TRAINABLE AI SYSTEM WITH MUSCLE ACTIVITY AND MOVEMENT FOR PHYSICAL TRAINING AND REHABILITATION
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- POC
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- TRAINABLE AI SYSTEM WITH...
Ziven Active uses wearables to gather data during physical exercises to train ML models, which are assigned to patients. The results are reported back to professionals for treatment planning. The project aims to optimize the models, improve user feedback, and add parameters like HRV and arrhythmia.
Start date: 01/02/2023
Duration in months: 9
Problem Description
The goal is to enhance existing professional-trained generic models, improve user feedback through eXplainable AI, incorporate arrhythmia AI analysis using Lorentz Plot model, and develop new data-driven revenue models.
Goals
New services
Challenges
To make sure the user/patient performs the monitored exercises and receives real-time feedback.
Innovation results
The experiment aims to offer professionals a customizable tool for controlling patients during exercise execution, allowing them to train their own exercises using muscle activity and movement data to feed machine learning models, thereby advancing business models in data services.
Business impact
Confidential