MAX32674C

RECOMMENDED FOR NEW DESIGNS

Ultra-Low-Power Biometric Algorithm/Sensor Hub

Low-Power Sensor Hub Family Seamlessly Communicates with Several Analog Devices Biometric Sensors

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Part Details

  • Analog Devices Supplied Software Enables Faster Time to Market:
    • Embedded Algorithms
    • Example Host Microcontroller Source Code
    • Complex Sensor Management and Synchronization Handled by the Sensor Hub
      • Reduces Host Interactions
  • Wrist-Based Algorithms Measure:
    • Pulse Heart Rate
    • Pulse Blood Oxygen Saturation (SpO2)
    • Heart Rate Variability
    • Skin Contact Detection
    • Activity Tracking
  • Automatic Exposure Control (AEC) Is a Multidimensional Improvement to Automatic Gain Control (AGC) that Optimizes:
    • Analog Front-End LED Currents
    • Sampling Rate
    • Pulse Width
    • Integration Time
    • Power Consumption and Performance
  • Both Raw and Processed Data Are Available
  • Software/Algorithm Upgradeable
  • FIFO Provides Minimal Host Interaction
  • Bootloader Facilitates Secure, Authenticated Software Upgrades
MAX32674C
Ultra-Low-Power Biometric Algorithm/Sensor Hub
MAX32674C: Simplified Block Diagram
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Evaluation Kits

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EVAL-STUDYWATCH45Z

Study Watch 4.5 User Guide

Features and Benefits

  • Device Configuration Block (DCB)
  • VSM Suite Library Configuration (LCFG)
  • Low Touch Feature

Product Details

This user guide explains the steps in connecting the ADI Study Watch 4.5 to a Microsoft Windows computer using a universal serial bus (USB) or Bluetooth low energy (BLE) for data streaming or logging, and analyzing the vital signs data using the Application Wavetool software.

ADI Vital Signs Monitoring Watch 4.5 is a product designed to showcase the capabilities of Analog Devices’ biomedical sensors and algorithms for vital sign monitoring.

The Study Watch 4.5 is a wearable, battery-powered device, which enables continuous monitoring and on-demand spot check measurement of photoplethysmography (PPG), electrocardiography (ECG, biopotential based), electrodermal activity (EDA, bioimpedance based), and skin temperature and motion/activity (based on a three-axis accelerometer). The raw sensor data can be parsed through the algorithms embedded within the watch to obtain real-time vital signs such as heart rate (HR), Oxygen saturation (SpO2), and respiration rate (RR).

EVAL-STUDYWATCH45Z
Study Watch 4.5 User Guide
EVAL-HCRWATCH4Z Platform

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