A Bio-Digital Twin is a virtual model of an individual’s biological systems developed by Hume. Using data captured from bio-sensors from wearable devices, body composition monitors, and lifestyle information, Hume constructs a digital avatar that visualizes your health. One of the critical features of Hume’s Bio Digital Twin is its ability to explore and analyze your health and well-being and predict potential future outcomes. Your Digital Twin is helpful for many applications, such as creating a weight loss program, preventing metabolic diseases, or managing chronic illnesses like diabetes. Therefore, your Digital Twin helps you better understand and manage your health by combining health vitals and lifestyle data.
How to Use Hume Bio-Digital Twin (BDT)?
You will need access to the Hume Health app to use the Hume Digital Twin. Once you have the app, connect your wearable device and body composition monitor. Our machine-learned AI will then generate a virtual model of your health based on the vast amount of data our scientists used to train it.
Steps to build your Digital Twin:
- 1. Download Hume Health
- 2. Register an account and log in (if you have an account, log in directly using your MyHealth/ Hume Health credentials)
- 3. Sync your bio-sensors
- 4. Select your goals
- 5. Get weekly insights on how you’re progressing toward your goals, learn what’s limiting you, and follow personalized recommendations to continue bettering your health.
Digital Twin Examples:
Let’s take a look at the actual use of Digital Twin first.
The Application of Hume’s BDT
BDT can assist you with a wide range of goals. Some of the potential applications of Digital Twin include:
- Weight Loss: The data collected from your Digital Twin can give you tailored advice on optimizing nutrition and exercise for maximum weight loss results. Additionally, Digital Twins can provide real-time feedback on your progress, so you know right away if what you’re doing is working.
- Prevention of Metabolic Illness: Your Digital Twin can help prevent chronic illness by providing personalized advice based on your health data. For example, suppose your Digital Twin suggests that specific lifestyle changes would help to reduce the chance of developing a particular chronic illness. In that case, you may be more likely to take those steps and try to prevent the condition.
- Management of Chronic Illness: By using machine learning algorithms, your Digital Twin can track changes in your health over time and provide insights into potential health risks associated with chronic illnesses. Digital Twins can also identify trends in a person's health data, allowing doctors to understand better how to prevent or manage chronic illnesses.
- Old Age Management: Your Digital Twin can help you age healthier by helping you identify health risks and make proactive lifestyle changes. Additionally, your Digital Twin can provide medical professionals with a complete picture of your health, allowing them to make more informed decisions about treatments and interventions.
The Limitations of Hume Bio-Digital Twin 1.0
Like any other machine learning model, Hume’s Bio-Digital Twin, in its first iteration, has some limitations. Some of the potential limitations of Hume’s Bio-Digital Twin include the following:
- Dependence on Data: Bio-Digital Twin 1.0 technology is a machine learning model trained by our data scientists using a large corpus of health data, though this is only the beginning. As such, the quality and accuracy of the model’s responses depend on the quality and diversity of the data it receives. If the model doesn’t have a comprehensive dataset, it may generate responses that are not as relevant or accurate.
- Limited Understanding: While BDT 1.0 technology learns from hundreds of thousands of datasets, it still needs to develop an understanding of more health issues. However, with the tool getting smarter with BDT 2.0, BDT 3.0, and beyond, we expect to see a significant improvement over time as it awakens the power of deep learning.
- BDT 1.0 Errors: Artificial intelligence can make some mistakes due to resource or technical limitations. BDT 1.0 continuously learns, and the potential for calculation errors will be reduced over time.
The Hume Bio-Digital Twin technology is a powerful and versatile health management tool that will only get smarter with more data sets recorded.