Using Pose Estimation in a Physiotherapy App
Physical therapy is an important part of the rehabilitation process for many patients with musculoskeletal injuries, conditions, and disabilities. However, access to physical therapy can be limited by geography, availability, and cost. To address these challenges, many patients turn to digital solutions, such as physiotherapy apps, to help them manage their conditions and recover from injuries.
The Problem
Many physiotherapy apps currently on the market rely on manual inputs and self-reported data, which can be unreliable and subject to human error. This can make it difficult for patients to accurately track their progress and receive the right treatment and support.
The Solution
Pose estimation, a computer vision technique that uses deep learning algorithms to estimate the pose of a person in real-time, can be used to improve the accuracy and effectiveness of physiotherapy apps. By using a smartphone camera and machine learning algorithms, the app can automatically estimate the patient’s posture, movements, and overall body language to provide a more accurate and objective assessment of their condition.
The Implementation
With QuickPose SDK – GitHub Repo
To implement this solution, the physiotherapy app is updated to include a camera function. The patient uses the camera on their smartphone to capture a video of themselves performing a series of prescribed exercises. The app then uses pose estimation algorithms to analyze the video and estimate the patient’s posture, movements, and overall body language.
The app is designed to detect and analyze several key indicators of a patient’s physical condition, such as posture, gait, range of motion, and overall body language. For example, a patient who has limited range of motion or is unable to perform certain movements may have a more serious condition than a patient who is able to move freely.
Once the app has analyzed the patient’s posture, it generates a report that includes a detailed assessment of their condition. This report can be used by the patient to track their progress and receive personalized treatment recommendations. In addition, the report can be shared with a physical therapist for further analysis and support.
