, Affordable smart patches revolutionise patient monitoring – light and wireless sensors capable of capturing respiration rate, oxygen saturation, heart rate, temperature and even an ECG
, Affordable smart patches revolutionise patient monitoring – light and wireless sensors capable of capturing respiration rate, oxygen saturation, heart rate, temperature and even an ECG

New High Performance Optical Sensor for Heart Rate Monitoring Ideal for Wearables

ROHM has recently announced the availability of an optical sensor for heart rate monitoring optimized for wearable devices such as sports bands and smart watches. The BH1790GLC leverages proprietary analog circuit technology and optical sensor expertise to improve sensitivity, allowing pulse waves to be detected with high accuracy, even with low LED brightness, resulting in class-leading low power consumption.

Recent years have seen an increasing demand for portable devices featuring greater energy savings and miniaturization. Among wearables such as sports bands and smart watches pulse sensing capability has become mainstream, with new functions continually being added. However, their limited battery capacity makes it necessary to reduce power consumption as much as possible in order to prolong operating time.

In response, ROHM utilizes optical sensor development expertise and IR removal technology cultivated over many years to develop an optical sensor for heart rate monitoring optimized for wearables that meets market needs for low power consumption and high accuracy. A specialized optical filter enables high accuracy detection, extending battery life while reducing the effects of IR rays by 10x vs conventional products. This makes it possible to acquire high quality pulse signals even in environments with strong IR presence, such as outdoors, or under intense movements (i.e. sports), contributing to increased performance and further evolution in the wearable device market.

In addition, an optical heart rate monitor expansion board (BH1790GLC-EVK-001) is available for purchase online that can collect and process sensor information by connecting to an open platform (general MCU board) such as Arduino Uno.

Key Features

  1. Achieves class-leading low power consumption

ROHM combines considerable optical sensor development expertise with original analog circuit technology to improve sensitivity, making it possible to accurately detect pulse waves even with low LED brightness. This reduces power consumption by approx. 74% – the lowest in its class – contributing to longer battery life in wearable devices.

  1. Superior IR removal characteristics enable high accuracy detection

A photodiode matched to the green wavelength ideal for pulse detection is used, along with a filter structure optimized for pulse detection that integrates green and IR cut filters in the receiver block. As a result, high accuracy is achieved while susceptibility to IR rays reduced by 10x compared with conventional products, enabling stable pulse detection even under noisy IR conditions such as direct sunlight or strenuous activity (i.e. sports).

  1. Decreases mounting area by 30%, reducing design load

The BH1790GLC is capable of detecting high quality pulse signals using low VF low brightness LED elements, eliminating the need for DC/DC circuits for LED power supply conventionally required. This decreases mounting area by 30%, lightening development load.

Applications

  • Sports bands, smartwatches, and other wearables
  • Smartphones
  • Devices requiring pulse sensing

Online Sales Information

Products: Optical Heart Rate Monitor Expansion Board

Part No: BH1790GLC-EVK-001

ROHM’s sensor shield makes it easy to collect and process sensor data by utilizing software and connecting to an open platform MCU board such as Arduino Uno.

Specifications

ParameterSpecifications
Current Consumption (LED OFF)200μA
Power Down Current0.8μA
VCC1 Supply Voltage Range2.5V~3.6V
VCC2 Supply Voltage Range1.7V~3.6V
Operating Temp. Range-20~+85 ℃
Package Size (W x D x H)2.8 x 2.8 x 0.9 mm

A proprietary pulse rate calculation algorithm is available.

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