Personalized Exercise Plan

These apps utilize machine learning and artificial intelligence techniques to generate personalized workout plans based on users' physical conditions, goals, and preferences. In conjunction with Nuvoton MCUs, the apps are capable of performing on-device computation and processing, ensuring users' data privacy while providing real-time recommendations and adjustments to maximize fitness outcomes. The MCU technology ensures that users can access efficient and personalized workout plans on their devices without the need to connect to cloud services.

Applicable Development Platforms
NuMaker-HMI-MA35D1-S1	1. Object Detection Example: Smart Gym Equipment Usage Monitoring Deploy cameras inside a gym to monitor the usage status of various fitness equipment in real time. MA35D1 processes the image data captured by the cameras, detecting whether specific fitness equipment, such as treadmills, cycles, or weightlifting machines, is being used. This monitoring helps gym management allocate resources more efficiently and provides a better gym experience for members. 2. Object Classification Example: Personalized Sports Video Analysis Record videos of users performing exercise routines, such as weightlifting or yoga, using a camera. MA35D1 processes this video data, classifying the type and quality of the user's movements, such as standard weightlifting actions or different yoga poses. Based on these classifications, provide targeted training feedback and improvement suggestions. 3. Real-time Recognition Example: Real-time Athlete Performance Tracking System Install high-resolution cameras at an athlete's training facility to capture their performance in real time. MA35D1 processes the image data, recognizing and analyzing the athlete's movements in real-time, such as running posture, jump height, or throwing technique. Provide immediate performance analysis and improvement suggestions, helping athletes optimize their training.
NuMaker-HMI-M467 NuMaker-IoT-M467	1.Vibration Detection Example: Jump Rope Counting and Analysis Embed vibration sensors in the handles of a smart jump rope. Cortex-M4 processes the data from these sensors, detecting each jump rope action and calculating the number of jumps. Able to analyze jump rope rhythm and consistency, helping users optimize their jump rope training plans. 2. Sensor Fusion Example: Multi-Sport Tracking Fitness Band Integrate a heart rate sensor, accelerometer, and gyroscope into a fitness band. Cortex-M4 processes the combined data from these sensors, recognizing the type of exercise the user is performing, such as walking, running, cycling, etc. Provide personalized data analysis for different types of exercises, helping users achieve their fitness goals. 3. Gesture Sensing Example: Yoga Pose Assistance Utilize gesture-sensing technology in a smartwatch or fitness band. Cortex-M4 processes the gesture and posture data from the user as they practice yoga, recognizing the accuracy of the yoga poses. Provide real-time feedback, helping users improve their yoga poses and enhance their practice.
NuMaker-M55M1	1. Vibration Detection Vibration detection technology can be used to monitor body vibrations during exercise, thereby assessing the effectiveness and rhythm of the exercise. The M55M1 development board's high-precision vibration detection capability helps users understand their exercise posture in real time and provides instant feedback on posture to ensure the correctness and effectiveness of the exercise. 2. Sensor Fusion Sensor fusion is the process of integrating data from multiple sensors to provide more comprehensive information. In personalized exercise plans, the M55M1 development board can integrate data from sensors such as accelerometers, gyroscopes, and heart rate monitors to achieve a comprehensive perception of the user's exercise status. This helps optimize exercise plans to meet individual needs. 3. Object Detection Object detection technology can be used to identify and classify different objects during exercise, such as exercise equipment or obstacles. The M55M1 development board's object detection function can help users ensure safety and ensure proper placement of exercise equipment. 4. Gesture Sensing Gesture sensing technology allows users to use gestures to control exercise plans and settings. This improves user interactivity, allowing them to easily adjust plans or perform specific operations. The M55M1 development board achieves a more intuitive control method by recognizing and interpreting user gestures. 5. Object Classification Object classification technology is used to identify different exercise equipment or props to ensure correct use and arrangement. The M55M1 development board's object classification function helps users quickly find the equipment they need during exercise, improving efficiency and convenience. 6. Real-time Recognition Real-time recognition technology can be used to instantly identify the user's movements and performance. This helps provide real-time feedback, helping users improve their exercise skills and performance. The M55M1 development board's efficient processing capability ensures the high responsiveness of real-time recognition, improving the effectiveness of exercise plans.

