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255 results on '"Ramachandran, Akhilesh"'

1. TEPI: Taxonomy-aware Embedding and Pseudo-Imaging for Scarcely-labeled Zero-shot Genome Classification

Author

Aakur, Sathyanarayanan, Laguduva, Vishalini R., Ramamurthy, Priyadharsini, and Ramachandran, Akhilesh

Subjects
Quantitative Biology - Genomics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

A species' genetic code or genome encodes valuable evolutionary, biological, and phylogenetic information that aids in species recognition, taxonomic classification, and understanding genetic predispositions like drug resistance and virulence. However, the vast number of potential species poses significant challenges in developing a general-purpose whole genome classification tool. Traditional bioinformatics tools have made notable progress but lack scalability and are computationally expensive. Machine learning-based frameworks show promise but must address the issue of large classification vocabularies with long-tail distributions. In this study, we propose addressing this problem through zero-shot learning using TEPI, Taxonomy-aware Embedding and Pseudo-Imaging. We represent each genome as pseudo-images and map them to a taxonomy-aware embedding space for reasoning and classification. This embedding space captures compositional and phylogenetic relationships of species, enabling predictions in extensive search spaces. We evaluate TEPI using two rigorous zero-shot settings and demonstrate its generalization capabilities qualitatively on curated, large-scale, publicly sourced data., Comment: Accepted to IEEE JBHI

Published
2024

4. Scalable Pathogen Detection from Next Generation DNA Sequencing with Deep Learning

Author

Narayanan, Sai, Aakur, Sathyanarayanan N., Ramamurthy, Priyadharsini, Bagavathi, Arunkumar, Ramnath, Vishalini, and Ramachandran, Akhilesh

Subjects
Computer Science - Machine Learning, Quantitative Biology - Genomics
Abstract

Next-generation sequencing technologies have enhanced the scope of Internet-of-Things (IoT) to include genomics for personalized medicine through the increased availability of an abundance of genome data collected from heterogeneous sources at a reduced cost. Given the sheer magnitude of the collected data and the significant challenges offered by the presence of highly similar genomic structure across species, there is a need for robust, scalable analysis platforms to extract actionable knowledge such as the presence of potentially zoonotic pathogens. The emergence of zoonotic diseases from novel pathogens, such as the influenza virus in 1918 and SARS-CoV-2 in 2019 that can jump species barriers and lead to pandemic underscores the need for scalable metagenome analysis. In this work, we propose MG2Vec, a deep learning-based solution that uses the transformer network as its backbone, to learn robust features from raw metagenome sequences for downstream biomedical tasks such as targeted and generalized pathogen detection. Extensive experiments on four increasingly challenging, yet realistic diagnostic settings, show that the proposed approach can help detect pathogens from uncurated, real-world clinical samples with minimal human supervision in the form of labels. Further, we demonstrate that the learned representations can generalize to completely unrelated pathogens across diseases and species for large-scale metagenome analysis. We provide a comprehensive evaluation of a novel representation learning framework for metagenome-based disease diagnostics with deep learning and provide a way forward for extracting and using robust vector representations from low-cost next generation sequencing to develop generalizable diagnostic tools., Comment: Expanded version of arXiv:2111.08001. Under review in a journal

Published
2022

7. Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis

Author

Aakur, Sathyanarayanan N., Indla, Vineela, Indla, Vennela, Narayanan, Sai, Bagavathi, Arunkumar, Ramnath, Vishalini Laguduva, and Ramachandran, Akhilesh

