Virtual Exercise Experience
These applications are often combined with virtual reality (VR) or augmented reality (AR) technologies, enabling users to engage in virtual sports and fitness activities.
Implementing Pose Landmark Detection using the NuMicro® M55M1 ML MCU
Pose landmark detection technology is an important tool for human movement analysis, posture correction, and behavior recognition. Human features such as head angles, limb movements, and posture changes can reflect a person's activity level, health condition, and athletic performance. By utilizing the latest machine learning software architecture and pose landmark detection models, this technology can run on the NuMicro® M55M1 microcontroller, which is equipped with a Neural Processing Unit (NPU).
What are Pose Landmarks?
Pose landmarks refer to key points identified in a human image, such as the head, shoulders, elbows, knees, wrists, and ankles. These landmarks describe the body's posture structure and movement trajectory and are used to train deep learning models for analyzing human movement, behavior recognition, sports training, and health monitoring.
NuMicro® M55M1 Machine Learning Microcontroller
The NuMicro M55M1 series is a high-performance microcontroller based on the Arm® Cortex®-M55 core, with 1.5 MB of SRAM and 2 MB of Flash memory on-chip. The main feature of this product is its integration of the Arm® Ethos™-U55 NPU, a specialized processing unit designed to accelerate neural network computations. It can perform 256 multiply-accumulate operations per clock cycle and has hardware support for Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), significantly improving the MCU's efficiency and speed in executing machine learning inference tasks.
The M55M1 MCU supports TFLite format neural networks, with models trained in the TensorFlow framework. Using the LiteRT (formerly TensorFlow Lite) tool, neural network weights are quantized to the INT8 format and converted into Ethos-U55 instructions through the Vela compiler, enabling execution on the NPU.
Pose Landmark Detection in Embedded Systems
Pose landmark detection has broad application potential in embedded systems, particularly in posture monitoring, fall detection, and similar areas. With the M55M1 ML MCU, this technology enables low-power, real-time posture recognition, offering more precise movement analysis and health management for users.
For example, in health monitoring systems, pose landmark detection helps identify the user's sitting and standing posture, providing corresponding suggestions based on posture changes. When the system detects prolonged improper posture, it automatically sends reminders to help users adjust their posture, reducing pressure on the back or spine and preventing health problems caused by prolonged poor posture. This technology can also be applied to fall detection. When the system detects that a user has suddenly fallen or lost balance, it immediately sends an alert to ensure timely assistance is provided.
The M55M1 ML MCU combines full controller functionality with NPU acceleration, enabling resource-constrained embedded systems to run complex deep learning models, offering significant practical value. With the help of pose landmark detection technology and the M55M1 ML MCU, embedded systems can more intelligently understand the user's status, further driving innovative applications of AI across various products.
Watch the application design video: Pose Landmark Detection
