Clinical Services

Sleep Clinics
Overnight sleep studies generate vast amounts of data, and involve a wide variety of signal types. Each study typically requires analysis by multiple parties, which can result in a cumbersome workflow without the right data platform. 

The HuNet system captures and stores data in real-time, making it instantaneously available to authorized users. Customized interfaces enable HuNet to work with all existing sleep monitoring systems.

As the data are collected, a variety of algorithmic event identification tools are utilized to improve speed and quality of analysis.
Inpatient Care
Current patient monitoring systems provide valuable data to guide treatment at a given point in time. However, these data are lost as they scroll off the screen.

Huneo believes that all of these data should be available for future analysis. With HuNet's efficient storage techniques, the vast expansion of biomedical data collection is immediately possible. Healthcare providers are empowered to make more informed medical decisions with a complete look at their patients' recorded biomedical history.

HuNet is designed to interface with all types of monitoring systems and devices. The data are compiled into a single patient record, which can be integrated into current EHR systems. 
Wearable Device Integrations
Explosive growth of wearable devices is creating a new class of available health data. 

The HuNet platform enables the continuous capture and storage of data from wearables – ranging from consumer wellness to mobile diagnostics devices. HuNet can be used as a back-end tool or front-end interface to maximize the potential of the large amounts of data these wireless devices produce.
And More
Huneo specializes in customized interfaces to any source of time-series data. Whether for managing patients in a single lab or making comparisons across millions of patient trends, HuNet empowers providers and patients with valuable information. 

Huneo's capabilities in devloping robust algorithms for signal pattern recognition enable improved workflows in any clinical setting.