EliteForm Lift Tracker vs Reaction RMO Pro

The EliteForm Lift Tracker blends powerful tracking with the motivation of community. Over a decade ago, EliteForm was the first to bring 3D depth camera technology to elite and professional weight rooms. Our legacy product, the EliteForm PowerTracker, is found on weight racks across the globe and currently tracks, Olympians, Pros and nearly half the lifts at Power5 schools today. We’re excited to leverage that same patented experience to track lifts wherever you lift today. EF’s Lift Tracker tracks weightlifting in real-time, giving you live rep by rep counts, velocities and power metrics. Watch your lifting level up as gain a deeper understanding of the work you are putting in and increase strength and explosiveness over time. No matter your goals, Lift Tracker provides better information to help you achieve whatever finish line you have in front of you. Designed to use your phone, and only your phone, Lift Tracker goes with you everywhere. Garage gym, fitness club, college campus, better information about your lifts is always at hand anytime, anywhere you go. Ways to start using EliteForm’s Lift Tracker: Start simply by lifting a comfortable weight and let the Lift Tracker count each rep in your set. Compete with yourself. Take that same load and watch how much more slowly you move that weight toward the end of your set. Conversely, how fast can you move it? Call out your Friends. Use the Share Button to send the results of that set to your friends. Can they move 225 pounds as fast as you can during a Bench Press? The Lift Tracker will let you know. For those familiar with velocity-based training (VBT), dive right in! You can follow the specific training protocol that’s right for you by targeting the proper velocity range for your desired outcome. If you’re not familiar with velocity-based training but would like to learn more, visit our Resources page at eliteform.com. Regardless of how you use EliteForm’s Lift Tracker, you’ll be able to share the numbers you want with friends and coaches. As we expand our community toolset, you’ll be able to not only share results, but gain friends, send congrats on a PR and or just flex on each other online. We all improve together so look forward to more. Powerful Tracking. Better Performance. And a bit of fun with your friends along the way. For more information please visit the link https://support.apple.com/en-us/HT202039 Support: https://eflifttracker.crisp.help/en/ Privacy Policy: https://eliteform.com/privacy-policy/ Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

This app allows you to determine the user's ability to react to a moving object. One of the methods for monitoring the functional state of the human central nervous system is to determine the ratio of excitation and inhibition processes during the reaction to a moving object (RMO). The human reaction to a moving object refers to the ability to determine the spatial and temporal parameters of the visual stimulus movement, and to quickly and accurately perform the necessary actions in response. To perform the test tasks, you need to click on the red circle when it matches the blue one. When performing this test, you can choose one of three testing modes. Each test task consists of three stages. You can choose between 10 to 30 attempts per stage. The demo mode 'Demo' allows for trial attempts. The standard mode 'Main mode' offers a test task where the visual stimulus speed is low in the first stage, increases by 1.5 times in the second stage, and has added distracting visual stimuli in the third stage. The 'Slow mode' offers a test task where the visual stimulus speed is low in all stages. The 'Fast mode' offers a test task where the visual stimulus speed is high in all stages. The program provides the following information about the measurements: - average value of the reaction (by module) for the whole test (Mean, ms), standard deviation (SD, ms); - the predominant direction of excitation or inhibition processes for the entire test ("Premature" - premature reactions, "Delayed" - reactions with a delay, "Accurate" - accurate reactions); - number of attempts in the stage; - test mode; - average values of reactions (by module, ms), standard deviations (ms), Shapiro-Wilk criterion (W) for each stage separately; - percentage of reactions for the entire test ("Premature, %" - premature reactions, "Delayed, %" - reactions with a delay, "Accurate, %" - accurate reactions). This app can be used by athletes and teachers of specialised educational institutions in their scientific research. The “Reaction RMO Pro” app includes an on-device machine learning model (Core ML) that automatically classifies reaction-to-a-moving-object (RMO) performance into sample-derived High, Medium, and Low levels based on the results of a three-stage test. The Boosted Tree model uses nine stage-specific predictors: mean absolute temporal deviation and temporal-deviation variability at each test stage, together with the percentages of premature, delayed, and accurate responses. The RMO_Index is calculated separately from standardised overall mean absolute temporal deviation and response variability, with higher values indicating more accurate and stable response timing. The app displays the ML-predicted RMO level, predicted class probabilities, the separately calculated RMO_Index, and descriptive characteristics of response timing. The High, Medium, and Low levels are sample-derived reference categories and should not be interpreted as universal normative levels or as validated indicators of competitive performance, fatigue, injury risk, or training outcomes. The model provides automated interpretation of RMO test results and may support future athlete-monitoring applications; however, external and longitudinal validation is required before broader practical use. All model inference and result processing are performed locally on the device without transmitting personal data to an external server. Results should be interpreted together with the athlete’s training status, testing conditions, and other relevant assessment data. The app is not a medical device and is not intended to provide medical diagnoses.