A New Frontier in Health and Wellness: Flow, TensorFlow, and Surface Electromyography (sEMG) for Deepfakes in Healthcare
Earlier in the afternoon while searching Google, I noticed the Google Doodle in honor of Mihaly Czikszentmihalyi, the Hungarian-American psychologist. He turns 89 today and is best known for his named concept of “flow”. This article explores “flow,” the Python library “tensorflow,” and surface electromyography (sEMG) to argue how deepfakes have potential for the positive use in healthcare. Think about curing a stranded space crew member who is feeling homesick and wants to talk to those who are too far from home.
Flow is the mental state where an individual is highly focused and productive. It shows how to aid individuals to reach peak performance.
TensorFlow is a Python Library which released in 2015. Its use has depth for applications such as:
- Image and Voice Recognition
- Text-based Sentiment Analysis
- Generative Adversarial Networks
- And more
Tensorflow is a tool for projects to create production-grade machine learning (ML) models.
Surface Electromyography (sEMG)
This technology is a non-invasive technique to capture and measure the electrical activity of muscles. Electrodes go on the skin surface above the muscle of interest. Convolutional Neural Networks harnessed with sEMG can classify muscle activity and find patterns for spatial distribution, time-series data, and more.