Subjects
Quantitative Biology - Genomics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Advances in next-generation metagenome sequencing have the potential to revolutionize the point-of-care diagnosis of novel pathogen infections, which could help prevent potential widespread transmission of diseases. Given the high volume of metagenome sequences, there is a need for scalable frameworks to analyze and segment metagenome sequences from clinical samples, which can be highly imbalanced. There is an increased need for learning robust representations from metagenome reads since pathogens within a family can have highly similar genome structures (some more than 90%) and hence enable the segmentation and identification of novel pathogen sequences with limited labeled data. In this work, we propose Metagenome2Vec - a contextualized representation that captures the global structural properties inherent in metagenome data and local contextualized properties through self-supervised representation learning. We show that the learned representations can help detect six (6) related pathogens from clinical samples with less than 100 labeled sequences. Extensive experiments on simulated and clinical metagenome data show that the proposed representation encodes compositional properties that can generalize beyond annotations to segment novel pathogens in an unsupervised setting., Comment: To appear in DMBIH Workshop at ICDM 2021

Published
2021

8. MG-NET: Leveraging Pseudo-Imaging for Multi-Modal Metagenome Analysis

Author

Aakur, Sathyanarayanan N., Narayanan, Sai, Indla, Vineela, Bagavathi, Arunkumar, Ramnath, Vishalini Laguduva, and Ramachandran, Akhilesh

Subjects
Computer Science - Machine Learning, Quantitative Biology - Genomics
Abstract

The emergence of novel pathogens and zoonotic diseases like the SARS-CoV-2 have underlined the need for developing novel diagnosis and intervention pipelines that can learn rapidly from small amounts of labeled data. Combined with technological advances in next-generation sequencing, metagenome-based diagnostic tools hold much promise to revolutionize rapid point-of-care diagnosis. However, there are significant challenges in developing such an approach, the chief among which is to learn self-supervised representations that can help detect novel pathogen signatures with very low amounts of labeled data. This is particularly a difficult task given that closely related pathogens can share more than 90% of their genome structure. In this work, we address these challenges by proposing MG-Net, a self-supervised representation learning framework that leverages multi-modal context using pseudo-imaging data derived from clinical metagenome sequences. We show that the proposed framework can learn robust representations from unlabeled data that can be used for downstream tasks such as metagenome sequence classification with limited access to labeled data. Extensive experiments show that the learned features outperform current baseline metagenome representations, given only 1000 samples per class., Comment: To appear in MICCAI 2021

Published
2021

9. Genome Sequence Classification for Animal Diagnostics with Graph Representations and Deep Neural Networks

Author

Narayanan, Sai, Ramachandran, Akhilesh, Aakur, Sathyanarayanan N., and Bagavathi, Arunkumar

Subjects
Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods
Abstract

Bovine Respiratory Disease Complex (BRDC) is a complex respiratory disease in cattle with multiple etiologies, including bacterial and viral. It is estimated that mortality, morbidity, therapy, and quarantine resulting from BRDC account for significant losses in the cattle industry. Early detection and management of BRDC are crucial in mitigating economic losses. Current animal disease diagnostics is based on traditional tests such as bacterial culture, serolog, and Polymerase Chain Reaction (PCR) tests. Even though these tests are validated for several diseases, their main challenge is their limited ability to detect the presence of multiple pathogens simultaneously. Advancements of data analytics and machine learning and applications over metagenome sequencing are setting trends on several applications. In this work, we demonstrate a machine learning approach to identify pathogen signatures present in bovine metagenome sequences using k-mer-based network embedding followed by a deep learning-based classification task. With experiments conducted on two different simulated datasets, we show that networks-based machine learning approaches can detect pathogen signature with up to 89.7% accuracy. We will make the data available publicly upon request to tackle this important problem in a difficult domain.

Published
2020

11. The correlation of force-velocity-power relationship of a whole-body movement with 20 m and 60 m sprint performance.

Author

Singh, Utkarsh, Ramachandran, Akhilesh Kumar, Baxter, Brett A., and Allen, Sam J.

