Summary

Congratulations on finishing the Data Science for Wearables Course! We’ve covered a lot in a very short amount of time.

The material in the introduction to signal processing lesson can fill textbooks. Now you have enough practical knowledge with that material that you can use those techniques to build algorithms from scratch. We then covered the physics underpinning the sensors we worked with and learned about the typical signal characteristics in each of these domains. This is valuable information that is typically only gained with domain experience. With this head start, we went through three case studies of building real-world algorithms on real datasets. From activity classification with the IMU sensor, to QRS complex detection and atrial fibrillation on the ECG, you’ve gained valuable hands-on experience with the algorithm design and implementation process. Now you have enough practical knowledge to apply these skills on your own.

Final Project

In the final project, you will take your knowledge of the PPG and IMU signals and design an algorithm from scratch using the signal processing techniques we have learned in this course. After completing the final project, you will have the confidence to study this field on your own. The journey doesn’t stop here. Download more datasets from Physionet, look for papers that cite these datasets, and try to reproduce their results. Try exploring new ideas and new problems and you will gain depth in this field in no time. The tools you have learned in this course should provide you with a solid base for further study.