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Episode 187: In this episode of the Athletic Shoulder Podcast, we’re joined by Annelies Maenhout, a visiting professor at Ghent University’s Department of Rehabilitation Sciences and a leading researcher in shoulder rehabilitation. As a core member of the university’s Upper Limb Research Team, Annelies has contributed significantly to the field through her work on EMG, motor learning, and kinetic chain mechanics.
Her research bridges cutting-edge science with clinical practice, offering insights into how shoulder rehab can be refined through eccentric loading, implicit motor learning, and neuromechanics. With a forward-thinking approach, she explores how VR, brain activity, and reaction time play a role in optimizing rehab for overhead athletes.
EMG research on kinetic chain and plyometric exercises
How her view on GIRD (glenohumeral internal rotation deficit) evolved over time
Key findings from eccentric training research
Transitioning from internal to external attentional focus in rehab
Applying implicit motor learning in shoulder rehabilitation
The current gap in research on reaction time in overhead athletes
Exploring the potential of VR and neuroscience in shoulder rehab
Future directions in shoulder research: muscle synergies and brain activity
Whether you're a clinician, coach, or researcher, this episode offers valuable insights into the future of evidence-based shoulder rehabilitation.
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Where you can find Annelies:
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Sponsors
VALD Performance, makers of the Nordbord, Forceframe, ForeDecks and HumanTrak. VALD Performance systems are built with the high-performance practitioner in mind, translating traditionally lab-based technologies into engaging, quick, easy-to-use tools for daily testing, monitoring and training
Hytro: The world’s leading Blood Flow Restriction (BFR) wearable, designed to accelerate recovery and maximise athletic potential using Hytro BFR for Professional Sport.
-
Where to Find Us
Keep up to date with everything that is going on with the podcast by following Inform Performance on:
-
Our Team
5
3939 ratings
Episode 187: In this episode of the Athletic Shoulder Podcast, we’re joined by Annelies Maenhout, a visiting professor at Ghent University’s Department of Rehabilitation Sciences and a leading researcher in shoulder rehabilitation. As a core member of the university’s Upper Limb Research Team, Annelies has contributed significantly to the field through her work on EMG, motor learning, and kinetic chain mechanics.
Her research bridges cutting-edge science with clinical practice, offering insights into how shoulder rehab can be refined through eccentric loading, implicit motor learning, and neuromechanics. With a forward-thinking approach, she explores how VR, brain activity, and reaction time play a role in optimizing rehab for overhead athletes.
EMG research on kinetic chain and plyometric exercises
How her view on GIRD (glenohumeral internal rotation deficit) evolved over time
Key findings from eccentric training research
Transitioning from internal to external attentional focus in rehab
Applying implicit motor learning in shoulder rehabilitation
The current gap in research on reaction time in overhead athletes
Exploring the potential of VR and neuroscience in shoulder rehab
Future directions in shoulder research: muscle synergies and brain activity
Whether you're a clinician, coach, or researcher, this episode offers valuable insights into the future of evidence-based shoulder rehabilitation.
-
Where you can find Annelies:
-
Sponsors
VALD Performance, makers of the Nordbord, Forceframe, ForeDecks and HumanTrak. VALD Performance systems are built with the high-performance practitioner in mind, translating traditionally lab-based technologies into engaging, quick, easy-to-use tools for daily testing, monitoring and training
Hytro: The world’s leading Blood Flow Restriction (BFR) wearable, designed to accelerate recovery and maximise athletic potential using Hytro BFR for Professional Sport.
-
Where to Find Us
Keep up to date with everything that is going on with the podcast by following Inform Performance on:
-
Our Team
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