Subjects
*BIOMECHANICS, *STATISTICAL correlation, *MULTIPLE regression analysis, *ACCELERATION (Mechanics), *DESCRIPTIVE statistics, *MUSCLE strength, *RESEARCH, *BODY movement, *ATHLETIC ability, *JUMPING, *EXERCISE tests, *SPRINTING, *PHYSIOLOGICAL effects of acceleration
Abstract

Sprinting ability is important for successful performance in sports. The aim of this study was to examine the correlation between force-velocity-power relationship of a whole-body movement and sprint performance. Twelve male participants performed maximal squat jumps with additional loads ranging from 0% to 100% body weight to obtain force-velocity profiles. The mean force and velocity were calculated during the push-off phase for each jump, which resulted in a force-velocity curve. The theoretical maximal force (F0), theoretical maximal velocity (V0) and theoretical maximum power (P0) were computed via extrapolation of the force and velocity data. In the second session, participants performed two 60 m sprints and the time to cover 20 m (t20), time to cover 60 m (t60), and maximum sprint velocity (Vmax) were calculated from the best 60 m trial. Correlation analyses revealed strong and significant correlations between V0 and t20 (r = −0.60), V0 and t60 (r = −0.60), P0 and t20 (r = −0.75) and P0 and t60 (r = −0.78). Multiple linear regression indicated that P0 explained 56%, 61% and 60% of the variability in t20, t60 and Vmax, respectively. Our results emphasise the importance of developing power production capabilities to improve sprint performance. [ABSTRACT FROM AUTHOR]

Published
2024
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12. AEROBIC BLOOD CULTURES AND COMPARISON TO CLINICAL FINDINGS OF FREE-RANGING GREEN TURTLES (CHELONIA MYDAS) IN EAST CENTRAL FLORIDA.

Author

Glassman, Alan R., Zachariah, Trevor T., Patterson, Jessica L., Mansfield, Katherine L., Seney, Erin E., and Ramachandran, Akhilesh

Abstract

Positive blood cultures have been identified in debilitated, stranded, and deceased green turtles (Chelonia mydas), suggestive of septicemia. Interpretation of these results is often difficult because multiple studies have previously identified bacteremia in clinically healthy reptiles. In this study, paired blood cultures and skin cultures obtained after aseptic preparation of the venipuncture site were collected from 50 immature free-ranging green turtles from Port Canaveral, Florida. Blood culture results were compared with health status (apparently healthy versus unhealthy, based on physical examination findings and appropriate body condition), date of collection, presence of external fibropapillomatosis, healed or unhealed injuries, and presence of barnacles. Weight, body condition score, body condition index, morphometric measures, volume of blood collected, and body temperature were compared between blood culture–positive and blood culture–negative turtles. Positive blood cultures were identified in 14% (7 of 50) of all turtles, including 15.6% (5 of 32) of apparently healthy turtles. Vibrio spp., Bacillus megaterium, Cellulomonas sp., and Staphylococcus pasteuri were isolated in blood culture from apparently healthy individuals. There was a significant association (P = 0.048) between positive skin cultures and positive blood cultures, but isolates obtained were consistently different between paired results. There was no significant association (P > 0.05) between blood culture results and health status, evidence of healed or unhealed injuries, external fibropapillomatosis, or presence of barnacles. Based on the results of this study, positive blood cultures suggestive of nonclinical bacteremia may be present in apparently healthy green turtles. The results of this study will aid the attending clinician in interpretation of blood culture results of apparently healthy or presumed septicemic captive and rehabilitating green turtles as part of the conservation and population recovery of this threatened species. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Effects of Neuromuscular Training on Muscle Architecture, Isometric Force Production, and Stretch-Shortening Cycle Function in Trained Young Female Gymnasts.

Author

Moeskops, Sylvia, Oliver, Jon L., Radnor, John M., Haff, G. Gregory, Myer, Gregory D., Ramachandran, Akhilesh K., Kember, Lucy S., Pedley, Jason S., and Lloyd, Rhodri S.

