It can be difficult to pick the right music for one's mood, so the Actywell ONE headphones have been designed to do it automatically. The headphones use body sensors, environmental data, machine learning, and a massive music database to autonomously pick tracks based on its users' perceived moods.
The Actywell ONE headphones connect to users' smartphones and access their Spotify accounts. They then assess the wearer's "Bio state," as Actywell puts it, to select the perfect song. Bio state is measured through a combination of heart rate and stress levels as sensed through the device as well as other environmental factors like weather, location, movement, date and time.
Users have a degree of control over the device. Though it makes its selections automatically, it also uses machine learning to discover what users enjoy based on their Bio states. Users can also opt to turn the sensors off entirely and use the device like a normal pair of headphones.
What's Driving This Trend
- Automatic Music Selection
- Technology that automatically personalizes music selection based on biometric and environmental data presents enormous opportunities for the music and consumer electronics industries to develop new products and services.
- Bio-data Analysis
- Using bio-data analysis to personalize music listening experiences can be extended beyond headphones or personal music players into health, wellness and sports industries to create new, innovative and market-disruptive products.
- Intelligent Sensor Devices
- The trend for intelligent sensors in wearable devices like headphones with music selection capacity has far-reaching implications for industries that need real-time data analysis such as healthcare, sports and entertainment.
Who This Affects Most
- Music
- Automated music selection based on biometric and environmental data presents new opportunities for the music industry to expand its market engagement by offering music that is explicitly tailored to individual listeners.
- Wearable Tech
- Disruptive innovation opportunities exist for the wearable tech industry in developing personalized sensor-laden devices that modify user experience depending on factors such as biometric, environmental, and situational information.
- Healthcare
- Applying machine learning techniques to bio- and environmental data can provide insights into health outcomes, leading to disruptive innovation opportunities in healthcare monitoring tools and health status alert systems.
