Future design outlook of wearable devices
Authors: Liu Zhiming , Liu Xiangyu 
Published: July 2023

Wearable fitness devices have become increasingly popular among fitness
enthusiasts, athletes, and health-conscious individuals seeking to improve
their overall wellness. These devices have transformed how people approach
fitness by providing real-time feedback and personalized insights into
physical activity, sleep patterns, and other vital signs.In recent years, a
significant focus has been on designing wearable fitness devices that can
accurately track and monitor performance metrics. This has reshaped
sophisticated sensors and algorithms to capture and analyze real-time data.
However, the current generation of wearable fitness devices primarily
focuses on tracking past performance and providing basic analytics.In the
future, wearable fitness devices are expected to become more sophisticated
and accurate in predicting future performance. This will be possible by
incorporating advanced sensors and machine learning algorithms to analyze
real-time data and provide personalized recommendations.One of the critical
challenges associated with designing wearable fitness devices is the
selection of appropriate sensors. Sensors must be able to capture accurate
data that can be analyzed to provide meaningful insights into a user's
physical activity, sleep patterns, heart rate, and other vital signs. Some
commonly used sensors in wearable fitness devices include accelerometers,
gyroscopes, heart rate monitors, and GPS. However, integrating these
technologies into wearable devices contributes to a limitation in the space
of such devices, which may result in reduced user comfort while wearing
them. However, there is a possibility that the monitors and integrated chips
can be made softer in the future. This is also in line with the development
trend of wearable devices, which are expected to become more comfortable and
user-friendly over time.In addition to sensors, wearable fitness devices
must incorporate advanced algorithms to analyze data and provide accurate
predictions. Machine learning algorithms are particularly well-suited for
this task, as they can analyze large volumes of data and identify patterns
that are difficult to detect using traditional statistical methods. These
algorithms can predict future performance based on past activity, identify
areas for improvement, and provide personalized recommendations for training
and recovery. Real-time data monitoring is essential for timely
interventions in the early stages of health issues, facilitating early
detection and intervention, and maintaining long-term health
prevention.Another important consideration when designing wearable fitness
devices is user experience. Wearable devices must be easy to use,
comfortable, and visually appealing. A well-designed interactive interface
can significantly enhance users' interest in wearable devices and their
overall experience while using them, ultimately helping them to achieve
their health goals more effectively.Besides, they must also integrate
seamlessly with other devices and platforms, such as smartphones and fitness
apps.In the future, wearable fitness devices can potentially revolutionize
how people approach fitness and wellness. Real-time performance prediction
can give users a more accurate and personalized view of their physical
activity, allowing them to optimize their training and recovery. Customized
coaching and recommendations can help users achieve their fitness goals more
efficiently and effectively.Overall, the design of wearable fitness devices
and their ability to predict future performance is an exciting area of
research and development. As technology evolves and improves, we expect to
see more sophisticated and accurate devices that provide users with a
comprehensive view of their health and wellness.