Literature DB >> 20944444

Exploiting system fluctuations. Differential training in physical prevention and rehabilitation programs for health and exercise.

Wolfgang I Schöllhorn1, Hendrik Beckmann, Keith Davids.   

Abstract

BACKGROUND: Traditional causal modeling of health interventions tends to be linear in nature and lacks multidisciplinarity. Consequently, strategies for exercise prescription in health maintenance are typically group based and focused on the role of a common optimal health status template toward which all individuals should aspire.
MATERIALS AND METHODS: In this paper, we discuss inherent weaknesses of traditional methods and introduce an approach exercise training based on neurobiological system variability. The significance of neurobiological system variability in differential learning and training was highlighted.
RESULTS: Our theoretical analysis revealed differential training as a method by which neurobiological system variability could be harnessed to facilitate health benefits of exercise training. It was observed that this approach emphasizes the importance of using individualized programs in rehabilitation and exercise, rather than group-based strategies to exercise prescription.
CONCLUSION: Research is needed on potential benefits of differential training as an approach to physical rehabilitation and exercise prescription that could counteract psychological and physical effects of disease and illness in subelite populations. For example, enhancing the complexity and variability of movement patterns in exercise prescription programs might alleviate effects of depression in nonathletic populations and physical effects of repetitive strain injuries experienced by athletes in elite and developing sport programs.

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Mesh:

Year:  2010        PMID: 20944444

Source DB:  PubMed          Journal:  Medicina (Kaunas)        ISSN: 1010-660X            Impact factor:   2.430


  8 in total

1.  Criteria-Based Return to Sport Decision-Making Following Lateral Ankle Sprain Injury: a Systematic Review and Narrative Synthesis.

Authors:  Bruno Tassignon; Jo Verschueren; Eamonn Delahunt; Michelle Smith; Bill Vicenzino; Evert Verhagen; Romain Meeusen
Journal:  Sports Med       Date:  2019-04       Impact factor: 11.136

2.  Gap-crossing behavior in a standardized and a nonstandardized jumping stone configuration.

Authors:  Karlijn Sporrel; Simone R Caljouw; Rob Withagen
Journal:  PLoS One       Date:  2017-05-03       Impact factor: 3.240

3.  Intra-individual gait patterns across different time-scales as revealed by means of a supervised learning model using kernel-based discriminant regression.

Authors:  Fabian Horst; Alexander Eekhoff; Karl M Newell; Wolfgang I Schöllhorn
Journal:  PLoS One       Date:  2017-06-15       Impact factor: 3.240

4.  Comparing the Effects of Differential Learning, Self-Controlled Feedback, and External Focus of Attention Training on Biomechanical Risk Factors of Anterior Cruciate Ligament (ACL) in Athletes: A Randomized Controlled Trial.

Authors:  Hadi Abbaszadeh Ghanati; Amir Letafatkar; Sadredin Shojaedin; Malihe Hadadnezhad; Wolfgang I Schöllhorn
Journal:  Int J Environ Res Public Health       Date:  2022-08-15       Impact factor: 4.614

5.  Functional gait rehabilitation in elderly people following a fall-related hip fracture using a treadmill with visual context: design of a randomized controlled trial.

Authors:  Mariëlle W van Ooijen; Melvyn Roerdink; Marga Trekop; Jan Visschedijk; Thomas W Janssen; Peter J Beek
Journal:  BMC Geriatr       Date:  2013-04-16       Impact factor: 3.921

6.  Pacing the phasing of leg and arm movements in breaststroke swimming to minimize intra-cyclic velocity fluctuations.

Authors:  Josje van Houwelingen; Melvyn Roerdink; Alja V Huibers; Lotte L W Evers; Peter J Beek
Journal:  PLoS One       Date:  2017-10-12       Impact factor: 3.240

7.  Systematic Review and Meta-Analysis on Proximal-to-Distal Sequencing in Team Handball: Prospects for Talent Detection?

Authors:  Ben Serrien; Jean-Pierre Baeyens
Journal:  J Hum Kinet       Date:  2018-09-24       Impact factor: 2.193

Review 8.  Always Pay Attention to Which Model of Motor Learning You Are Using.

Authors:  Wolfgang I Schöllhorn; Nikolas Rizzi; Agnė Slapšinskaitė-Dackevičienė; Nuno Leite
Journal:  Int J Environ Res Public Health       Date:  2022-01-09       Impact factor: 3.390

  8 in total

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