Subjects
SKELETAL muscle physiology, GYMNASTICS, EXERCISE physiology, ADOLESCENCE, PLYOMETRICS, SKELETAL muscle, CALF muscles, DESCRIPTIVE statistics, KINESIOLOGY, HUMAN growth, AGE distribution, STRENGTH training, JUMPING, DATA analysis software, NEURODEVELOPMENTAL treatment, MUSCLE contraction
Abstract

This study evaluated the effects of a 10-month neuromuscular training (NMT) intervention on muscle architecture, isometric force production, and stretch-shortening cycle (SSC) function. Thirty-seven girls aged 6-12 years were placed into gymnastics + NMT (gNMT; n = 15), gymnastics only (GYM; n = 10), or maturity-matched control (CON; n = 12) groups. The gNMT group followed a 10-month NMT program in addition to gymnastics training, whereas the GYM group only participated in gymnastics training. Isometric midthigh pull (IMTP) and drop jump (DJ) kinetics were measured, in addition to muscle thickness, fascicle length, and pennation angle of the gastrocnemius medialis at baseline and at 4, 7, and 10 months. A3 x 4 (group x time) repeated-measures ANCOVA (covariate, % predicted adult height) was used to evaluate within-group changes. Significance level was set at p < 0.05. Significant interaction effects were observed in muscle thickness, absolute (PFabs) and relative peak force (PFrel) in the IMTP and various DJ variables. The gNMT group demonstrated improvements in muscle thickness, IMTP PFabs and PFrel, and DJ kinetics, most commonly evidenced from 7 months onward. The GYM group's muscle thickness also significantly improved, accompanied by improvements in some DJ kinetics. The CON group did not experience any desirable changes. Overall, NMT elicited positive changes in muscle thickness, PFabs and PFrel, and SSC function to a greater extent than gymnastics training alone or growth and maturation. As most adaptations took 7 months, longer-term NMT programs should be implemented with youth female gymnasts. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Sim2Real for Metagenomes: Accelerating Animal Diagnostics with Adversarial Co-training

Author

Indla, Vineela, Indla, Vennela, Narayanan, Sai, Ramachandran, Akhilesh, Bagavathi, Arunkumar, Ramnath, Vishalini Laguduva, Aakur, Sathyanarayanan N., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Karlapalem, Kamal, editor, Cheng, Hong, editor, Ramakrishnan, Naren, editor, Agrawal, R. K., editor, Reddy, P. Krishna, editor, Srivastava, Jaideep, editor, and Chakraborty, Tanmoy, editor

Published
2021
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16. Training, Tests, and Tech

Author

Harmon, Carrie Lapaire, primary, Akey, Bruce L., additional, Ochoa-Corona, Francisco Manuel, additional, Ramachandran, Akhilesh, additional, and Sharma, Poonam, additional

Published
2022
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20. Biomechanical and physical determinants of bowling speed in cricket: a novel approach to systematic review and meta-analysis of correlational data.

Author

Ramachandran, Akhilesh Kumar, Singh, Utkarsh, Connor, Jonathan Douglas, and Doma, Kenji

Subjects
*ARM physiology, *KNEE joint, *ONLINE information services, *CINAHL database, *RESEARCH, *META-analysis, *SHOULDER joint, *SYSTEMATIC reviews, *CRICKET (Sport), *SPORTS, *ARM, *DESCRIPTIVE statistics, *BIOMECHANICS, *MEDLINE, *INFORMATION storage & retrieval systems, *STATISTICAL correlation, *GROUND reaction forces (Biomechanics)
Abstract

