A New Frontier in Health and Wellness: Flow, TensorFlow, and Surface Electromyography (sEMG) for Deepfakes in Healthcare
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Introduction
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
Flow is the mental state where an individual is highly focused and productive. It shows how to aid individuals to reach peak performance.
TensorFlow
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
- Robotics
- 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.
The photorealistic Metaverse shows where sEMG and neural networks can take us. Check out the Lex Fridman podcast where he interviews Mark Zuckerberg about the avatars in the Metaverse.
Collision Between Flow, TensorFlow, and Surface Electromyography for Mental Healthcare in Space
At DEFCON31, I had the pleasure to meet Gal Zror. He demonstrated how deepfakes have the ability for real-time scenarios. For more information about deepfakes and their potential use in healthcare, check out https://releif.medium.com/a-new-frontier-in-health-and-wellness-the-intersection-between-super-recognizers-deepfakes-and-3de12746946.
When considering astronauts, a problem can arise. They are too isolated for too long in a stressful situation. If a vessel that orbits Mars has a communication breakdown, and a return to Earth isn’t possible, things could be a problem.
Imagine when the situation could stabilize for a bit, and some are still down in spirit. Therapeutic intervention could take place and the mental healthcare provider can use Deepfakes as the method to support the other crew members. Homeostasis — flow, might be reached. The provider can look and sound like anyone to encourage their cohort.
I suppose the warm memories, sympathy, understanding, and enhanced realism can make the healthcare provider empower the astronaut back to flow. This is a hope of mine.
Summary
Creating heightened states of awareness is a goal for astronauts when using deepfakes in healthcare. Flow might be reached with the help of some requirements such as tensorflow, surface electromyography, and convolutional neural networks. The result is to view photorealistic results with consent for medical use. Prior consent for recreations should be required.
Voice Cloning and the future
Besides perfecting visual stimuli with sEMG, achieving a better output to produce a nurturing, ambient, and realistic effect comes with voice cloning. Come back next week to learn more.
References
- Gold, J., & Ciorciari, J. (2020). A Review on the Role of the Neuroscience of Flow States in the Modern World. Behavioral Sciences (Basel), 10(9), 137. https://doi.org/10.3390/bs10090137
- Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., … & Zheng, X. (2015). TensorFlow: Large-scale machine learning on heterogeneous systems. Software available from https://www.tensorflow.org
- Mueller, N., Trentzsch, V., Grassme, R., Guntinas-Lichius, O., Volk, G. F., & Anders, C. (2022). High-resolution surface electromyographic activities of facial muscles during mimic movements in healthy adults: A prospective observational study. Frontiers in Human Neuroscience, 16, 1029415. https://doi.org/10.3389/fnhum.2022.1029415
- Fridman, L. (Host). (2023, September 29). Mark Zuckerberg: First Interview in the Metaverse [Audio podcast episode]. In Lex Fridman Podcast. https://www.youtube.com/watch?v=MVYrJJNdrEg