Applicable Development Platforms

NuMaker-HMI-MA35D1-S1

1. Object Detection

Example: Smart Gym Equipment Usage Monitoring

Deploy cameras inside a gym to monitor the usage status of various fitness equipment in real time.
MA35D1 processes the image data captured by the cameras, detecting whether specific fitness equipment, such as treadmills, cycles, or weightlifting machines, is being used.
This monitoring helps gym management allocate resources more efficiently and provides a better gym experience for members.

2. Object Classification

Example: Personalized Sports Video Analysis

Record videos of users performing exercise routines, such as weightlifting or yoga, using a camera.
MA35D1 processes this video data, classifying the type and quality of the user's movements, such as standard weightlifting actions or different yoga poses.
Based on these classifications, provide targeted training feedback and improvement suggestions.

3. Real-time Recognition

Example: Real-time Athlete Performance Tracking System

Install high-resolution cameras at an athlete's training facility to capture their performance in real time.
MA35D1 processes the image data, recognizing and analyzing the athlete's movements in real-time, such as running posture, jump height, or throwing technique.
Provide immediate performance analysis and improvement suggestions, helping athletes optimize their training.

NuMaker-HMI-M467

NuMaker-IoT-M467

1.Vibration Detection

Example: Jump Rope Counting and Analysis

Embed vibration sensors in the handles of a smart jump rope.
Cortex-M4 processes the data from these sensors, detecting each jump rope action and calculating the number of jumps.
Able to analyze jump rope rhythm and consistency, helping users optimize their jump rope training plans.

2. Sensor Fusion

Example: Multi-Sport Tracking Fitness Band

Integrate a heart rate sensor, accelerometer, and gyroscope into a fitness band.
Cortex-M4 processes the combined data from these sensors, recognizing the type of exercise the user is performing, such as walking, running, cycling, etc.
Provide personalized data analysis for different types of exercises, helping users achieve their fitness goals.

3. Gesture Sensing

Example: Yoga Pose Assistance

Utilize gesture-sensing technology in a smartwatch or fitness band.
Cortex-M4 processes the gesture and posture data from the user as they practice yoga, recognizing the accuracy of the yoga poses.
Provide real-time feedback, helping users improve their yoga poses and enhance their practice.

NuMaker-M55M1

1. Vibration Detection

Vibration detection technology can be used to monitor body vibrations during exercise, thereby assessing the effectiveness and rhythm of the exercise. The M55M1 development board's high-precision vibration detection capability helps users understand their exercise posture in real time and provides instant feedback on posture to ensure the correctness and effectiveness of the exercise.

2. Sensor Fusion

Sensor fusion is the process of integrating data from multiple sensors to provide more comprehensive information. In personalized exercise plans, the M55M1 development board can integrate data from sensors such as accelerometers, gyroscopes, and heart rate monitors to achieve a comprehensive perception of the user's exercise status. This helps optimize exercise plans to meet individual needs.

3. Object Detection

Object detection technology can be used to identify and classify different objects during exercise, such as exercise equipment or obstacles. The M55M1 development board's object detection function can help users ensure safety and ensure proper placement of exercise equipment.

4. Gesture Sensing

Gesture sensing technology allows users to use gestures to control exercise plans and settings. This improves user interactivity, allowing them to easily adjust plans or perform specific operations. The M55M1 development board achieves a more intuitive control method by recognizing and interpreting user gestures.

5. Object Classification

Object classification technology is used to identify different exercise equipment or props to ensure correct use and arrangement. The M55M1 development board's object classification function helps users quickly find the equipment they need during exercise, improving efficiency and convenience.

6. Real-time Recognition

Real-time recognition technology can be used to instantly identify the user's movements and performance. This helps provide real-time feedback, helping users improve their exercise skills and performance. The M55M1 development board's efficient processing capability ensures the high responsiveness of real-time recognition, improving the effectiveness of exercise plans.

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