This systematic review and meta-analysis examined the influence of biomechanical and physical characteristics on ball release speed in cricket using correlation data. Search was conducted across PubMed, Cinhal, Scopus, SportDiscus and Web of Science, with eighteen studies included. The ball release speed had a moderate correlation with overall biomechanical (r = 0.42, p < 0.001) parameters and a strong correlation with physical (r = 0.65, p < 0.001) characteristics. Furthermore, individual biomechanical and physical parameters were also correlated with ball release speed. The run-up speed had a strong correlation (r = 0.50, p < 0.001) and front knee angle at ball release had a moderate correlation (r = 0.40, p < 0.001). Poorer correlations were identified for centre of mass velocity at ball release (r = 0.16, p = 0.134), front knee angle at front foot contact (r = 0.26, p = 0.015) 25 and vertical ground reaction force (r = 0.13, p = 0.659). Strong and significant correlation was found for total arm length (r = 0.65, p < 0.001) and shoulder strength (r = 0.58, p < 0.001). This review highlights the biomechanical and physical parameters that are major determinants of faster ball release speed. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Exploring the influence of task and environmental constraints on batting and bowling performance in cricket: A systematic review.

Author

Singh, Utkarsh, Ramachandran, Akhilesh Kumar, Doma, Kenji, and Connor, Jonathan D

Subjects
CRICKET bowling, CRICKET batting, CRICKET (Sport), CINAHL database, CRICKET players
Abstract

Cricket is an unique international sport where environmental and task constraints have shown to have a significant impact on batting and bowling performance. The aim of this systematic review was to determine the effect of task and environmental constraints on cricket performance. A systematic literature search was conducted across Scopus, PubMed, Web of Science, CINAHL, and SportDiscus. Studies were deemed eligible if they reported the effects of pitch type, pitch length, equipment (e.g. cricket bat, batting pads, ball type, etc.) on cricket performance. A total of 20 studies met the inclusion criteria with Kmet score ranging between 75% and 92%. The results from this study demonstrate that environmental constraints such as pitch-type and task constraints such as equipment modification (e.g. type of cricket bat, batting pads, ball) and pitch length can influence cricketer's batting and bowling performance. Scaling cricket bats and reducing pitch length were acutely beneficial to cricket batting, while ball type, pitch length and soil properties were impactful on bowling performance. Importantly though, the impact of constraint manipulation seemed to be influenced by the skill level of the performer. The findings from this study may help to inform coaches and practitioners improve skill acquisition, through constraint manipulation, to develop highly adaptive cricket batting and bowling skill. [ABSTRACT FROM AUTHOR]

Published
2023
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26. TEPI: <underline>T</underline>axonomy-Aware <underline>E</underline>mbedding and <underline>P</underline>seudo-<underline>I</underline>maging for Scarcely-Labeled Zero-Shot Genome Classification

Author

Aakur, Sathyanarayanan N., Laguduva, Vishalini R., Ramamurthy, Priyadharsini, and Ramachandran, Akhilesh

Abstract

A species' genetic code or genome encodes valuable evolutionary, biological, and phylogenetic information that aids in species recognition, taxonomic classification, and understanding genetic predispositions like drug resistance and virulence. However, the vast number of potential species poses significant challenges in developing a general-purpose whole genome classification tool. Traditional bioinformatics tools have made notable progress but lack scalability and are computationally expensive. Machine learning-based frameworks show promise but must address the issue of large classification vocabularies with long-tail distributions. In this study, we propose addressing this problem through zero-shot learning using TEPI, Taxonomy-aware Embedding and Pseudo-Imaging. We represent each genome as pseudo-images and map them to a taxonomy-aware embedding space for reasoning and classification. This embedding space captures compositional and phylogenetic relationships of species, enabling predictions in extensive search spaces. We evaluate TEPI using two rigorous zero-shot settings and demonstrate its generalization capabilities qualitatively on curated, large-scale, publicly sourced data.

Published
2024
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27. Sex-based differences in concussion incidence and its underlying injury mechanism in team bat/stick sports: A systematic review and meta-analysis.

