Huami Corporation, a biometric and activity data-driven company with significant expertise in smart wearable technology, announced the launch of the new generation health band, Amazfit Health Band 1S, which delivers new features and benefits powered by AI technologies and brings advanced heart health monitoring capabilities to the smart wearables industry.

The Company also introduced its groundbreaking self-developed smart wearable AI chip, Huangshan-1.  

Utilizing an embedded AI algorithm, the new Amazfit Health Band 1S serves as a convenient extension of established heart health monitoring techniques and offers a battery life of up to 7 days.

For the first time, the new band features self-developed optical modules that provide highly accurate photoplethysmography (PPG) and deliver continuous, real-time heart rate and heart rhythm monitoring. 

The Amazfit Health Band 1S is capable of screening the user's heart rhythm in the background and sending an alert if an arrhythmia including atrial fibrillation is detected.

Once an arrhythmia is detected, the user is instructed to put a finger on top of the band to start a 30 to 120 second ECG recording process to capture detailed heart health data in real time.  

The recorded heart-related data is uploaded to the cloud and users can access medical consultation services for this data via 24 x 7 online and phone channels.

This service is provided free of charge to registered Amazfit Health Band 1S users for the first 6 months following product purchase. Certain conditions and restrictions apply.

The Company also introduced groundbreaking technology in its self-developed smart wearable chip, Huangshan-1.

Based on Open Instruction Set Architecture RISC-V technology developed at UC-Berkeley, the Huangshan-1 is built with four specialized core AI engines: Heart Biometric ID Engine, ECG Engine, ECG Pro Engine and Arrhythmia Engine.

Huangshan-1 is the first smart wearable chip utilizing Huami's self-developed AON (Always On) Technology, which can automatically transfer sensor data to the smart wearable's SRAM inside the chip while making data storage faster and more stable.

In addition, the neural networks acceleration module can compute AI tasks locally (offline). The high performance and low power consumption characteristics of RISC-V make it perfect for smart wearable technology.