In research, data access and flexibility are key to producing high-quality results. Fibion Helix takes this principle seriously, offering full access to raw data—giving researchers unparalleled control over their data analysis. Unlike consumer-grade wearables, Fibion Helix provides access to raw, unprocessed data directly from the device’s sensors, which opens up limitless possibilities for analysis, future-proofing your research, and enabling custom insights that go beyond standard metrics.
What Is Raw Data?
When we talk about raw data, we’re referring to the unprocessed, original data collected directly from a device’s sensors. For Fibion Helix, this includes:
- Three-axis accelerometer data: Raw data capturing every movement across all three axes (x, y, and z), providing precise motion tracking.
- PPG (Photoplethysmography) data: This measures blood flow changes, from which heart rate and HRV (Heart Rate Variability) are calculated.
- RR intervals: The time between each heartbeat, key for analyzing HRV and stress levels.
By providing researchers with full access to these raw datasets, Fibion Helix ensures transparency, customization, and the ability to conduct highly detailed and specialized analyses.
Advantages of Full Access to Raw Data
Customization for Specific Research Needs: Having full access to raw data allows researchers to customize their analysis in ways that wouldn’t be possible with pre-processed data. Whether you want to apply your own algorithms, analyze a specific subset of data, or look for particular trends, the flexibility of raw data enables you to adapt your analysis to meet the specific needs of your study.
Future-Proofing Your Research: One of the major advantages of having access to raw data is that your research becomes future-proof. As new analysis techniques, algorithms, or methods (e.g., in AI or machine learning) emerge, you can revisit your old datasets and apply these newer technologies to uncover insights that may not have been possible at the time of the initial study.
For example, advances in machine learning may allow you to train models using your original raw data, helping to discover new relationships or patterns that weren’t evident during the original analysis.
Higher Quality Results: Raw data ensures that your research results are not constrained by predefined metrics or summaries. You can define exactly how data is processed, ensuring higher accuracy and better quality results that reflect the true depth of the dataset. This allows for innovative approaches to data analysis and ultimately leads to more impactful publications.
Comparing Consumer Devices to Research-Grade Wearables
Most consumer wearables like fitness trackers or smartwatches are designed to simplify data for everyday users. They typically offer pre-processed data such as step counts, estimated calorie burn, or average heart rate, with little to no access to the raw sensor data. While this can be sufficient for personal health monitoring, it severely limits the depth of analysis that can be performed in scientific research.
Why Fibion Hlix is Different
Fibion Helix is designed specifically for researchers, offering raw data access to key metrics such as:
- HRV (Heart Rate Variability): Raw PPG data to measure detailed variability in heart rate.
- Acceleration Data: Full three-axis data, allowing for custom activity recognition and motion analysis.
This means that you are in control of how the data is used and analyzed, and you’re not limited by the manufacturer’s interpretation of the data.
Use Cases for Raw Data in Research
Physical Activity and Heart Rate Variability (HRV) Studies
By combining raw three-axis accelerometer data with HRV measurements, researchers can explore detailed relationships between physical activity and physiological stress markers. For example, does an increase in physical activity lower stress levels, as measured by changes in HRV? With Fibion Helix’s raw data, researchers can conduct these kinds of in-depth analyses that provide more meaningful insights into health outcomes.
AI and Machine Learning Applications
Raw data from Fibion Helix is perfectly suited for modern applications such as AI and machine learning. By feeding raw accelerometer data and HRV measurements into machine learning models, researchers can develop predictive algorithms or uncover new patterns in the data. This could be used to, for instance, predict cardiovascular risks, monitor recovery, or assess how exercise impacts stress levels over time.
- Advantage for Researchers: Having access to raw data ensures you can apply cutting-edge analysis techniques as they emerge, making your research more relevant and impactful.
How Fibion Helix Provides Raw Data Access
Fibion Helix is built to provide easy access to raw data for researchers:
- Simple Data Export: The raw data can be easily exported in common formats such as CSV, allowing researchers to immediately import it into their preferred analysis software.
- SDK and API for Advanced Integration: Fibion Helix also offers a Software Development Kit (SDK) and Application Programming Interface (API) for those who need deeper integration with their own platforms or custom data analysis tools. This level of customization ensures that Fibion Helix can be seamlessly integrated into a wide variety of research environments.
Future-Proof Your Research with Fibion Helix
Access to raw data makes Fibion Helix a future-proof investment. As new algorithms and technologies emerge, you’ll be able to revisit your existing datasets and apply new techniques to extract novel insights. This is especially valuable as AI and machine learning evolve, enabling researchers to discover trends and relationships that were previously difficult to detect.
By leveraging raw data, researchers can continue to produce innovative and impactful research long after the initial data collection has taken place, ensuring greater long-term value from each study.
Conclusion
The ability to access full raw data from Fibion Helix gives researchers the power to perform customized, flexible, and high-quality analysis. Whether you’re conducting physical activity research, stress monitoring, or using AI-driven insights, Fibion Helix provides the tools you need to produce reliable and impactful results.
Book a Call with Our Expert
To learn more about how Fibion Helix can support your research, book a video call with our expert.
Frequently asked questions about this topic:
Why is raw data important in research? +
Raw data allows researchers to customize their analysis, adapt to new methodologies, and uncover trends that pre-processed summaries may overlook, ensuring more accurate and meaningful results.
How does raw data future-proof research? +
With raw data, researchers can revisit old datasets and apply new technologies, such as AI or machine learning, to discover insights that were previously impossible to detect, keeping research relevant over time.
What are the benefits of raw data for AI and machine learning? +
Raw data enables machine learning models to analyze detailed metrics like three-axis motion and HRV, helping to build predictive algorithms and uncover patterns that enhance research outcomes.
How does Fibion Helix differ from consumer wearables? +
Fibion Helix provides raw data access for HRV and motion tracking, unlike consumer wearables, which typically offer pre-processed averages, limiting the depth of scientific analysis possible.
What features enable Fibion Helix to provide raw data? +
Fibion Helix supports simple data export formats like CSV and offers an SDK and API for advanced integration, ensuring seamless access to raw data for various research environments.
What research applications benefit from raw data in Fibion Helix? +
Raw data is ideal for studies in physical activity, HRV, and AI-driven analysis, enabling researchers to explore correlations, develop algorithms, and gain deeper insights into health outcomes.