Abstract
Adaptive Training Protocols (ATP) is a collection of algorithms and software to apply principals of intelligent tutoring to physical fitness training. To obtain norming data for ATP, we examined exercise performance from 34 participants under an adaptive workout regimen lasting 13 weeks. The goal of the regimen was to train to pass the performance criteria of the US Marine Corps Initial Strength Test (IST; a 1.5-mile run, sits-ups, pull-ups, and push-ups). The weekly regimen comprised an IST, an interval workout, and a maximum workout. Adaptation was accomplished via two algorithms: maximum-day reps were double those accomplished on the prior IST and maximum-day and interval-day runs were performed at specified rates of perceived exertion. Starting capabilities for run, sit-ups, and push-ups negatively correlated with progression rates; participants who exhibited lower performance at the start of the study made steeper gains in performance. Individual logistic curve fitting found decelerating, inflecting, and accelerating progression profiles. Participants showed considerable variation in their profiles both across individuals in each exercise and within individuals across exercises. Progression profiles can be used to forecast the performance that a person can attain in a given timeframe under a given training regimen. This knowledge can be used to adapt the workout to provide more time to reach a goal if needed or to focus on exercises that are in jeopardy of not achieving the goal in time. ATP will help the Marine Corps plan for when intended recruits may be physically ready to ship out to boot camp.
| Original language | English |
|---|---|
| Title of host publication | Adaptive Instructional Systems. Design and Evaluation - Third International Conference, AIS 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Proceedings |
| Editors | Robert A. Sottilare, Jessica Schwarz |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 616-630 |
| Number of pages | 15 |
| ISBN (Print) | 9783030778569 |
| DOIs | |
| State | Published - 2021 |
| Event | 3rd International Conference on Adaptive Instructional Systems, AIS 2021, Held as Part of the 23rd HCI International Conference, HCII 2021 - Virtual, Online Duration: Jul 24 2021 → Jul 29 2021 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 12792 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 3rd International Conference on Adaptive Instructional Systems, AIS 2021, Held as Part of the 23rd HCI International Conference, HCII 2021 |
|---|---|
| City | Virtual, Online |
| Period | 07/24/21 → 07/29/21 |
Funding
Acknowledgements. This material is based upon work supported by the United States Navy Office of Naval Research (ONR) under Contract No. N00014–19-C-2028. Submitted to ONR for Public Release, DCN#43–7669-21. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the US Navy or ONR. We are grateful to Dr. Allie Duffie for discussion of muscle memory and hypertrophy. We are grateful to Peter Squire, Natalie Steinhauser, and Mark White for support and feedback during this research.
| Funders | Funder number |
|---|---|
| Office of Naval Research | N00014–19-C-2028 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 14 Life Below Water
Keywords
- Adaptive training
- Exercise
- Physical fitness progression
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