We are excited to share our latest findings in predicting finger movement and pressure using machine learning. The results show that our model is capable of predicting the finger movement within a Mean Absolute Error (MAE) of 25, which is a sufficient level of accuracy for detecting both the finger movement and the pressure applied.

The system is comprised of a bracelet and label system that captures the data to feed into an artificial neural network.

Bracelet in the background with the LASK label system in the foreground.

These screenshots showcase a portion of the data file available for download, which contains the actual and predicted finger movement and pressure values. Our model not only indicates that a finger is moving but also estimates the amount of pressure being applied, providing valuable insights into the intricacies of finger movements.

This achievement opens up new possibilities for applications that require precise finger movement and pressure detection, such as in rehabilitation therapy, robotics, and gesture-based user interfaces.

We invite you to download the full data file and explore the results in more detail. As we continue to refine our model and improve its accuracy, we look forward to discovering new ways to utilize this technology for the betterment of various fields and industries.

All data to train the model and code available on our Github: https://github.com/turfptax/openmuscle

https://www.youtube.com/watch?v=ZC1migPdiRk

Open Muscle Bracelet.

Comments

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Badbabyboyo t1_jdwreio wrote on March 27, 2023 at 7:28 PM

That’s awesome! Keep up the good work. Most people don’t realize we got voice to text translation technology about as far as it could go in the 90’s and it wasn’t until they combined it with machine learning in the 2000’s that it really improved to the point of being useful. A majority of future human machine interfaces will probably have to be developed using machine learning and this is a perfect example!

turfptax OP t1_jdws798 wrote on March 27, 2023 at 7:33 PM

Thank you!

I have friends with other sensors systems but my goal is also to provide the platform for all types of biometric sensors with labels to be used in a similar vein.

I'm working on the next prototype that can be tested in the field with higher bit ADCs.

The label system was the most important to simplify the problem to be able to test different sensors and configurations.

lxe t1_jdx0adz wrote on March 27, 2023 at 8:25 PM

I've been using ChatGPT to help me with machine learning and data transformation as well. I knew very little of the field, and now with its help I feel like I have a superpower.

turfptax OP t1_je2p7tg wrote on March 28, 2023 at 11:45 PM

https://youtu.be/S3Lz1L-ee3k this is what 5 min of training can do :D

StudentBrilliant3388 t1_je8kijr wrote on March 30, 2023 at 4:55 AM

This is brilliant! And one of the very few projects I’ve seen here focused on rehabilitation or improving the lives of those struggling with new or chronic conditions, it makes me happy. 💗

I wish you all the best in your journey!

turfptax OP t1_jealzsn wrote on March 30, 2023 at 4:58 PM

Thank you!
Everything we produce is open source and open hardware in the hopes that it helps people and makes the resources for the tech freely available to everyone.

I truly believe that machine learning can help humanity and that it will advance so many technologies in the years to come :D