App: Fitness Personal Trainer Adapt
Developer: Stackwize
Category: Health & Fitness
Price (USD): 0.0
Installs: 5000
Rating: 0.0 (0.0 ratings)
Released: Nov 7, 2023

Description:
Get stronger, lose weight, or gain muscle mass with Adapt! In the gym or at home. Adapt uses science-based training algorithms to help you reach your fitness goals. Adapt will guide you through the right exercises, sets, reps, and weights based on your custom workout to help you achieve your goals just like a personal trainer.

FEATURES
• Personalized workouts based on your training experience, available time and days, goals, target muscles, and equipment.
• Customizable workouts: Remove, adjust, or add exercises according to your preferences.
• Food tracker to track your calories, protein, carbs, and fat based on your goals.
• Easy-to-use interface for tracking meals and snacks.
• Comprehensive dashboard that provides an overview of your daily health and fitness progress.

◆ A personalized plan:
Adapt makes a workout plan for you. It considers your experience, schedule, goals, muscles that you want to emphasize, and equipment. As if it were your own evidence-based personal trainer that you carry in your pocket. And like if you were training with a fitness coach you can remove, adjust, or add exercises you like!

Our training algorithm uses a combination of progressive overload and auto-regulation, two techniques to keep your workout challenging and optimize your results. It takes into account your previous achievements and calculates the next optimal workout.

◆ A food tracker:
Adapt calculates your calories, protein, carbs, and fat targets based on your goals. It's very easy to track your meals and snacks.
You can search for foods by name or quickly add the macros. Adapt will show you the calories, carbs, protein, and fat content of each item.

◆ Dashboard to keep you on track:
The dashboard view shows your daily health and fitness progress clearly. It displays your workout achievements. It also displays your nutrition intake. It shows how many calories, carbs, protein, and fat you consume compared to your daily goals.

The dashboard displays your weight changes throughout the week, so you can see how you're doing with your weight loss or muscle gain progress. You can see how many calories you burn in a day this is based on your weight changes which is the most accurate way of measuring your energy expenditure.

The dashboard can also track how many steps you take each day and how much water you drink. This information can help you understand how active you are and if you are staying hydrated.

◆ Streamlined Interface:
Adapt's design philosophy focuses on simplicity and ease of use. This ensures that you can easily navigate through Adapts features without any unnecessary complexities. This user-centric approach is evident in several key aspects of the app's design: easy to start, progress your workout, or adjust your workout. Quickly track your food, or water intake.

WHY IT WORKS:

◆ Individualized Training: Adapt understands that each person is different. So it creates personalized workout plans based on your body, experience, environment, and goals. This personalized approach makes your workouts challenging and effective, increasing your chances of reaching your fitness goals.

◆ Balanced Workouts: Adapt prioritizes muscular balance, understanding that optimal results are achieved when muscle groups work in harmony. Adapt prevents muscle imbalances and promotes overall muscle development by designing balanced workouts.

◆ Flexible Adjustments: Adapt lets users freely adjust the recommendations it creates because everyone has different preferences and limitations. Users can change the length and frequency of their workouts. They can also replace exercises or adjust their targets for calories, carbs, protein, and fat.

Privacy Policy: https://www.adapt-hub.com/privacy-policy
Terms of Use: https://www.adapt-hub.com/terms-conditions

Classification: AI_FITNESS
AI authenticity label: F
AI function: plan_generation
Evidence: User viewed app; "algorithms" ≠ ML, rule-based