Upper Extremity Pain Is Associated with Lower Back Pain among Young Basketball Players: A Cross-Sectional Study

Hagiwara, Yoshihiro; Yabe, Yutaka; Sekiguchi, Takuya; Momma, Haruki; Tsuchiya, Masahiro; Kanazawa, Kenji; Yoshida, Shinichirou; Sogi, Yasuhito; Yano, Toshihisa; Onoki, Takahiro; Itoi, Eiji; Nagatomi, Ryoichi

doi:10.1620/tjem.250.79

Cited by 15 publications

(27 citation statements)

References 23 publications

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“…In the process of setting up the principle model of the goal system of basketball players, the action point of the joint force when the ball is thrown is calculated, the action point of the joint force transmitted by the femoral head of the human body is shifted outward, the stress distribution curve of the femur under the action of the force on the femoral head is obtained, and the principal model of the goal system of basketball players is established [13,14]. e specific steps are described as follows:…”

Section: Principle Model Of Goal System For Basketball Playersmentioning

confidence: 99%

“…In formula (13), ε represents the regularization parameter, w represents the number of classifiers, f represents the training function, x i and y i represent the independent and dependent variables of the function, and i represents the training times. To prevent fitting in the classifier training process, the optimal solution of the aforementioned calculation formula ( 13) is taken, and the calculation formula of the optimal solution can be expressed in the following equation:…”

Section: Build Team Strength Evaluation Algorithmmentioning

confidence: 99%

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Evaluation Algorithm for Team Strength Based on the Collected Healthcare Data through IoT and Smart Devices

Qiao¹

2022

Journal of Healthcare Engineering

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In the past, the fans used to evaluate the strength of the team according to the victory and defeat ranking or according to their own intuition and preferences, however, the strength of the team is difficult to measure in analytical figures. The team’s winning rate is not the only factor to be considered to determine the strength of the team. There are many factors to be considered for determining the strength of the team. According to the variation coefficient of basketball scoring frequency, the paper designs the principal model of basketball players’ pitching target system. The data is captured by IoT devices and smart devices. The algorithm sets the number of the frequency of Gabor filter transformation features, controls the error accumulation, extracts the cascade features of basketball score video, constructs the video conversion discrimination rules, detects the basketball target, and obtains the tracking target contour to frame information. Finally, it realizes the target tracking detection of the team based on the team strength using an evaluation algorithm. The aim of this research work is to determine the strength of the team based on the healthcare data, team cohesiveness, and variance coefficient of basketball score frequency. The study on the coefficient of variation for basketball score frequency in teams can provide a theoretical research direction for team strength evaluation and meet the real-time needs of the coefficient of variation of basketball score frequency in teams. The empirical results show that the designed algorithm has the optimal execution time, more successful evaluation targets, high efficiency, and more reliability in evaluating the strength of the team.

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Section: Principle Model Of Goal System For Basketball Playersmentioning

confidence: 99%

Section: Build Team Strength Evaluation Algorithmmentioning

confidence: 99%

Evaluation Algorithm for Team Strength Based on the Collected Healthcare Data through IoT and Smart Devices

Qiao¹

2022

Journal of Healthcare Engineering

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“…Previous systematic reviews have reported that the prevalence of LBP in these athletes ranges from 17% to 94% [1,2]. Specifically, the prevalence of LBP in past 12 months has been reported from 6.5% to 47% in soccer players [3][4][5] and from 12.8% to 44% in basketball players [6][7][8]. A previous episode of LBP is often predictive of future back injury [9], which will affect sports participation and performance [9].…”

Section: Introductionmentioning

confidence: 99%

The Potential Role of Hamstring Extensibility on Sagittal Pelvic Tilt, Sagittal Spinal Curves and Recurrent Low Back Pain in Team Sports Players: A Gender Perspective Analysis

