We-Be Platform
All-in-one platform visualize and analyze all vital signals (PPG, EDA, Temperature)
Support all platforms (Windows, Mac, Android, iOS); track all patients/participants data.
Available on all platforms, coordinates among platforms
Inspect in real-time
Monitor Stress
Comprehensive Data Management
We-Be Platform provides sound data management solution from raw data visualization, data denoising to feature extraction and cloud data storage.
The platform is designed with user friendly features including one click drag, zoom in/out, time window segmentation, auto peak detection.
Seamless Experience
Once We-Be is connected to the gateway (PC, mobile phone), data can be visualized in real-time for easy visual inspection.
Simultaneously, the data is synchronized to the cloud and can be instantly accessed by any other devices 24/7.
Extended by Intelligence
With sensors on the band, We-Be platform can derive various implicit vital signals behind them by using AI/ML techniques.
For instance, EDA-based stress detection that is developed by ASEEC lab team at UC Davis, context awareness and blood pressure estimation algorithm that is developed by HealthSciTech Group at UCI are examples of intelligent data that can be realized with We-Be.
One click Machine Learning
The success of machine learning in various applications has led to a growing demand for data scientist and ML practitioners. We realize machine learning in the true sense, so that as much work as possible can be automated and further reduce the prerequisites for domain experties, such that researchers without expertise in the field can use ML to do related work.
Meet all requirements
Off-the-shelf
Cloud Integration
Fully Customizable
We-Be can be used with fully customizable app and cloud development following the detailed SDK.
Case study
Dr. Hostinar is a Psychologist Professor at UC Davis. She is trying to use physiological signals and machine learning to detect stress. She is experts in physiology and stress but not in machine learning. Our team provide an API to feed We-Be collected data to Google and Amazon AutoML so that Dr. Hostinar team could also conduct machine learning analysis themselves.
