The Smart Wearables Course: AI in Health and Fitness Devices it immerses you in the the vibrant world of portable devices, a a booming sector with growing demand for labour. You will learn how to define and classify wearables, you’ll understand his development and the underlying technologies, such as sensors y collection of biometric data. The applied artificial intelligence will enable you to to train models using physiological data y assess their performance in real time. In digital health, you’ll master the vital signs monitoring and the disease detection, whilst in the field of sporting, you’ll explore the performance analysis and the injury prevention. This course online offers you the chance to purchase key skills in a dynamic market, getting ready for Innovating in health and sport with cutting-edge technology.
Smart Wearables: AI in Health and Fitness Devices
AI Academy
3 pm
Introduction
Objectives
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Understanding the development y classification of wearable devices to identify its use in health and sport.
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Analyse common sensors and how it works for the collection of biometric data in wearables.
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Explore fundamentals of AI y models used on mobile devices for to improve its effectiveness.
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Apply real-time data processing techniques for optimise performance wearables.
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Assess the performance of AI models in the disease detection y health monitoring.
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Identify AI applications in sport for improve performance y prevent injuries in real time.
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Integrate wearables with telehealth platforms y sports apps for a connected ecosystem.
Table of Contents
TEACHING UNIT 1. INTRODUCTION TO SMART WEARABLES
1. Definition and development of wearable devices
2. Classification: health, sport, wellbeing and other areas
3. The most common sensors and how they work
4. Biometric data collection: types and purposes
5. Initial challenges in the implementation of wearables
TEACHING UNIT 2. FUNDAMENTALS OF APPLIED ARTIFICIAL INTELLIGENCE
1. Artificial intelligence and machine learning
2. Types of models used in wearables
3. Real-time data processing and edge computing
4. Training models using physiological data
5. Performance evaluation of models on portable devices
TEACHING UNIT 3. APPLICATIONS OF AI IN DIGITAL HEALTH
1. Monitoring of vital signs: heart rate, oxygen levels, ECG
2. Detection of chronic diseases and prediction of medical events
3. Wearables for monitoring sleep and mental health
4. Telehealth and connectivity with medical platforms
5. Regulation, clinical validation and the security of medical data
TEACHING UNIT 4. APPLICATIONS OF AI IN SPORT AND PHYSICAL PERFORMANCE
1. Analysis of sporting performance using AI
2. Real-time injury detection and prevention
3. Wearables for personalised training and adaptive feedback
4. Biomechanical variables: posture, speed, acceleration
5. Integration with fitness apps and mobile ecosystems
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