Cejudo

Centenera-Centenera²,

Santonja-Medina

2021

IJERPH

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It is assumed that mechanical restriction of hamstring tightness disrupts sagittal spine–pelvis–leg alignment and alters the lumbar–pelvic rhythm predisposing to low back pain (LBP) in athletes; however, this association is not clear. A prospective cross-sectional cohort study was conducted to determine the influence of hamstring extensibility (HE) on sagittal pelvic tilt, sagittal spinal curves, and LBP in 94 soccer and basketball players (61 man and 33 woman) with (n = 36) and without recurrent LBP (n = 58). Descriptive analysis displayed significant gender differences for HE, sagittal pelvic tilt, and lumbar curve. Differences were found between the low-HE and high-HE groups in lumbosacral angle in for the maximum trunk forward flexion (LH-MTFP). Low-HE was associated with LH-MTFP, lumbar curve and LBP in male players (p ≤ 0.023). In female players, LH-MTFP and lumbar curve were associated with low-HE (p ≤ 0.020). Low-HE predicted LH-MTFP (p = 0.000; OR = 65.6950) and LBP (p = 0.028; OR = 13.915) in male players. The decision tree analysis showed that 50.8% of the players were classified with restricted LH-MTFP, 77.4% with low-HE among male players. The 100% of male players with recurrent LBP had low-HE. The 65% of female players with low-HE had restricted LH-MTFP. Measurement of HE, lumbar curve, and LH-MTFP are important in making training decisions for to reduce the incidence of recurrent LBP in soccer and basketball players.

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“…[6][7][8][9] According to a study of 590 basketball athletes, 12.9% reported low back pain. 10 In many cases, pain can even prevent subjects from performing daily activities. 1 In elite basketball players aged 13-19 years, the prevalence of back pain (49% vs. 28%) and neck pain (42% vs. 20%) is higher in women than men.…”

Section: Introductionmentioning

confidence: 99%

Musculoskeletal disorders in basketball players and associated factors: a systematic review protocol with meta-analysis

Borges

Fernandes²,

Noll

et al. 2021

F1000Res

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Introduction: Musculoskeletal disorders play an important role in athletes’ health and success in sports; they are the main contributors to disability, and back pain is a common problem in athletes. Back pain and spinal injuries occur in players because of the repetitive and unilateral body overload during sports practice. Reviews focused on musculoskeletal disorders in basketball players are scarce in the literature. We describe a systematic review protocol for assessing the prevalence of musculoskeletal disorders and the associated factors in basketball players. Methods and analysis: The protocol will be based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) items and articles will be searches in the databases EMBASE, PubMed, and Scopus. Studies will be included if they are written in English and without restriction regarding the search period. All research stages will be performed by two independent reviewers and will be conducted using Rayyan. Potential disagreements will be analyzed by a third reviewer. The inter-rater reliability will be determined through the Cohen's kappa coefficient. Evidence quality will be ascertained by using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) system, while the Downs and Black checklist will be used for assessing the risk of bias. A descriptive summary and presentation of the characteristics and findings of all included studies will be provided in a table. Regarding these data, if there are sufficient high-quality studies, we plan to perform a meta-analysis. Discussion: The obtained results might possibly relate back pain to postural changes in this population. In addition, the data will be compared based on gender and different age groups. It is expected that the results can support the implementation of programs and actions for prevention, ultimately aiming at improving health, quality of life, and sports performance. Registration: PROSPERO CRD42020201653 on August, 31, 2020.

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Upper Extremity Pain Is Associated with Lower Back Pain among Young Basketball Players: A Cross-Sectional Study

Cited by 15 publications

References 23 publications

Evaluation Algorithm for Team Strength Based on the Collected Healthcare Data through IoT and Smart Devices

Evaluation Algorithm for Team Strength Based on the Collected Healthcare Data through IoT and Smart Devices

The Potential Role of Hamstring Extensibility on Sagittal Pelvic Tilt, Sagittal Spinal Curves and Recurrent Low Back Pain in Team Sports Players: A Gender Perspective Analysis

Musculoskeletal disorders in basketball players and associated factors: a systematic review protocol with meta-analysis

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