Author

Sundaram, Vasanth, Ramachandran, Akhilesh Kumar, Singh, Utkarsh, and Pearce, Alan J

Subjects
ROOSTING, BRAIN concussion, SPORTS participation, MEDICAL personnel, RANDOM effects model, SPORTS, MALE athletes
Abstract

This study aimed to synthesize and quantify the sex-based differences in concussion incidences rate and associated mechanism of injuries in team bat/stick sports. Following a systematic search across five electronic databases, 46 studies were included in the review; 24 were included in the incidence rate (IR) meta-analysis and 13 of the 24 studies met the eligibility criteria for the meta-analysis involving injury mechanism. DerSimonian and Laird random effects models were used for pooling the Rate Ratio (RR) data. Ice-hockey had the highest overall risk of concussion, followed by lacrosse and baseball/softball. Female players had higher concussion IRs compared to males (RR 0.74 [95% CI 0.58–0.95], p =.02) across all sports included in this study. Sex-based differences in concussion IRs for ice-hockey and lacrosse were not statistically significant. Male athletes were more statistically likely to sustain concussion because of player-contact in ice-hockey (RR 1.55 [95% CI 1.29–1.86], p <.001) and lacrosse (RR 3.20 [95% CI 1.54–6.64], p =.002). Conversely, female athletes showed a higher risk of concussion due to equipment contact in lacrosse (RR 0.29 [95% CI 0.20–0.43], p <.001). Injury mechanism varies between male and female athletes across these bat/stick sports. Female athletes have a higher risk of getting concussed due to the impact of players with equipment (ball/puck) and surface contact for lacrosse and ice-hockey. Findings from this study can help coaches, sports administrators, and health care providers with further data on the current information regarding concussion-related factors in these respective sports. [ABSTRACT FROM AUTHOR]

Published
2023
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33. Effect of strength and plyometric training programs on physical characteristics of youth soccer players: a systematic review and meta-analysis

Author

Ramachandran, Akhilesh, Singh, Utkarsh, Ramirez-Campillo, Rodrigo, Lloyd, Rhodri, and Oliver, Jon

Subjects
Medicine and Health Sciences, Sports Sciences, human activities
Abstract

Strength, speed and power characteristics are considered crucial for soccer players in improved performance and reduced risk of injuries. As primary outcomes, our review aims to analyse jumping (e.g., countermovement jump (in cms)), linear sprinting time (e.g., 10 m, 20 m (in seconds)), change-of-direction speed (e.g., Illinois test (seconds)), strength (e.g., maximal, dynamic, isometric (number of repitition, load in kgs)) performances from included studies. The pre- and post-training intervention mean and standard deviation during the above mentioned tasks will be collected for the experimental and active control group for analysis. The findings from our review can be useful for coaches and practitioners aiming to improve the overall fitness levels of youth soccer players and help them transition through to advanced playing levels.

Published
2022
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34. Combined and Individual effect of strength and plyometric training programs on strength, speed and power characteristics of highly-skilled youth soccer players: a systematic review and meta-analysis

Author

Ramachandran, Akhilesh, Singh, Utkarsh, Ramirez-Campillo, Rodrigo, Lloyd, Rhodri, and Oliver, Jon

Subjects
Medicine and Health Sciences, Sports Sciences
Abstract

The primary aim of our study was to compare the individual and combined effectiveness of ST and PT training practices on youth soccer player’s strength, power and speed characteristics.

Published
2022
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41. sj-docx-2-spo-10.1177_17479541221131650 - Supplemental material for Sex-based differences in concussion incidence and its underlying injury mechanism in team bat/stick sports: A systematic review and meta-analysis

Author

Sundaram, Vasanth, Ramachandran, Akhilesh Kumar, Singh, Utkarsh, and Pearce, Alan J

Subjects
Sociology, FOS: Sociology
Abstract

Supplemental material, sj-docx-2-spo-10.1177_17479541221131650 for Sex-based differences in concussion incidence and its underlying injury mechanism in team bat/stick sports: A systematic review and meta-analysis by Vasanth Sundaram, Akhilesh Kumar Ramachandran, Utkarsh Singh and Alan J Pearce in International Journal of Sports Science & Coaching

Published
2022
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42. Virus viability in spiked swine bone marrow tissue during above‐ground burial method and under in vitro conditions

