with reality, which can assist beginners in the training of billiards to a large extent.

The Design and Simulation of a 16-Sensors Plantar Pressure Insole Layout for Different Applications: From Sports to Clinics, a Pilot Study.

The quantification of plantar pressure distribution is widely done in the diagnosis of lower limbs deformities, gait analysis, footwear design, and sport applications. To date, a number of pressure insole layouts have been proposed, with different configurations according to their applications. The goal of this study is to assess the validity of a 16-sensors (1.5 × 1.5 cm) pressure insole to detect plantar pressure distribution during different tasks in the clinic and sport domains. The data of 39 healthy adults, acquired with a Pedar-X® system (Novel GmbH, Munich, Germany) during walking, weight lifting, and drop landing, were used to simulate the insole. The sensors were distributed by considering the location of the peak pressure on all trials: 4 on the hindfoot, 3 on the midfoot, and 9 on the forefoot. The following variables were computed with both systems and compared by estimating the Root Mean Square Error (RMSE): Peak/Mean Pressure, Ground Reaction Force (GRF), Center of Pressure (COP), the distance between COP and the origin, the Contact Area. The lowest (0.61%) and highest (82.4%) RMSE values were detected during gait on the medial-lateral COP and the GRF, respectively. This approach could be used for testing different layouts on various applications prior to production.

TRAINING SPORT COACHES FOR ATHLETES WITH INTELLECTUAL DISABILITIES: THE TEAMUP PROJECT

This paper presents the Erasmus + TeamUp project which aimed to provide basic skills and knowledge to sport coaches in order to enable them to work with individuals with intellectual disability (ID) and act as facilitators in their own country and local community transmitting this knowledge and values. The rationale for conducting the program is analyzed and its aims and objectives are described, with emphasis given on all relative educational material developed for application in sport and physical education settings. In particular, one of the main activities of the program was the development of the educational package by the Department of Physical Education and Sport Science, University of Thessaly, aiming to increase knowledge and skills of sport coaches in three different chapters concerning ID, Special Olympics and Paralympic Games, individualized education programming and physical activity adaptations and inclusion strategies for athletes with ID, respectively. Dissemination of this educational package and results of sport coaches’ responses from Greece, Croatia, Romania and Spain to three online questionnaires relative to the three topics created, are also presented and analyzed. Finally, practical implications and suggestions for further development are discussed. &#x0D; &#x0D; &lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0728/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Multimodal Sensor Fusion for Low-Power Wearable Human Motion Tracking Systems in Sports Applications

This paper presents a prototype human motion tracking system for wearable sports applications. It can be particularly applicable for tracking human motion during executing certain strength training exercises, such as the barbell squat, where an inappropriate technique could result in an injury. The key novelty of the proposed system is twofold. Firstly, it is an inside-out, multimodal, motion tracker that incorporates two complementary sensor modalities, i.e. a camera and an inertial motion sensor, as well as two externally-mounted points of reference. Secondly, it incorporates a novel multimodal sensor fusion algorithm which uses the complementary nature of vision and inertial sensor modalities to perform a computationally efficient 3-Dimensional (3-D) pose detection of the wearable device. The 3-D pose is determined by fusing information about the two external reference points captured by the camera together with the orientation angles captured by the inertial motion sensor. The accuracy of the prototype was experimentally validated in laboratory conditions. The main findings are as follows. The Root Mean Square Error (RMSE) in 3-D position calculation was 36.7 mm and 13.6 mm in the static and mobile cases, respectively. Whereas the static case was aimed at determining the system's performance at all 3-D poses within the work envelope, the mobile case was used to determine the error in tracking human motion that is involved in the barbell squat, i.e. a mainly repeated vertical motion pattern.

The Impact of Vigorous Cycling Exercise on Visual Attention: A Study With the BR8 Wireless Dry EEG System

Many studies have reported that exercise can influence cognitive performance. But advancing our understanding of the interrelations between psychology and physiology in sports neuroscience requires the study of real-time brain dynamics during exercise in the field. Electroencephalography (EEG) is one of the most powerful brain imaging technologies. However, the limited portability and long preparation time of traditional wet-sensor systems largely limits their use to laboratory settings. Wireless dry-sensor systems are emerging with much greater potential for practical application in sports. Hence, in this paper, we use the BR8 wireless dry-sensor EEG system to measure P300 brain dynamics while cycling at various intensities. The preparation time was mostly less than 2 min as BR8 system’s dry sensors were able to attain the required skin-sensor interface impedance, enabling its operation without any skin preparation or application of conductive gel. Ten participants performed four sessions of a 3 min rapid serial visual presentation (RSVP) task while resting and while cycling. These four sessions were pre-CE (RSVP only), low-CE (RSVP in 40–50% of max heart rate), vigorous-CE (RSVP in 71–85% of max heart rate) and post-CE (RSVP only). The recorded brain signals demonstrate that the P300 amplitudes, observed at the Pz channel, for the target and non-target responses were significantly different in all four sessions. The results also show decreased reaction times to the visual attention task during vigorous exercise, enriching our understanding of the ways in which exercise can enhance cognitive performance. Even though only a single channel was evaluated in this study, the quality and reliability of the measurement using these dry sensor-based EEG systems is clearly demonstrated by our results. Further, the smooth implementation of the experiment with a dry system and the success of the data analysis demonstrate that wireless dry EEG devices can open avenues for real-time measurement of cognitive functions in athletes outside the laboratory.

Acceleration Feature Extraction of Human Body Based on Wearable Devices

Wearable devices used for human body monitoring has broad applications in smart home, sports, security and other fields. Wearable devices provide an extremely convenient way to collect a large amount of human motion data. In this paper, the human body acceleration feature extraction method based on wearable devices is studied. Firstly, Butterworth filter is used to filter the data. Then, in order to ensure the extracted feature value more accurately, it is necessary to remove the abnormal data in the source. This paper combines Kalman filter algorithm with a genetic algorithm and use the genetic algorithm to code the parameters of the Kalman filter algorithm. We use Standard Deviation (SD), Interval of Peaks (IoP) and Difference between Adjacent Peaks and Troughs (DAPT) to analyze seven kinds of acceleration. At last, SisFall data set, which is a globally available data set for study and experiments, is used for experiments to verify the effectiveness of our method. Based on simulation results, we can conclude that our method can distinguish different activity clearly.