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Effects of Different Cardiorespiratory Training Program on Endurance Performance

NCT04357691 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 20

Last updated 2020-05-04

No results posted yet for this study

Summary

Conventional training methods are typically administered in a fixed progressive manner, which can lead to sub-optimal responses and injuries. Artificial intelligence (i.e. CURATE.AI) can be harnessed to personalise physical training strategies. Using a single participant training profile, a parabolic/quadratic response to the intervention can be generated to identify the training intensity needed to optimise training outcomes. Previous studies showed CURATE.AI could dynamically modulate drug dosing in oncology. Extending the utility of results to human performance, this study will adapt CURATE.AI with the goal of optimising endurance performance through individualised training regimes.

Up to 20 participants will be recruited and randomised into two groups to undergo a calibration phase, which involves performing 3 sessions of exercise sessions per week over 2 weeks per intensity (low, moderate and high) in a crossover study design. Exercise sessions will be interspersed with a 2.4 km time trial, a VO2peak test and 2 weeks of wash out period. The utility phase will divide participants into two groups to undergo 3 exercise sessions per week, totalling to 12 exercise sessions. Either an AI-led training or a conventional training programme will be performed to compare the differences in training outcomes. Blood plasma will be obtained at selected time points in both phases to evaluate the effects of training on blood lipid profiles.

Findings from this study can potentially optimise efficacy and efficiency of endurance performance through personalised training with AI.

Conditions

  • Healthy

Interventions

BEHAVIORAL

Conventional training

Participants will perform a conventional training for 4 weeks, using low-moderate-high-low intensity progression training model

BEHAVIORAL

AI-led training

Participants will perform an AI-led training for 4 weeks

Sponsors & Collaborators

  • The N.1 Institute for Health (N.1)

    collaborator OTHER

  • Wang Yongtai Raymond

    lead OTHER

Principal Investigators

  • Kai Wei, Jason Lee, PhD · National University of Singapore

  • Dean Ho, PhD · National University of Singapore

Study Design

Allocation
NON_RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Model
CROSSOVER

Eligibility

Min Age
21 Years
Max Age
35 Years
Sex
MALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-05-25
Primary Completion
2022-12-31
Completion
2022-12-31

Countries

  • Singapore

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04357691 on ClinicalTrials.gov