The Future of Wearable Technology and Sensors: Unlocking New Senses and Signals
Summary
The speaker discusses the potential for wearable technology and sensors to unlock new senses and signals that can be interpreted and made meaningful to individuals. They believe that biometrics, which are traditionally understood as medicalized numbers coming from the body, will become a subset of the larger story of personalized data interpretation. The speaker also touches on challenges around utilizing patient-generated data in the medical community, but ultimately believes that the potential for individuals to “feel” or “sense” data in new ways will be a significant shift in human potential.
Table of Contents
- Opening: Unlocking New Senses and Signals
- Biometrics and Personalized Data Interpretation
- Challenges in Utilizing Patient-Generated Data
- The Future of Data Analysis and Learning
Introduction
As wearable technology and sensors become more advanced and more ubiquitous in our everyday lives, it’s important to consider the potential impact that they can have on our understanding of ourselves, our bodies, and the world around us. In this Q&A, we will dive into the future of wearable technology and sensors, and explore the exciting new senses and signals that they can unlock.
Biometrics and Personalized Data Interpretation
Q: How do you see biometrics fitting into the larger story of personalized data interpretation?
A: We see biometrics as an important subset of personalized data interpretation, but not the whole story. Biometrics are often thought of as medicalized numbers that come from the body, but in reality they are just one type of data that can be used to better understand an individual’s health and wellbeing. By incorporating biometric data with other types of data, such as lifestyle factors and environmental data, we can get a more complete picture of an individual’s health and how to improve it.
Q: What are some examples of new senses and signals that wearable technology and sensors can unlock?
A: Some exciting new senses and signals that wearable technology and sensors can unlock include things like air quality monitoring, sleep tracking, and even emotional monitoring. For example, with advances in sensors, we can now track things like heart rate variability and perspiration, which can give us insights into an individual’s emotional states and stress levels. With smart homes and Internet of Things (IoT) devices, we can track things like temperature, humidity, and noise levels, which can give us insights into air quality and overall environmental health.
Challenges in Utilizing Patient-Generated Data
Q: Do you see any resistance from the medical community towards utilizing patient-generated data?
A: There is certainly some resistance from the medical community when it comes to utilizing patient-generated data, particularly around the issue of data quality and accuracy. However, there is also a growing awareness that patient-generated data can be incredibly helpful in providing a more complete picture of an individual’s health, especially when it comes to chronic conditions like diabetes. We believe that as more research is conducted and more evidence is gathered around the efficacy of patient-generated data, we will see a broader acceptance of its use in clinical settings.
Q: Are there certain types of patient-generated data that medical professionals are more willing to utilize than others?
A: Yes, we’ve seen that medical professionals are generally more willing to utilize certain types of patient-generated data, such as blood glucose readings or blood pressure readings, which are more directly tied to specific medical conditions. However, there is growing interest in utilizing other types of self-reported data, such as patient-reported symptom data or even sleep data, to help inform clinical decision-making.
The Future of Data Analysis and Learning
Q: What are some of the challenges associated with analyzing noisy data, and how can we overcome them?
A: Analyzing noisy data can be incredibly challenging, and often requires specialized skills and toolsets that are not yet widely available. However, as more people work with big data and more companies develop tools for data analysis, we expect that basic literacy in data analysis will become more commonplace. Additionally, we believe that there is value in simply making observations and analyzing data, even if we don’t immediately understand what patterns or insights we can glean from it. Often, just going through the process of analyzing data can lead to some sort of learning, even if it’s not immediately clear what that learning is.
Q: How important is creating a community around data analysis, as opposed to working in isolation?
A: We believe that creating a community around data analysis is incredibly important, as it can provide support, resources, and expertise for individuals who are working on data analysis projects. Additionally, by collaborating with others and sharing insights and methodologies, we can develop a much richer and more comprehensive understanding of data, which can lead to new breakthroughs and discoveries. We want to thank the interviewers and others who work to catalyze the data analysis community and create a movement around data analysis.
Conclusion
Overall, the future of wearable technology and sensors is incredibly exciting, and has the potential to unlock new senses and signals that can change the way we understand ourselves and the world around us. While there are certainly challenges around utilizing patient-generated data and analyzing noisy data, we believe that with continued collaboration and innovation, we can overcome these challenges and fully unlock the potential of wearable technology and sensors.