Author

Ebling, Rafael, primary, Paim, Willian Pinto, additional, Turner, Justin, additional, Flory, Gary, additional, Seiger, Jeremy, additional, Whitcomb, Caleb, additional, Remmenga, Marta, additional, Vuolo, Matthew, additional, Ramachandran, Akhilesh, additional, Cole, Leslie, additional, Flores, Eduardo Furtado, additional, Miknis, Robert, additional, Brewer, Becky, additional, Miller, Lori, additional, Bailey, Keith, additional, Talley, Justin, additional, and Bauermann, Fernando Vicosa, additional

Published
2022
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44. Multi-laboratory evaluation of the Illumina iSeq platform for whole genome sequencing of Salmonella, Escherichia coli and Listeria

Author

Mitchell, Patrick K., primary, Wang, Leyi, additional, Stanhope, Bryce J., additional, Cronk, Brittany D., additional, Anderson, Renee, additional, Mohan, Shipra, additional, Zhou, Lijuan, additional, Sanchez, Susan, additional, Bartlett, Paula, additional, Maddox, Carol, additional, DeShambo, Vanessa, additional, Mani, Rinosh, additional, Hengesbach, Lindsy M., additional, Gresch, Sarah, additional, Wright, Katie, additional, Mor, Sunil, additional, Zhang, Shuping, additional, Shen, Zhenyu, additional, Yan, Lifang, additional, Mackey, Rebecca, additional, Franklin-Guild, Rebecca, additional, Zhang, Yan, additional, Prarat, Melanie, additional, Shiplett, Katherine, additional, Ramachandran, Akhilesh, additional, Narayanan, Sai, additional, Sanders, Justin, additional, Hunkapiller, Andree A., additional, Lahmers, Kevin, additional, Carbonello, Amanda A., additional, Aulik, Nicole, additional, Lim, Ailam, additional, Cooper, Jennifer, additional, Jones, Angelica, additional, Guag, Jake, additional, Nemser, Sarah M., additional, Tyson, Gregory H., additional, Timme, Ruth, additional, Strain, Errol, additional, Reimschuessel, Renate, additional, Ceric, Olgica, additional, and Goodman, Laura B., additional

Published
2022
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47. Effects of Plyometric Jump Training on Balance Performance in Healthy Participants: A Systematic Review With Meta-Analysis

Author

Ramachandran, Akhilesh Kumar, Singh, Utkarsh, Ramirez-Campillo, Rodrigo, Clemente, Filipe Manuel, Afonso, José, and Granacher, Urs

Subjects
human physical conditioning, exercise, Physiology, plyometric exercise, Systematic Review, resistance training, movement, postural control
Abstract

Background: Postural balance represents a fundamental movement skill for the successful performance of everyday and sport-related activities. There is ample evidence on the effectiveness of balance training on balance performance in athletic and non-athletic population. However, less is known on potential transfer effects of other training types, such as plyometric jump training (PJT) on measures of balance. Given that PJT is a highly dynamic exercise mode with various forms of jump-landing tasks, high levels of postural control are needed to successfully perform PJT exercises. Accordingly, PJT has the potential to not only improve measures of muscle strength and power but also balance. Objective: To systematically review and synthetize evidence from randomized and non-randomized controlled trials regarding the effects of PJT on measures of balance in apparently healthy participants. Methods: Systematic literature searches were performed in the electronic databases PubMed, Web of Science, and SCOPUS. A PICOS approach was applied to define inclusion criteria, (i) apparently healthy participants, with no restrictions on their fitness level, sex, or age, (ii) a PJT program, (iii) active controls (any sport-related activity) or specific active controls (a specific exercise type such as balance training), (iv) assessment of dynamic, static balance pre- and post-PJT, (v) randomized controlled trials and controlled trials. The methodological quality of studies was assessed using the Physiotherapy Evidence Database (PEDro) scale. This meta-analysis was computed using the inverse variance random-effects model. The significance level was set at p

Published
2021

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